PRB

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Transcript

Aïssata Fall, Africa Director, PRB: To better achieve our development goals and more specifically, we will be talking about budgeting processes in order to enhance Africa’s demographic dividends. Demographic dividends is an issue that is being widely spoken about, and sometimes it seems theoretical or abstract. But today we are fortunate to be able to look at this more concretely and look at some of the processes that have been developed and put into place with the help of the African Union and several African countries to help capture some of these demographic dividends by investing in youth and in women. And our presenters today will be talking about how research in Africa has been helping to better analyze and create tools in collaboration with technical staff from various governments, specifically in French speaking Africa, in order to create these tools and provide them to decisionmakers to help them better plan and be able to really capture the demographic dividends.

We will have Professor Dramani, who is the coordinator of the CREG, in Senegal. He will be speaking to you, and first he will be talking about a tool that is the budgeting tool that is sensitive to demographic dividends. And he’ll be talking about how we can use public expenditures to better enhance these dividends.

Let me give you just a moment. I am having a connection, let me ask you to give me just a minute, 30 seconds, I’m having a connection issue here in Dakar, and I need to switch networks.

I think that is better.

Professor Dramani has his doctorate in Economy from Senegal, and he is a Professor at the University of Thiès and Coordinator of the Center for Research and Applied Economics and Finance -Thies, representing Africa in the National Transfer Accounts Network. He is also the coordinator of the Regional Center of Excellence in Generational Economics, or CREG, and Africa’s representative in the NTA Network. Professor Dramani is affiliated with several universities around the world: University of Manchester, Berkley, Baku State University, University of Cape Town, University of Hawaii, and he’s the author of several scientific and programmatic works. Professor Dramani primarily conducts research on sustainable development through the lens of demographic dividend and generational economics, poverty dynamics, unpaid domestic work, and women’s contributions to GDP. And finally, he works on national and local economic integration. So, I would now like to give the floor to Professor Dramani, who will be speaking to us in French. Professor Dramani, if you could turn on your camera.  Over to you, Professor Dramani.

Prof. Latif Dramani, President and Coordinator, CREG: Thank you very much. And good morning. Good afternoon, everyone. Thank you, Aïssata. And thank you to PRB.

I would like to say hello to everybody, all the colleagues online, all the participants who have joined us on our call today. I see a lot of friends online, and a lot of colleagues from many different institutions. It’s a pleasure to see you and as Aïssata was saying, I’m going to give a brief presentation, opening up our webinar to get our discussion started. We have two presentations today. We have a presentation that will be focusing on policymakers and then also presentations, focusing on researchers who will be talking about some of the tools they’re developing. And we will also be sharing links with all the, for all these tools from NTA that will be of use for the researchers, and especially if they want to get more into the technical and scientific issues. Thank you once again and to Aissata and all the colleagues from PRB for all the work you have done to organize today’s webinar.

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We have been attempting to see how we can integrate demographic dynamics into development policies and the ICPD Cairo resolution has been from 1994, has been seeking to integrate demographic dynamics into these policies as a priority. We also have the African Union’s Agenda 2063, which was launched in 2013. For the Africa we want, which is a strategic framework for the social economic transformation of the African continent over a 50-year period, looking at how we can capitalize on the potential of youth and women. We also have the African Union 2017 Roadmap on Harnessing the Demographic Dividend through investments in the youth. And this roadmap contains four pillars Employment and entrepreneurship, education and skills development, health and wellbeing, which is pillar three and then pillar for law, governance and youth empowerment.

So, this is the framework in which we have been conducting this work looking at demographic dynamics and we are going to be looking at all of these frameworks. The Cairo resolution from 1994, the African Unions agenda 2063. These are all important frameworks to help us, spur this work and give us a basis for all this work that we will be presenting today.

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So, our NTA network has published this was in 2022, published some of the, document about the major, one slide back, please, about some of the major international trends. One slide back. Thank you. So these are some of the major global trends about demographic change and how it impacts the global economy and overall we see that there were six main outcomes in terms of these trends. That, first of all, Africa is the continent that has the youngest population right now, Africa is more and more going to continue having growth. And we’re seeing a huge demographic explosion in Africa. But this is not necessarily the case at the global level or in other countries where the other countries are facing issues of an aging population. So, we are looking at how we can really enhance and maximize these demographic dividends, and where we can best invest our resources in which sectors, which are the priority sectors in an environment where there are limited resources, where can we best invest our resources? So, this overall is the overview that we see from this document about the impacts on the global economy and demographic trends, and looking more specifically at Africa with its young population and how we can benefit from this demographic growth, whereas in other continents we are seeing an aging population.

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In this perspective, there is a whole range of tools that have been developed, and the tools that were developed are aligned with the AU’s roadmap on capturing demographic dividends. So, among these tools, there were tools to analyze and understand the impacts on the economy, the impacts of demographic growth on economic. So, population economics as we said. And because all leaders when they come to power whether it’s in the DRC or Senegal or various countries.  In Kenya, we’re seeing that our leaders are facing this issue of social demands with the new generation because they are more and more demanding and this is a huge problem for many leaders. So, we are developing tools to analyze these pressures. Also, tools to help measure and to monitor demographic dividends. We’ve also been developing tools that will enable us to see how demographic dividends can be better aligned or integrated into national development plans in our countries because, as all economists know, as well as development actors, if we don’t have budgeting policies that are sound and integrated we are not going to be able to capture these dividends. So, we have developed a whole range of tools with support from the NTA network that we are a member of. We have also worked with UNFPA, which contributed greatly, especially in the West African countries. We have, The Hewlett Foundation, that also provided a lot of support in developing these tools. So, we have a number of partners, we have the NTA profile and NTTA profile, that looks at how all individuals produce, consume and share and savings. So, we have about 30 African countries right now who have developed profiles. And then we have the National Time Transfer Account (NTTA), which quantifies and values an unpaid domestic works contribution to the economy. Whereas the National Transfer Accounts (NTA), they examine how individuals produce, consume, share and save resources. But the NTTA focuses more on unpaid domestic work. Also, we have tools that measure the contributions of persons with disabilities, which is often not accounted for.

We also have tools to monitor dividends, which we call the DD monitoring rather monitoring index. This tracks progress implementation and in the African Union’s roadmap through five dimensions. And then we have the GDDI, the gender index, which measures the differentiation of women and men’s participation in achieving demographic dividends. And then we have the BSDD, the budgeting sensitive to demographic dividend, which assesses demographic dividend issues and budget allocation and effective consideration of DD and public policies. So, these are the tools that were developed, and they are aligned with the recommendations in the AU roadmap.

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Here we show an example of some of the results. And this is a result from the NTA. And this is the example from Togo, if you look at the graph on the left in red you have consumption by age, aggregated consumption by age from childhood through working age and then older persons. And what we observe here is that, and this is a country that is an example of what we see in many African countries where we have a youth bulge, and the fact that consumption. Is quite high in earlier years. And this shows that there is a huge problem in terms of being able to meet consumer needs for young people. And then we see that there’s also a surplus during the working age, you see that in light blue where we don’t overcome these two deficits, the two deficits that we see in among youth and working aged person. So, this is part of the analysis from the NTA that looks at the whole population economy to see what trends are occurring in a country. And then we also have the support ratio, where we look at the number of effective producers and the number of effective consumers. So, if everybody works, then you didn’t have the same productivity necessarily. Uh, somebody may be working more hours a day than another person, or somebody may, for example, for a surgeon or a doctor, they might be spending some days just doing medical visits and other days during surgery, saving lives that it’s not necessarily the same degree of productivity. So that’s how we look at effective producers and then effective consumers. This takes into account the consumer needs and the fact that they vary with age. A child is not going to consume the same amount as a young person or an adolescent who’s not going to consume the same amount as an adult or an elderly person. So that’s what we mean by effective consumers. And this is what we’re looking at with the NTA tool and we’re looking at the growth rate and what we call the primary dividends. And overall, this is an overview, a quick overview of the basis for all this work that we have been conducting to look. Of course, economies have a certain life cycle. And we look at the households at the microeconomic level. But then we look at the state at the macro-economic level.

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Here we have looked at this as data that is disaggregated by sex or by gender.

And what you see here is that there is a predominance of men on the market, and that is in the blue line, where you see the men’s average labor income, and then you see the women’s average labor income in red, and you can see that men predominate or dominate in Togo throughout the whole life cycle. There’s a dominance of men over women in terms of the labor market. And so, where the market is, where money is circulating, it is men who are dominating.
And this is illustrated here with the case of Togo.

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So, this looked at the market, but there is another market and that is the domestic market where it is much more about the older types of work you know, so non unpaid domestic work. So, every one of us at home do a certain type of work, even, uh, women, even if they were to have servants, they do certain work at home. And this is not counted within national accounts, but this work is at the very heart of the dividend, because without this work, being done, nobody can get out of the house to go work elsewhere. So, this is very important, uh, you know, this socialization that exists there, there are all these implicit contracts in terms of social cohesion. So, this is a very important work that contributes to the population, but it is not accounted for. In terms of the University of Berkeley, we are attempting to achieve an international harmonization of a way to account for this time used within households. So, we will call it NTTA, the national time transfer accounts. This has to do with all everything we do about women empowerment, gender equality etc.

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Okay, here we see an illustrative example. So, we have this profile that you see on the screen that shows you the number of hours per week that are produced and consumed. So, the dark red line, that is the position of time in women. So, you see that woman, produce a maximum of 20 hours per week, let’s recall that 40 hours as a work week. If you look at men, their maximum is six hours, seven hours per week.

So, if you look at 15 years old or 20 years old, you will see that young women and their male equivalents, they produce much more domestic work in terms of time. And this really, you know, so in the SWEDD project, we’re currently really looking into dropping out how why women drop out of school. so young women are dropping out of school not because they want to, but because there is this amount of time that is part of socialization. That is because they are women. So, they have, say, 15 hours of work. So you have a woman who is at university, she has to spend 20 hours working in the home. This is enormous. So and this work is unpaid. So it is not accounted for within national accounts. It is almost invisible work labor. And then, you know, when we talk to parliamentarians, you know, like in Senegal, we were told, oh No, we must say that this work is not used in accounting. So first we have to acknowledge that women do a lot of work. And this is what we’re going to detail here. Everybody works for a number of hours, but not everyone produces during these hours. So, you know, when you have young children or elders that you have to take care of, that is one thing.

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So, we looked at a few countries that are represented here. So, we looked at Niger, Cote d’Ivoire, and a few other countries in terms of paid work and unpaid work. So, what you can see here If you look at, you know, the production of type like for example, in Cote d’Ivoire and Niger so we showed that in could Cote d’Ivoire we had the weakest estimates in terms of time, in terms of domestic working time. These were the lowest amounts, this is tied to socialization in Cote d’Ivoire. In Niger we found the highest times. And this again has to do with the socialization in Niger, because the fact that from a sociological standpoint women get married very early, very young. And so in terms of time you know, they have around six children on average. So you can imagine it takes time to take care of that many children. And they get married very young, around 16, 17 years old and so between that and up to 45 years old, they’re spending all this time. So, this takes time and, and all the other domestic work that they have to do. So that is what we’re trying to illustrate here. Here we have a deficit of care because in the. Here we see a lack of sufficient care throughout the life cycle. So, this is care for young children and elder individuals. And this is shown on the slide.

So, there we did a quick we took stock of the NTA and NTTA, this is very the basis of the work that we are doing. And the African Union has asked for the creation of an index for the monitoring of the demographic dividend. So this is how the DDMI was established, which is made up of four pillars, uh, with five dimensions. So pillar one was employment and entrepreneurship so this pillar one is covered by three dimensions of the DDMI, economic dependency. That is the first one dimension to is quality of living conditions and dimension three is poverty transition. And then the second pillar about education and the development of skills, and then the pillar on health and well-being, which is, um, fueled by dimension four, which we’ve talked about, which we’ve called extended human development, which makes us able to see the human and development at the national and subnational level. And then we have of course, rights, governance and youth empowerment. This is fueled by dimension five and also dimension two. And this is everything that has to do about, the arrangement of the territory the having potential opportunities at the national level, not just in some regions, as we see in most of our countries at this time. And the fact that people must have access to services, young people, women must have access to reproductive services, health services, infrastructures, transportation services, financial services, for example, throughout the entirety of the country’s territories. So that’s dimension five of DDMI. And we have results for about a dozen countries in West and Central Africa.

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So we have GDDI and its gender specific version because we know that women represent 51 to 50%, 52% of the population in general. So, we saw earlier with Togo and what we saw for Togo is pretty much what we see throughout Africa. We have inequality between the genders. So, the DDMI index was divided by gender. So the GDDI gender, demographic dividend and to see how we could budgetize to take care of national issues, but also taking care of this 52% of the population. That is enormous, because as we saw it, is the women who contribute the most to socialization and do all this unpaid work that is not accounted for at the national level. So, this can represent 10 to 25% of GDP in countries. That is the estimate we have for the region.

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So, this brings us once we developed all these indexes. So we have the basic preferences that show us where things are not going well. So we can go okay. It is not going well here. But the plan, the diagram is not complete. When you look at this diagram, you can see it’s incomplete as someone who is a policymaker, etc. And then you have issues of equity, territorial planning, etc. you have equity issues. But the question is what do you do with all this? So this is where Democratic Dividend sensitive budgeting originates, because it’s not just a we can’t just stop here. You know, this gives us a diagnostic it tells us what to do. But how do we do it? We need public resources. Demographic dividend sensitive budgeting is because we are talking about public funds everything that we know about economic theory is that the state is the sole guarantor of collective good. A private person cannot create and build an airport. It will be his airport. It will not be a public airport. So when we’re talking about public funds, they are what is going to be used to take care of all these problems? How to use these resources to obtain the benefits of this demographic dividend. So, the DDMI that we talked about with five dimensions, it is very much a diagnostic tool, but it’s not really legible for those who take care of budgeting, those who are in charge of public finance, they really want things to be very clear for them. This is why the BSDD was created. So, this is about budgeting, we broke down the index so that it could become understandable to our friends who create budgets within our countries. So we created four components that can be used by any country. The first one, the first component is human capital, then second governance, then economic structure and the fourth component is network. And within each of these there are two functions, first education and health, which fall under human capital. Under governance you have institutions and security, under economic structure you have economic affairs and infrastructures, public works, energy and then networks you have specialized networks, which we call social networks and professional networks.  So this is the normal type of nomenclature that can be understood by people who take care of budgeting. And this is actually informed by the DMI. So here we have this results indicator, the DMI, which is now anchored to the budget via this table. These four components. so this is the very core of what we want to talk about today. We this was what was asked for by our leaders. You know, we know we have finance. We have a growth in the youth population, but we must establish priorities. You know, in a developing country, everything is important. So what is the priority? So this work has been done to establish where the priorities lie in terms of budgeting, where do, where must authorities make strategic investments, you know, and where do these authorities, decide that they must do very specific things, things like commercial plans, essentially, have a total rupture from the past.

So here these are the first results of BSDD demographic dividend sensitive budgeting. This is the structure of budgets. So when we analyze the budgets of our countries, when we talk about, you know, it’s often analyzed in terms of percentage of increase of growth. Yes. Growth is important, but what is even more important is the weight of each sector within the budget. So, when we talk about demographic dividend there are very simple things we can observe. So the dividend first must have a well-educated population that has skills and that is in good health. So there you will see the columns that are labeled education and health. What do you see there? So that’s the head. That is the top part. It is well formed. So now I must have an economy that can support this so that the infrastructure, you know the buildings and public works, etc. so we can have an economy without energy to, for example you know, create electricity and manufacturing etc. So that is very important. So on top we have education, so that’s the head of the body. Then we have the spinal cord is the structure of the economy. And then we have governance coordination, So we have security, So we have laws. And then finally we need social cohesion. We need specialists, And that is your networks. So, you have the head, the spinal cord, two feet and two hands. So when you look at the structure, we observed that in our countries we allocated many more resources to institutions. Institutions consumed a lot of the budget. You know, look in, in comparison to the resources that so for example, the resources allocated to institutions and the resources allocated to health there you can see there is a problem. If you look at both those columns. Now, when you talk about gender, that’s about social matters. And look at the portion of the budget that is allocated in the various countries, to creating gender programing, you know, about gender equity to empower women, in order to improve the system. So then you have the social networks.

So apart from Mauritania, things are not going very well in that aspect. So this enables us to tell the authorities because you know, we’re talking about public expenditure. This is everybody’s money. So we need to tell the authorities things are not going right without, we can’t really benefit from the dividend in this way. We really need to change how we allocate resources. So that is an initial analysis of the first results of the first results that we have found in terms of the various countries noted on this slide.

So I talked about the various countries on the previous slide, but this is an average of all our countries together. So, you know, we have about 12 countries that we averaged out to get to these results. If you look at the budget structure you have 100% there. And then you can see how these budgets are allocated. So, you will see more specifically. So the budget does what you know is it used to invest. Is it used for operation or for transfers? I’ll take the line on Health First because without health you can’t get anywhere. So, let us talk about health, you have 6% in total on average between all these countries, when you look at the investment column, you see 1%. So as an economist, if I am not even as an economist, we can see that we do not have a good medical basis. We do not have the materials to achieve health within the population. So even if we have staff, we have personnel they cannot do anything because you need to have equipment to achieve health. So, we don’t have adequate medical equipment for our reality now. So the average is 6% but then look at institutions now just going down one line, that’s 32%. That is five times more, So institutions were originally created to coordinate the system, yet we see that they are taking up a lot of time, a lot of money. They are at 30% for investments, so 13 times higher than health. So, investments for institutions, it’s usually often equipment, cars, that sort of thing that is purchased. but it is more important for human capital to do a strategic investment rather than investment in these institutions. So we have countries undergoing crises. Well, so look at what is there. So we’re, you know, and then there’s the other sectors, sectors that are just sort of left aside. So we have a lack of balance among our budgets, basically we cannot benefit from the dividend with all this you have, it’s the institutions that are taking up most of the budget. There is no money allocated to health, to human capital, to education and you see that governance is actually more weighted than the economic structure. And so I am therefore a man whose spinal column could not support its arms if we do this body analogy. So basically, that means that we cannot stand as such because the spinal column cannot support the hands. So the spinal column is the economy. So, you have 14%, 10%. So these countries cannot stand up on their own feet until they can, really fix this issue and balance out the structure.

These are the initial steps of BSDD. They are the easiest to use, especially for policymakers and for everyone. Because okay, so you have public funds. This is our money. This is everybody is concerned by this. So we establish we provide the reasons why things are not going well. And these can be verified, because this is work that is done with various countries. It is done in an anonymous manner. So now is important to talk about issues of collaboration to bring about change because it is not obvious, but everybody has got to play their role. We have various stakeholders. So you have the sectorial ministries, you have the parliamentarians, you have civil society, you have researchers and the entire society. Everybody has to play their role because we learn while talking with parliamentarians that when they say that they can’t take on a problem if civil society doesn’t tell them, hey, there’s a problem here. And from a technical standpoint, we must strengthen the different sectorial ministries so that we can really start creating these services for our Populations strengthening skills, have communication an advocacy so that things can change. Especially, I really emphasize health because I really think without health, you cannot even begin to change things. Um, you know, the previous column we saw, we were about around a dozen countries where at about 6%. So there’s a lot of work to still be done. So we need for the tool to be truly used by the budget team so that they know that when they allocate resources, you know they are allocating resources for the development of their countries, but you can’t do it haphazardly. You need to find out what sectors you must invest in order to have results. And so this this tool can really allow us to seize upon this dividend. We have the youth, we have the young people, and they’re going to be around for quite a while, you know, but in 20 years, they’ll be 20 years older.

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I really want to thank the SWEDD project and I want to, thank you the UNFPA, the Hewlett Foundation on the Counting Women’s Work, but they also supported us in our research and, and the fact that we were able to do this research with thanks to the Hewlett Foundation. We had Gates Institute also supported us in achieving these results. So thank you to all the stakeholders. Because what I just presented, this is 10-12 years of research work. And, you know, it may seem simple, but it’s it really represents 12 years of work for all from all these partners. So UNFPA, WCARO, Hewlett, UNECA, Gates Institute, etc. and of course, all the other partners we may have forgotten. The NTA network also has been a supporter since the very beginning, well before this program in order to really work on fundamental research on and as a applied researcher. Thank you so much, sorry, I took a little too much time. Thanks again Aïssata.

Aïssata Fall: Thank you very much, Professor Dramani. It was necessary for you to take that time. Professor Dramani, I cannot explain all the technical details. It is not really useful for me to repeat them but I think that this information is really important for us to continue having engagement. Engagement of all the member states of the EU, for the roadmap, for capturing demographic dividends, because this is going to be absolutely essential to really be able to capitalize on the youth contribution to this kind of these countries economies. We can also see the overall trend on the global level that these demographic trends are having an impact on economies. And we can’t ignore this. It is absolutely necessary and this started already back in 2014 when we were looking at this issue as part of a development issue.

Analysis show us and thanks to the work that we’ve done with the NTA and the NTTA, the analysis show us what is driving countries’ economies in terms of investments, but also not only money, but investments in terms of time. And this shows us we can’t ignore the fact that time is also a fundamental investment in order to have it. And we have to really have a good vision of the labor force in our countries, but also the policies that are going to allow every person, man or woman to be able to contribute to productively and fully to the growth of their countries’ economies. Another essential element, I think, is that in Africa, we have to look at the budget resources of states and in most cases, the government, the state is the main employer, and the private sector does not always dominate the market. It is more the public sector and so we need to see how we can also maximize the effectiveness of these tools and budgeting tools and processes. So now we’re going to be talking with some of our panelists who are representatives of their governments, who are talking, who are going to be talking to us about their budgeting processes and how they’re using these to capitalize on demographic dividends and before moving to our panelists, I would like to look at a few of the questions that we had for Professor Dramani, we have one question saying, when you look at the gender differences in terms of time spent on work, we can see that the differences start at a very young age. Is this a gender socialization issue, or is it an issue of early marriage? Or what are the issues that make this separation appear so?

Put a question in the Q&A. Could you retype in your questions please? And I will ask Professor Dramani to ask the first question that I had just asked right before we got cut off. Did you hear the question, professor Dramani? No. Could you repeat it again, please? Yes. The question. I’m not entirely sure I remember exactly what it was, but the fact that we see the set of this differentiation at a very young age in terms of time and is this different use of time, is this big difference at a young age? Is this because of working time? Is this because of socialization? Is it because of early marriages, or are there other factors that explain this different gender difference at such a young age? And what are the problems that we can see? What are some of the barriers in terms of the difference of time use at a very young age for between paid work for girls and boys.

Prof. Latif Dramani: Yes. Would you like me to answer?

Aïssata Fall: Yes. Go ahead and then I will follow up with the other questions after.

Prof. Latif Dramani: Yes. Thank you. Aïssata. What we see from the results of our analysis, and we’ve been working with all the different national representatives from the countries that we’re working with, to maybe also, give us some way in as to explanations. How do we explain this? Is it because in many of our countries, we have observed that there is this difference, starting at a very young age, especially in the countries we’ve observed this, and we see a very a different set of very young age between young girls and young boys. And this is probably most likely due to social norms and cultures. There are certain domestic activities that girls do that boys don’t do. And this is just something that is hardwired into social norms, if you will, that women have, work that they do a household work that is expected of women. So, I think that this is probably what really explains it, this division of labor that we see at a very early age because of social norms. So, I think it’s mostly socialization in the various countries. Then we can also see that when we look at countries in the Gulf region, for example, that changes quite a bit. There are differences, but they’re not quite as marked. And this is this is the answer I can provide as of now. But we have asked for the different country teams that have been doing the NTA and the NTTA. We’ve asked them to also consult with sociologists who can help give a shed light on this phenomenon that we’re observing and give us more explanation, because this is something that we do see quite clearly in many countries. It’s not something that we see that changes really from one country or one analysis to another. This is something that we really see that in every country across these this region and so I will stop there. But I that is my answer.

Aïssata Fall: Thank you very much. Let me take a second question now.

What is the strategy that could be implemented in order to urge our states to change these trends? We have talked about investing more in education and in health, but nothing is happening. What can we do to what strategies can we use to really pressure our governments to make these changes?

Prof. Latif Dramani: Would you like me to answer? Is it good?

Aïssata: Yes. Go ahead please.

 Prof. Latif Dramani: Well, I think that one of the main things we see is that we have to, first of all, get the results more widely disseminated because we see often that our ministries, this is not something that people are talking about. It’s not being analyzed in terms of the state budget, It’s awful. Often looked at just at the growth rates. The budget is growing and it’s being looked at from that point of view. But it’s not necessarily looking at how this impact is affecting the budget. And often this is what the politicians are looking at, the minister is saying, well, we get a little more money, so we’ll give a little bit more money to health or if we get a little bit more money or money, rather, we can give a little more money to the health sector. But in terms of structural changes, things are not really changing much. So I think that we need to, first of all, start analyzing this from a structural point of view, looking at the structures, because in terms of our budgetary policies. Things need to be trending upward in terms of our structural policies, but you have to look at whether you’re investing 10%, 5%, 25% and that and then if there is a growth rate, you have to look at it and say, why are we seeing budget growth? Because unless there are budgetary shocks such as crises, wars or so forth, all the aggregates are generally on an upward trend over time and this is because social demands, the basis is growing, the population is growing. And so the needs that have to be a matter also growing. So if we don’t look at the structure, if we look at only growth rates, which is often what we do then we’re not going to be able to really implement these changes. We have to change the way we analyze it. And ministries and the sectoral departments and regional departments have to look at how this is impacting the budget. Because if you look at a certain sector and if they don’t have sufficient resources, it’s going to fail. So often it’s because they haven’t been given the resources, they need to do the work that needs to be done. So in health or education, if they don’t have the resources, if we want to make progress, we have to have a clear basis and we have to have a good structure in place.

And then once we have these structural policies in place, then we can look at how things are progressing and how we are improving public expenditures.

Thank you.

Aïssata: Thank you. For people who had posted questions, I am sorry, but we have a lot of questions, and we don’t have a lot of time left. So, some questions are more country specific. Why Senegal invests this or why Mauritania doesn’t invest that and so forth. So rather than discussing individual countries now, we will provide answers by in writing after our webinar. But we are going to try to look at some of the more general questions today.

I think this important for us to look at issues of. And this is a question in English it says, how can this information be used for advocacy and what are the desired outcomes over the long time? So these are the types of questions we would like to ask of our panelists today who I’m going to introduce shortly. But the other questions, we are not going to forget the other questions. And we will provide answers after. But what I can say for now is that, yes, these results are in tools are publicly available and they are intended to be meant by or intended to be used by governments and policymakers. This is the fruit of about ten years of work. But these are tools that are now newly being used in the budgeting and planning, uh, areas. And we’re trying to see how social sectors can not only use these results, but also use these mechanisms to better understand these budgeting processes. And this is of course related to the quality of the data and how the data is being used. For me, in terms of social protections and demographics, I think that the use of these tools and these results is useful because these are tools that are going to help governments have concrete tools to help better plan their budgeting processes. But it’s also a way to validate the work of technicians, researchers who have validated these tools as being effective tools. And by usin the data that we have, we will come back to these questions. We will provide answers in writing after the webinar, as I said, but we don’t have a lot of time left. So I would now like to continue with the next section of our webinar. And we will have a roundtable discussion with four people, who are directly involved in using this data. And they will be giving us their opinions about how useful this data can be and these tools for policies and decision making.

We have, first of all, Mariama Fanneh, who is a Director of the National Population Council in Gambia. She is with the office of the Vice President in the Gambia. In this role, she is responsible for coordinating the national population policy and programs, including the UNFPA funded country program. As Director, she also leads the National Observatory for the Demographic Dividend in The Gambia. Currently, she is a part time lecturer in public policy at the Management Development Institute, and her career includes positions such as Assistant lecturer in Management and Economics at the University of the Gambia and other schools. She’s currently pursuing a PhD in Public Administration at the University of the Gambia focusing her research on harnessing the demographic dividend through youth and women’s empowerment in the Gambia. She holds a Master’s degree in Business Administration from Clayton State University in Georgia, United States, and a masters in Population Studies from the University of Ghana, and she also has a bachelor’s degree in Economics, and she has also led significant research projects, including a national study on COVID 19 in The Gambia. And she’s worked on several initiatives related to youth and women empowerment.

Next, we have Pr. Germaine Anate, who is a full professor in information and communication sciences, and she is the director of the center for Studies and Research on Organizations, Communication and Education at the University of Lomé. She is a member of the National Assembly of Togo, and she has also served as Minister of Communication, Culture, Arts, and Civic Education. In addition, she is deeply involved in humanitarian and associated organizations. In this capacity, she chairs the Board of Directors of the NGO care solidaire, where she advocates for the empowerment and development of youth and women through, among other things, leadership training, communication techniques, and efforts to combat gender-based violence. She is also the president of the Togo Writers Association, and she’s published several articles, scientific works, and literary books.

Next, we will have from Burkina Faso, Dr. Larba Issa Kobyagda, who has a Ph.D. in economic sciences and a background as a financial economist. He has held strategic positions within the Burkinabe public administration for the past ten years, including at the Ministry of Economy and Development as a lecturer and assistant professor in economic sciences at Thomas Sankara University. He’s also a member of the research team on the global economic policy issues, and has authored several scientific publications on economic and financial policies. Dr. Larba, as Director General of Economy and Planning, is responsible for coordinating tools to support the effective management of the economy and development, as well as overseeing the monitoring and evaluation of public investments. Additionally, he serves as the coordinator of the National Observatory of the Demographic Dividend of Burkina Faso, where he conducts studies and research in generational economics, advocates for policy, and strengthens national capacities in monitoring demographic dividends.

And finally, from Mali, we have Mr. Moussa Sidibe, an agro-economist and local development expert, who is the national coordinator of the World Bank’s Sahel Women’s Empowerment and Demographic Dividend, or SWEDD project in Mali. Moussa Sidibe holds a degree in agricultural engineering and rural engineering from the Institute Polytechnique Royale from Göteborg in Mali, and a master’s degree in analysis and evaluation of agricultural, social, industrial and environmental development projects from the School of Economic Sciences of Rennes one, France. He has over 30 years of experience in social economic development, particularly in rural areas, working with NGOs and consultancy firms. He is conducted several expert missions for development partners in Mali, Africa and Europe, and since February 2016 he has been coordinating the SWEDD Mali project, which focuses on population issues, human capital, and particularly on women’s empowerment and the demographic dividend in the Sahel.

I am going to ask our panelists to turn on their cameras if possible. But I know that sometimes the connections don’t allow for your videos to be on. But so if you have the bandwidth and can turn on your cameras.

Great. I see, Dr. Larba and Professor Aneta. Moussa, are you able to turn on your camera? But if you’re not, that’s fine. No problem. And then I also see that we have Ms. Astou Diouf, who is a legal expert with degrees from the Cheikh Anta Diop University in Senegal. And she is currently the national director of Gender Equity and Equality since November 2019 at the Ministry of Family and Solidarity. With a rich experience of 19 years, she has held various leadership roles in the sectors of women, children, family and gender. She has worked in promoting women’s status, managing legal affairs, and directing programs related to gender equity and equality. As a national focal point for ECOWAS, she is played a key role in initiatives concerning women, peace, and security. Her career demonstrates a deep commitment to improving the living conditions of women and families through an approach focused on equality and social inclusion, and Miss Diouf holds a master’s degree in finance and public management, a master’s degree in defense, Peace and security, and a masters in Environmental law.

So I would like to start with our questions for the panelists, and I’d like to ask you to try to answer your questions in just 2 to 3 minutes. we have had a few connection issues, so we lost a little bit of time. So if you could be very brief with your answers, that would be great. So we’ll try to pretend as though we’re not in West Africa with the connection issues. And I don’t think anybody’s going to be too traumatized by the fact that we had some issues and are running a little late. But first of all, and before I ask my questions, I don’t know if everybody I don’t know if all the panelists can turn on their cameras if possible. Okay, great. Thank you. Now I see you all. Oh, for those who are able to.

To begin, I would like to ask this question to Mr. Larba from Burkina Faso, Miss Diouf from Senegal, and Miss Fanneh Gambia. And when we look at this process the BSDD and we see that it’s a long process and we’re looking at the demographic dividends and the final results. We have all these analyzes that we’re doing, the NTA, the NTTA so forth. And we’re also looking at the different indicators and the indexes that are allowing us to align these analyzes with the African Union roadmap. So I’d like to ask if you could explore the concrete impact and benefits. And can you provide some specific examples of how the BSDD has influenced your decisions and improved outcomes in economic development and gender equity?

So for Dr. Larba, Burkina Faso is rather advanced in this BSDD process. So can you maybe talk about which BSDD tool has most influenced your economic decisions and development? And if you look at how things were done in the past, how things have changed over time. Thank you.

Dr. Larba Issa Kobyagda: Thank you, Aissata, for giving me the floor. And thank you to all the other panelists for being here today. Thank you for to Professor Latif, for your great overview, which really gave us a good idea of what we can do from a technical point of view with the BSDD. I’m going to answer the question directly for Burkina Faso. Looking at population trends has always been a major priority. But of course, now with the tools that we have this has helped us better develop our strategies and we’ve been working with the CREG to develop our BSDD profile, which we did in 2018. This profile showed us that for the five different dimensions that are measured in this index, Burkina Faso did not achieve more than 50% in any of these different dimensions. And we see that we have a lot of work to be done in order to really capture the demographic dividends and to make more real progress. So this process was conducted looking at budget sensitive demographic dividends. And we were looking at how we could take economic shocks into account in our budgeting processes. And as we looked at the BSDD, we were looking at the country’s profile and so the BSD, the advantage is that it gives us more opportunities to look at expenditures and to see how we can better invest our public, our public funds into improving the wellbeing of our population.

It also helps us to analyze our budget from a functional point of view and also looking at the impacts of productivity of expenditures by different departments and sectors. And it also looks at efficiency issues and which expenditures have greater impact.

So these types of analysis have been difficult to do with the classic with the traditional budgets but when we look at the traditional budget up from 2017 up to 2020, when we look at the demographics, we see that efforts were done by countries. But these efforts didn’t necessarily take into account the different economic shocks that we sell in the various countries, and we saw that the proportions were relatively low in terms of investments in education and health. But there was a clear improvement in terms of the health investment from year to year.

And from 2.5 from 212, we tremendously increased from 2021 to 2023. And these, you know, are weak compared to what is really expected. So the country told itself, given its current, security crisis, it is good to intensify the use of BSDD, so that budget allocations in the favor of human capital may lead to better health. Now, when we examined budgetary flexibility in terms of the BSD process, we had effects. We saw different effects of these allocations in terms of health or education. Nevertheless, this means that the country has done a lot of effort to work for youth and the female population in agreement with the African Union efforts. So this means that we have been able to undertake a political dialog with the Directorate of Budget Institution, the National Assembly, etc. to take BSDD into account in the 2025 budget. So we look at these strategic choices that were documented in the multi-year budget document for 2024-2026. This BSDD is important and has been brought to the attention of the government. And so. We have had comments about the taking into account of BSDD. So the 2025 circular has taken into account BSDD as an innovation in the creation of the budget to implement in a progressive manner. So we’re talking about demographic transition and how to take advantage of the demographic dividend by 2025. And this is what we are working on to ensure that this instrument brings us a better solution to the things that concern young people and women.

Aïssata Fall: Thank you very much, Doctor Larba. Interesting. When you were talking about how the process made it so that you could highlight the efforts and broaden the political dialog so that for you, even within the government, this really enables you to do better advocacy work.

Miss Astou Diouf from Senegal, if you could talk to us about your opinion about how the process, the BSDD process had changed the national digitization culture within Senegal. We have participated in multiple sessions together. So we’ve talked about this. I would like to know, what do you think about this process and how it has changed the budget budgeting process in three minutes, please.

Astou Diouf: Thank you so much. Miss Fall and members of the panel. Yes. My mic is on. You can hear me.

Aïssata: Yes. Yes, we can hear you.

Astou Diof: Yeah and thank you to the CREG for your presentation. And then thank you for Burkina Faso there is moving in the right direction. And Senegal is working on establishing the means and ways to implement BSDD. And we want to see the methods of application for BSDD. Now in terms of structuration as a function of the budget we have. We are aware of the study published by CREG recently, Senegal. You know, if you look at the various functions human capital, economy, governance, etc.. There is a single dimension that is at 52% for us, it’s the human capital where we talk about the main levers of the demographic dividend for education and health, where 22%. So the figures that have to do with these various dimensions are important for us. And we were able to note an interesting trend between 2011 and 2019 in terms of performance. But given the things that have happened on the past few years with political tensions we are not certain that this trend has been confirmed. Um, the situation has led us to open dialog with various actors. Beyond the studies, we are communicating with this key sectors and we are also undertaking a series of advocacy efforts with the sectorial ministries, the parliament, civil society. And so these will be cooperation sessions that are going to be ongoing. Now in terms of budgetization, we feel this is a good opportunity to address indeed this this issue of the BSDD by and also in adhering to what is of most interest to us now in analyzing DDMI for Senegal, we saw that it remained very weak among women 35.4% among women in like 47% among men. So we have a lot to do, to catch up. And we are one of the countries that joined up with SWEDD project and so we want to pursue the ongoing objectives to really undertake BSDD. So this means that we must raise awareness among policymakers and also we must increase capacity build among the various actors. And this is where the CREG does a lot of work with to enable us to put in place BSDD and to really reduce inequalities between the genders.

Thank you.

Aïssata Fall: What’s interesting is, once again, we are hearing that BSDD is an interesting objective to really improve and optimize public expenditure. It is a reading of budget programing. It is a different reading of budget programing in terms of DDMI and this other dimension that enables us to look at what’s going on in our countries in a different way. And it’s really, it’s been a new way of thinking about things and the ability to do this internal advocacy for it to have more effective public expenditure.

Um, Miss Mariama from Gambia. Can you hear me? Your camera is off. But thank you. I would like to know. So. Gambia. The Gambia undertook the first steps the NTA profiles. I know you are undertaking a study, an investigation on the use of time in order to create an NTTA profile, and I would like to know your opinion as to why The Gambia is undertaking this process. And you know what do you think of it in terms of the you in comparison to the usual practices? And what are you hoping to achieve from this? What are your expectations? Thank you.

Mariama Fanneh: Thank you very much. Thank you to CREG and PRB for the opportunity to attend this. Um, I don’t know whether I’m.

Aïssata Fall: The sound is very very weak.

Mariama Fanneh: Is it still very weak or is it okay?

Aïssata Fall: Is it okay for translation interpreters?  Okay. Go ahead Mariama.

Mariama Fanneh: Okay. Thank you very much. Thank you very much CREG and PRB for the opportunity to attend this important webinar, which is key for building the capacity of technicians and getting the support of policymakers. I hope this is something that you’ll be organizing often. Regarding, why we want to apply the BSDD process and why we want to continue ensuring that the Gambia harness the demographic dividend. The reason for wanting to apply the BSD process is because the Gambia now stands the pivotal moment when it comes to harnessing the demographic dividend. Uh, because when the demographic dividend profile of The Gambia was updated, we realized that we have a steep increase in our potential for harnessing the demographic dividend. And also following the updating of our BSDD profile, we also developed the demographic dividend monitoring tools. And this we did with technical support from CREG through the World Bank project, which is the SWEDD Plus. So we develop the BSDD like Professor Dramani, he was explaining. And these are tied to the four pillars of the AU for harnessing the demographic dividend. We have the profile ready and we also have the DDMI, which is the diagnostic tool. But it was very unfortunate that at the time of developing the NTA, we couldn’t develop the NTTA because we didn’t have the data on time use but we are currently working on that because we know women contribute a lot when it comes to the GDP, but it goes undocumented. And we want to know how much women are contributing when it comes to the GDP.

Currently in the Gambia, Aïssata, it’s very difficult for us to be able to harness the demographic dividend because of the budgeting system that we have, which is the traditional budget. And we know that for the traditional budgeting approach, it’s mostly about maintaining fiscal balance and allocate funds based on past spending. And it’s also addresses immediate needs without considering long term demographic trends. For instance, when Professor Dramani was explaining, my mind went to, um, you know, um, what happened last year with the budget and that is how I’m sure a lot of countries that are budgeting based on the traditional, system of budgeting, that is how they budget, because for last year’s budget when it comes to education and health for education, it was 37.3%. And for health, it was 17.1%. And when it comes to youth empowerment and employment, it was 0.01%. And we know that for a country to harness the demographic dividend, especially for a country like the Gambia, where you have 79.2% of the population below the age of 35, and we’ve also have had a decline in child dependency between 2013 to 2022. Our child share dependency declined by 10%. And we know that that is one of the prerequisites for the opening of the window of opportunity for addressing the demographic dividend. Going back to the numbers that I just mentioned, 37.3% and 17%. Yes, that is the percentage of the budget that goes to health and education. What are they going into service provision? No. Most of our budget goes to recurrent expenditure. So in having a DD sensitive budgeting we’ll be able to know what is going well, what is going to service provision and also what is going to a recurrent budget, because we know that we recurrent with most of our funding going to recurrent budget might be impossible for us to harness the demographic dividend, knowing that the current opportunity will not last forever. It’s expected to peak in 2035 and close by 2050, depending on the DD profile.

The demographic dividend is also not automatic, and we know that is the potential that must be harnessed for economic growth and development. Therefore, I think it’s very, very important for us not only to also go ahead and do a time use survey and develop the entity profile for the country to know women’s contribution to the GDP. But it’s also a very, very important for us to have a budget that is really responsive to the demographic dividend, a budget that is conducive to harnessing the demographic dividend, and that is the DD sensitive budgeting. And we’re looking forward to really getting the support we able to transform our budget into our budget that is sensitive to the demographic dividend. Thank you all very much for your kind attention.

Aïssata Fall: Thank you very much, Miss Fanneh. It’s very interesting to hear what you were explaining about the classical manner of establishing a budget, and to into relying on recurring expenses last year’s budget, without wondering how does this contribute to the various dimensions and the objectives that are necessary in order to take to benefit from the demographic dividend, without also wondering whether these expenses contribute or make use of the demographic dividend? You know, and having zero invested in youth when you have such a young population is very striking. So I would like to speak a little bit about how this process started and how the countries integrated the various questions and challenges in their budget.

And now I’ll talk to Pr. Germaine Anate, Togo, so you are in the National Assembly, which he has not necessarily been involved in this work in the beginning because it’s a very technical type of work. But the tools are here, and in the end, it is the National Assembly that must approve the budgets, that must support policies that will strengthen efforts to take advantage of the demographic dividend. So for you, what are the specific roles of the gender dimensions and what role do they play in your budgeting process and your decision making process at the National Assembly? And how can BSDD help us to help you to deal with this, these issues of gender equity. You have the court, you have the floor.

Germaine Anate:  Thank you for having inviting me to participate. You spoke about the fact that the process has been very long. And forTogo, we must say that the opportunity we had is that in Togo we had a gender sensitive policy. We also had a budget program that included pretty early on the gender issue and this has improved over time. And so the current version that is being finalized, it includes this. So this has been mainstreamed throughout all the various ministries and institutions. And it has taken into account in the 2025 budget, which is being finalized. And so Togo, you know, is taking advantage of the fact this mainstreaming of this issue in its budgeting and to take advantage of the demographic dividend. And really, this is something that’s been accomplished because the draft budgets are currently being created and this dimension has been included in it you know and and I mean, so in term we’re going to allocate amounts to every action activities and taking into account gender and demographics.

Next, I would say that the gender dimension has an essential role in the budgeting process in Togo, especially given the National Gender policy that has been put forth, and that establishes gender units within each ministry. And Togo is also working on gender equity and the empowerment of women. So in terms of strategy, this gender dimension is already taken into account. And to really enable all levels of the population to participate and benefit from development. This effort was undertaken in 2020, integrating gender into the budgeting process. I am not going too long on the budgeting issue, but we must recognize that, you know, during the budget cycle, yes. We have included the gender dimension you know, in terms of the budget, audit, etc.. And but we must say also that BSDD data is taken into account in the improving of budgeting that is sensitive to gender and in terms of the specific role of the gender dimension. For me, it’s really a function of facilitation and a translation of public policy, because it is particularly about facilitating and making sure that the budgeting process is inclusive throughout all its steps, and to ensure that women are direct beneficiaries of budget allocations that have been justified by supported by these criteria. And, you know, in my position when we, we look at the line item that is dedicated to gender to make sure that the allocation is there and that it is what it should be and that it is not actually used for something else. So there’s this role of facilitation, and we need to also monitor the governmental policy.

[The interpreter apologizes. She cannot hear the speaker anymore.]

So for a parliamentarian, this is very important because we monitor government activities. So we, you know, taking this into account to have a more aware review of what’s going on when we are asked to review the state’s budget. So in Togo, the BSDD is really going to enable us to strengthen this gender issues to reduce inequalities, and particularly in terms of investments for young people and for young women, young girls, and also for health care. And let’s recall that Togo joined the project for the Empowerment of Women and for the demographic dividend in sub-Saharan Africa and one of the results of this study is BSDD. So this is what I have to say.

Aïsatta Fall: Thank you so much, one certain women must be the beneficiaries of allocations for which they serve as a pretext and this is a very important topic, you know, because to budget for gender is one thing. Budgeting for women. Yes. But what is the impact and how do you monitor the efficiency, the effectiveness of the allocations, the effectiveness of the policies. So this is a tool that enables us to do this progressively. But also to analyze these policies in a different way. Uh, thank you very much Honorable Anate.

 Moussa Sidibe from Mali, you are next. Could you talk to us about what are the assets, what are the challenges associated with BSDD at this current time, especially for the improvement of social sector planning? You know, this has to do with finance, budgets, taxation, etc. You know, we have had research in economics, demographics which and then tying this to planning needs. So budgeting is not just within the Ministry of Finance. You know the ministry; it the ministry must understand how the social sectors function. And so for you, what are the advantages and disadvantages of BSDD?

Moussa Sidibe: Thank you very much, Miss Fall. Um, hello to everyone and I want to specify that in Mali and this exercise was made possible in Mali thanks to certain number of advantages we have. The first advantage is an observatory for the demographic dividend. And it is a sustainable observatory in Mali. And it is able to continue to studying and research work in terms of the economy specifically, the analysis of budget of BSDD in order to improve budget allocations to very basic sectors and to improve health, education, etc. Our second advantage is the existence of a national multidisciplinary team that is a part of a network. And so we people who are working at the national level and they’re working on overall statistic systems and they support the observatory’s work. Um, and this multidisciplinary team is really an advantage for the creation of reports on BSDD, and they contribute to the strengthening of national expertise in BSDD.

So there is also a center of this means that we have um, a ministerial and parliamentary system that is well informed and that enables us to have an optimal distribution of the state budget to achieve sustainable growth.

So first I will note the budget general Directorate, the uh Directorate for planning And the National Council for transition. So all these structures are key actors in budgeting in Mali. And they were all trained and informed about the importance of BSDD. A lot of the directors of these entities have visited, uh, Senegal with the CREG to undergo training on these issues, and this has enabled us to get things started and to make it so that they could be advocates on this issue. And the last advantage is really taking into account the results of BSDD in the formulation in terms of human capital as stated by CREG. So this is really a document that was created to federate all the bring together all the policies in Mali and we are participating in the monitoring of this as well as working on the promotion of BSDD. So these are really the advantages, the, the assets that we have within Mali. Of course, there are challenges that are present. I can talk about five of them. First, the need to have reliable data, up to date data, the regular production of statistics is essential. And then the strengthening of national capacities to ensure the creation of regular reports on BSDD. The lack of a strategic plan for communication on BSDD. The strengthening of the partnership with the research institutions, the technical partners, the financial partners, etc. to mobilize financing to sustain the research needed on BSDD and the improvement of the security situation within the country. Um, you know it. We know that the issue of security, especially in the states of the Sahel, means that there are elements that are detrimental to human capital, especially when we’re talking about health and education. And even if we are able to maintain certain rates, the movements of the local populations, unfortunately, can sort of cancel out a lot of the efforts undertaken by the government. So this is a summary of what I wanted to say in response to your question.

Aïsatta Fall: Thank you so much. Thank you for that very good summary. And I think it’s very interesting that you talked about your assets, but also the challenges, but you also highlighted some of your assets that are helping you having the observatory, for example, for demographic dividends, that was created by law by a decree, and that this then provides a sustainable structure. And this is in fact a very useful in giving you the favorable environment, the necessary environment you need to do conduct these studies and analysis. I think it might be difficult to be able to really use the data on a regular basis, long term basis for these analyses. If you didn’t have these types of structures in place, and the fact that you have a lot of stakeholders that are engaged in the process and it’s a true collaboration amongst the various government bodies, decision makers and analysts. This is also one of the advantages and the fact that you’re working in such a collaborative manner with decision makers and analysts. I feel that this is really essential in order to bring about sustainable change.

Talking now still about collaboration and participation. Participatory processes. I’d like to come back to Dr. Larba from Burkina Faso and I’d like to ask you, because you’ve been doing this process for some time now, if you could talk about some of the challenges you’ve had in integrating these tools in your national budgeting processes. And you were saying earlier you were talking a little bit about how this knowledge and these techniques are also impacting other people who are involved in budgeting decisions and at various levels in various spheres.

Doctor Larba, can you hear me? Uh, okay. If not, I will come back to Dr. Larba. And so maybe I’ll go back to Miss Diouf and so Miss Diouf, can you hear me? Can I come back to you?

Atou Diouf: Yes, I can hear you.

Aïssata Fall: Okay, great. Miss Diouf, can you quickly share a few words about some concrete examples of how you’re using the BSDD and how this could, in your opinion, approve the planning and implementation of public policies in your country and particularly for gender equity, and I say could improve because I know that you have been making efforts and you’re and I know that you work specifically on gender equity. So how do you see this tool helping you to achieve your objectives for gender equity?

Astou Diouf: Thank you very much. That’s a question I think we could ask all the questions or all the countries rather, because the most vulnerable population in Senegal is the youth population, as we’ve seen in our recent census. And Senegal, like other countries, also has a demographic dividend National Observatory. And we also have a focus on gender equity. This observatory is also a multidisciplinary multisectoral and it does bring together all the different decision makers from the various sectors. So I think what we need to do more, though, is we’ve started with these studies, but it’s been a bit of a slow start and I think that we need to continue conducting more studies and perhaps more thematic, specific studies. But for those of us who are working on gender equity issues at the national level, we’re now in our third edition. We’ve been doing this for two years of what we call our forum of dialog forum. And this is a forum really looks at the challenges and addresses the obstacles of for integrating these techniques and whether it’s the BSDD or the gender sensitive budgeting.

And whether it’s at the dialog forum or the national Observatory we have been trying to identify our priorities And I think that looking at the biggest issue or the biggest aspect of demographic dividends is human capital, and we need to look at how we can better understand this through our analyzes and studies. But we’ve also been drawing a link between gender sensitive budgeting and demographic dividend budgeting. I say that because in 2016, we started initiated, we started initiating more gender sensitive budgeting. And we observed that some parliamentarians, those who deal specifically with the budgeting process are now more willing to use these instruments and these tools. But another key element that I think has helped us to make improvements is that we were talking to decision makers before we even before they even undertake the budgeting process to show them what some of the weaknesses are, but also some of the key points that policies need to focus on and the impacts that we can have. And I think it’s important that we’re promoting these issues.

And then when we look at gender equity and investments because obviously economists know these issues better than we do but we have to look at these different dynamics and some of these criteria that are related or aligned with international standards and norms. For example, we need to be talking more and more about the issue of what the stakes will be at the international level. At the national level, when we look at these different dimensions that we can we have to see how we can really implement, bold and gender sensitive budgeting in our countries. And I think that this is going to be an essential issue for all of our countries.

Aïsatta Fall: Thank you very much. I’d like to go back now to Mariama, Miss Fanneh, and I’d like to ask you, how do you envision the future evolution of demographic dividend sensitive budgeting in your country, and what additional support would be needed to strengthen the BSDD approach? We’ve seen that this is a very long process, and if we want it to be inclusive and have a holistic approach, and if we want it to be supported by the community of decision makers and politicians and you might need different supports when you start up, because you have to look at all the different fractures in the budgeting process. So over to you, Mariama, to answer that question.

Mariama Fanneh: I thank you very much Aïssata for again giving me the floor. Uh, the demographic dividend sensitive budgeting, if implemented like we already know where to implement it in the Gambia, will represent a strategic shift from traditional budgeting to a more dynamic and data driven approach. A responsive to demographic dynamics and allocating resources to sectors that maximize the harnessing of the demographic dividend. Currently in the Gambia, not only in the Gambia, but across Africa. We are at a crossroads. We have seen and we need to empower our Marimar.

Aïsatta Fall: Apologize. I think it’s quite low. Mariama. Your sound is really low.

Mariama Fanneh: Let me. Let me move it closer to my mouth. I’m saying it’s okay. Can you hear me now?

Aïsatta Fall: Yes. It’s better. Yeah, better.

Mariama Fanneh: Sensitive budgeting, if implemented in the Gambia, will represent a strategic shift from traditional budgeting to a more dynamic and data driven approach, responsive to demographic dynamics and allocating resources to sectors that maximize the demographic dividend and that is what we want in Africa. Because if you look at Africa currently with its very young population, all the countries stand at critical crossroads. We have seen what happened in Kenya, and we have also seen what happened in Ghana lately and in the Gambia. Anticipate a Gambia with a budgeting system, if implemented, that relies on a comprehensive analysis of its budget utilizing demographic data to inform policies and investments anchored on proactive planning for population change to ensure that long term benefits of the demographic dividend foster a robust and adaptable economy. When it comes to the additional support that might be needed. We know that transitioning to a demographic dividend sensitive budgeting might encounter resistance from those accustomed to traditional budgeting. We all know that change is not something easy, and every sector would see their structural budget as being very, very important. So if we want to overcome this challenge, it necessitates capacity building for government officials and policymakers through targeted trainings like the ones that we are currently having.

The Gambia, like many other nations, also faces economic pressure due to the Russia-Ukraine war and high debt levels. And the BSDD can help prioritize spending and accelerate the country’s transformative agenda to fully realize the BSDDs potential ,The Gambia will require increased financial resources, technical assistance, and a robust data infrastructure. Gaining public trust is also very, very important. The public needs to be needs to be aware of the importance of this very sensitive budgeting and here to transparent communication, public awareness campaign and feedback mechanism will be very, very important for building support for BSDD and aligning it with citizens needs and aspiration. By prioritizing these areas, The Gambia can effectively harness its demographic dividend, attaining sustainable development and a prosperous future through BSDD. Thank you very much for your kind attention.

Aïssata Fall: Thank you, Mariama. That’s very interesting and as I heard you say, it represents a big change, a shift for something that to something that’s going to be more dynamic and more in line with the reality of your of your objectives.

In the interest of time, I’m going to have to just pass out my questions a little bit more. So I’d like to go back to Mr. Sidibe from Mali and ask you, generally speaking, with the experience that you’ve had. What needs to be done, not necessarily in Mali, but also with your experience with SWEDD project that’s been done in many countries in the region. And knowing what’s happening in other countries that are at different levels of budget execution, in your opinion, what needs to be done to ensure the effective dissemination of this new tool, in that it involves a more active and targeted knowledge sharing process to create a measurable impact. We see that in Mali you’ve been reaching out to decision makers and you’ve been working with many stakeholders. So it has this enabled you to bring about this change in budgeting culture in all sectors? And looking at one of the questions in the chat, specifically looking at the social sector, have you seen this change, change of culture?

Moussa Sidibe: Thank you, Miss Fall. Yes, it’s true that there have been advantages, but we have not yet achieved all of our objectives and we need to still work more on communication. I think that first of all, it’s important to strengthen our communication capacities for the decision makers and policy makers. We need to be able to continue developing more communication tools, such as policy briefs, that we can disseminate to Parliamentarians decision makers to help create a more measurable impact. I think it is also important to hold advocacy sessions or educational sessions to be able to get this information disseminated out to the various regional levels and the different sectors that work with women or youth, etc. and to do this throughout the entire country even at the community council level, because not everything is decided at the national level, but even at the community level, the local level, there are very decisive actors who do have an impact on how these the budget is allocated and used.

We also have to involve civil society organizations more, and we need to work more with the media so that they are more educated about these budgeting issues. We need to have more citizen focused budgeting, if you will. And we need to be able to create allies to help us with this advocacy work with members of Parliament and decision makers. We need to see how we can mobilize civil society actors, the media and by holding educational workshops about the budgeting process and to see how civil society organizations can maybe organize meetings or educational sessions to talk about what we can do to advocate for this and I think we need to also encourage, um greater publication or more wider publication of the results of these analyzes and studies. I think those are the key points that I would like to offer. Thank you very much.

Aïssata Fall: Thank you very much. So to briefly, Honorable Anate, if you could, you spoke about the importance you minorities spoke about my question during your first response. So I would more ask, I’m going to ask a concluding question instead, as a parliamentarian who knew this type of information, we met in Togo during presentations on exactly this type of information. And, and I’m grateful for this meeting because it was really interesting to be with this network of former and current women parliamentarians. So a decision was made to work on advocacy towards the Prime Minister to not improve things for civil society, but to make it so that the various sectorial departments would be involved directly into what was just said.

Now, as a parliamentarian what is your advice or what are your ideas in order to improve the use of this type of information that is provided by the BSDD? Because it is the BSDD it’s a process, it’s a tool. So it’s really about it’s new way of looking at things, these tools that it provides, this information, it provides. So as a decision maker and we don’t have enough I think in this type of session, what would you say?

Germaine Anate: So yes, as to sum up, essentially, I think the data provided by the BSDD is contributes to improving budget allocations to meet the development challenges in the country. But we know that the budget is developed on the executive side and then the parliament is called upon to approve it. So it is really having this data for the parliamentarians in order to vote on laws that are appropriate to meet the needs of the populations. You know, this is essential. And I wanted to come back to this question of national work on BSDD. I think, you know, desperately provides the opportunity to really seize upon all this, to capture this work at the national level and especially for women. And because we know that women are in this informal work sector and they are they’re numerous within this sector of the informal work. So I think we can have a really have a better understanding of BSDD on work in the household, you know, the work of young women of women. And with this data, we could develop strategies and policies that could sort of perhaps reduce this informal sector so that we have a greater formal sector. And this will be more advantages in terms of the empowerment of women. And we had recently the opportunity thanks to the PRB and the CREG initiative on awareness raising among parliamentarian, women and Ministers but this enabled women to better understand the topic, to take a greater ownership of this topic. Because one of the big challenges is the taking ownership and the understanding of this topic.

And someone talked about, you know, training on communication. And I think this is something I really want to emphasize. We must have more awareness raising including at the parliamentarian level. So I would ask PRB and CREG to continue this work, but I think we also need to make it so that the state institutions in charge of these issues share this information. Because, you know, what I realized during this is that those who hold who have information within our institutions they don’t disseminate. So we must have a better dissemination of information and this will really help parliamentarians in this process. And the other challenge I want to note in the Parliament Arena, is we must, like the Togolese Parliament, must really invest in research and investigation issues to provide to get the data that we need to carry out our functions. And we’re also called upon to question the government and, and we must do it in a way that is well informed.

And so you know, and of course, in connection with gender and demographic policies and for the development. You know, we talk here about the government’s roadmap and if a parliamentarian is well trained and is well aware of the topics, this really helps. So we have a commission that is responsible for these social issues. And so we must make it so that this commission is better trained and better informed. So there are a lot of challenges, but we can’t, you know save money on communication etc.. It is really essential to have this.

Aïssata Fall: Thank you so much. Thank you for what you said. We’re talking about, you know, the dissemination, the provision of information as well as the resources, the tools, so that they can be used in an effective manner. So it’s not just a question of providing information. Um, you know, it’s really we want to see how this can be adapted to those who are going to use this communication. I’ll ask one last question of Dr. Larba, if you are back with us?

Dr. Larba Issa Kobyagda: Uh, well. Uh.

Aïssata Fall: So one last question rather quickly because we need to finish. But given your experience I’ll ask the same question I asked the other participants to documents are created reports, sectorial reports there are conversations. Is that sufficient? And it’s not just about Burkina Faso, but you know what? What would you say? What would you advise to improve this national cooperation and to take advantage of this demographic dividend. You know, this is really we’re not just talking about a five-year plan. We’re talking about a whole change in governance. So in two minutes, what would be your the essential points that you would advise to take into account. Thank you.

Dr. Larba Issa Kobyagda: I think very quickly, I think we have to talk about the, the obvious really. Um, so the state budget is voted on by the various parliaments. So it’s only evidence that is going to prove to governments that they must use this type of budgeting. So the results and, and the results that have been shown by the scientific research that show us that BSDD can really benefit us in, in taking advantage of the demographic dividend. So the planning that is done within our various governments, it already takes into account this issue of populations, youth, empowering women. But what we noted in Burkina Faso is like despite the fact that we had all these programing documents you know, so all these documents were there and, and it stated that there would be a very important role. But from there, um, there was not a you know, that something that made it possible for this youth to bring a added value. So the policymakers, etc. members of the government must be fully aware of what is important, and then we must work so that the results of this research do not remain disconnected from policies, from politics. So say we find very interesting results, but we have problems contextualizing things. So if you look, for example, at the Sahel context currently with the security challenges, it is very difficult to ask a country that is just really trying to survive, to ask them to attribute a huge part of their budget to a particular sector when they really need this money to just survive. Um, so, you know, we must look at research, we must look how in these the findings of research can have a result can achieve results depending on the context. Then we have Civil society can disseminate results of research through the research centers. I saw that, the University of Berkeley provides data in this area, but you know this data is perhaps not so relevant to a farmer in Burkina Faso, etc. So what makes it possible to use this is the state local authorities. So we must continue this awareness raising effort. So the research institutes must provide the finding but we must continue also to disseminate these results.

Aïssata Fall: Thank you so much, Dr. Larba. Um, when you talk about, you know, the involvement of the population, civil society and to keep research connected to reality and to day-to-day practices. I wanted to note something that Mr. Sidibe spoke about the fact that and when he talked about decentralized authorities, budgeting is not something that just exists at the national level. The integration of, you know, the gender dimension and demographic change. It’s not just a theoretical thing. It’s something that happens in real life. So having an approach that informs reality but takes context into account and to have, you know, an understanding from the population so that they don’t necessarily understand the technical aspects, but how this can be useful. You know, so having a dialog at a decentralized level in every space where you can have a budget discussion, where citizens can talk to those who are elected, you know, this is a very beginning. It’s not an end product. You know, this is a continuing process, under many, you know, and there will be other dimensions that will be refined. But this provides us a very solid base to start talking about how our economies operate in terms of money, the flow of money, and in terms of time. Um, so when you can illustrate the links between, you know, this, this way of thinking and the budgetization etc. it’s so we need to understand how research can, um, have an impact at the various levels of decision making. So we hope to be able to continue what we just started and with you and other countries to conclude and thank you for having remained so late with us.

Now I’m going to give the floor to Professor Dramani. You started over ten years ago, an adventure that has created tools that are used in many countries. BSDD is a performance indicator for countries that are taking part in this web project. So you’re a researcher, but you regularly talk to decision makers. So this process was a collaboration that was undertaken in a holistic manner to meet the needs of decision makers, policy makers, to answer their questions. So very briefly, could you tell me what is the risk in terms of future development that doesn’t take into account demographics and gender? And how do we speed this up? You know, demographic transition, the demographic dividend. We talked about it 20 years ago, but now the windows are opening up where we need to speed up. We need to accelerate this work.

Prof. Latif Dramani:  Thank you. Yes, thank you Aissata and thank you to all the panelists; Dr. Larba, Mr. Sidibé, Professor Anate, Ms. Diouf. Oh, I almost forgot Miss Fanneh from Gambia. But thank you to all of our panelists and to everybody who has stayed online till now. When we started this work. It has been it was it has been a long process, It’s been a long road and I would like to thank all the foundations that have enabled us to do this work. I think that our dean is on the line and I’d like to thank him and all everybody that we’ve been working with for the past ten years to develop this tool, UNECA, Hewlett Foundation and all the many partners. Uh, and I think that really the fundamental issue that we have to grapple with now is that today we no longer have the choice, African countries no longer have a choice. They have to review their budgets and rethink them, because it’s not just private funds or donations that are going to develop our countries. It’s our national budgets. And so the collective well-being of our populations is something that’s going to be ensured by our investments and investments to increase our productivity and our growth. So these are investments that we have to make in health and education and so forth, and infrastructure In order to enable our economies to create the jobs that we need and to be able to spur growth. So this issue is fundamental if we don’t take this into account the economy.

If we look at the history of economics over the past centuries of study on the problem of poverty we cannot resolve issues of poverty, you cannot resolve issues of an aging population unless you take these issues into account. You have to be able to use these windows of opportunity and when you have an aging poor population, that’s a catastrophe for anybody. So you have to use these windows of opportunity that are opening for everybody because you can’t just think about this and without realizing that the best thing for all of us, for our decision makers and our and our continents, our countries, is to invest in our youth and to be able to really profit or to really capture all the dividends from this youth, this energy and their productivity. This is something that’s going to be beneficial for everybody, for future generations, and as part of this work, what we observe Dr. Larba talked about this and others is that it’s the research is not always easy because we work a lot. We spend a lot of time to obtain these results, but sometimes our politicians or decision makers don’t have the time to sit down and discuss this with researchers. So what we really need to do is to make sure that people understand that research is extremely important, and it’s going to play a crucial role in decision making in our countries. And that we also need to be able to duplicate these successes. When we see their successes, we need to achieve a critical mass. We need to be able to have a critical mass of people who are dedicated to working on these issues. And we have to create centers of excellence, centers of excellence, rather, where we can train people to continue this research and where we can also continue implementing good best practices and monitor what we’re doing. We need to control or monitor the quality of data that we’re obtaining. And we have to really look at the fact that our continent is one of the youngest right now. And other countries, other continents are not facing this issue. Asia, Europe, they have a more aging population. They’re not dealing with this issue, they have an aging population, not a youth population, youthful population. So we need to look at how we can apply best practices and continue this work. Thank you very much and back to you, Miss Fall.

Aïssata Fall: Thank you very much, Professor Dramani. That was very encouraging and very convincing. I think that indeed we know what we can do and we need to do it. The work that we’ve been doing, the collaboration with CREG and the various countries that are partners in this project with and funded by the Hewlett Foundation. This collaboration has enabled us to see just how far we can really use our technical assistance to work with different actors and of course, in this process, which is highly based on analysis and research, we can see how we are, how we can continue to define our priorities and to look at finding the most effective solutions. And I come back to what Dr. Larba was saying earlier,there’s not necessarily just a standardized solution. There’s a lot of common research, but we have to adapt it to our different contexts, and we have to do this work of looking at contexts and how we can continue refining the research and the techniques and the language that we’re using the approaches. And this all has to be based on the context and I think that in our various presentations and in the answers and responses we have, we see that it’s important to look at productivity and we have to of course, we think about this at a high level, international level. But we also have to look at it at a decentralized level as well. And we have to see how the data and the BSDD process can help us continue with advocacy, advocating for change, the changes that will be implemented in countries based on context. But this is a huge change in mentality where we’re setting aside our traditional budgeting Processes of whether it’s programmatic based and then looking at how we can adopt these new budgeting processes. And this is something that is going to enable us to also promote our goals of having more transparent governments.

I would like to thank everybody who was part of our panel today, and thank you for everybody who stayed online a little bit longer than planned. Uh, I know we had these technical issues, but of course this happens from time to time. There’s nothing we can do about it. And we hope to continue this discussion. As many people have said, we do need to continue this discussion and dialog because these are areas that are not always as discussed as we should in our various African countries. Uh, we need to be able to translate these tools and use them. And as I said at the beginning, all the questions that were asked will be answered. We will also share the presentations and the recording of the webinar, not right away, but because we are trying to think about the best way to share all this information.

We don’t want to just send out the presentations because there were things that were said today during this webinar that are extremely interesting and could be the topic for a further a future meeting. And somebody, many of the questions that came in and writing were also very interesting. And we’ve had a lot of people in this discussion talking about the youth potential, the demographics of the dividends and so we will be looking at how we can incorporate all this and so that people can understand what we’re talking about today. We need to include not just technicians and analysts and politicians in the debate. It’s important to also bring in many other stakeholders in different countries to talk about all these different issues along the whole decision-making chain.

And so we will, of course, have to think about how we can involve the young people themselves. The youth who are working at various levels every day to improve their futures. So how can we also include them more in this dialogue? It’s not something that we can just talk about at a theoretical level that has no interest. We need to talk about how we can change our political cultures and how we can really have a more effective dialog, including youth. So we will have future webinars where we can have discussions focus more, maybe on the policy side of things. We’ve been talking a lot about the technical side today, but we will also be talking about how we can use all these processes, this data, and how it can be better integrated into your role as a decision maker or a policymaker.

Thank you very much for being with us today. I hope you all have a wonderful rest of your day and I hope to see you soon. Thank you.

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Transcript

Mark Mather, PRB: Hi everyone, thank you for joining today’s webinar on how state contexts impact Population Health. I am Mark Mather. I’m with the Population Reference Bureau, or PRB, and I work in collaboration with the Coordinating Center for the Demography and Economics of Aging and Alzheimer’s Disease and Related Dementias at the University of Michigan. And our goal is to help publicize research on health and well-being, especially among older adults. I also want to acknowledge the National Institute on Aging for making this webinar possible, and my PRB colleague, Toshiko Kaneda, for helping us to organize this event.

I’m excited to introduce our two speakers today. We have Dr. Tyson Brown, who’s a Professor of Sociology, Associate Professor in medicine, and Associate Scientific Director of social sciences of the Duke Aging Center at Duke University and Dr. Jennifer Montez, who is a Professor of Sociology, Gerald B Kramer faculty scholar in aging studies, Director of the center for Aging and Policy Studies, and Co-director of the Policy, Place and Population Health Lab at Syracuse University.

We’re also going to put two links in the chat, I’m not going to read their long bios, but if you’re interested in learning more about the speakers and their research, we will be putting links in the chat where you can get more information. And finally, just a couple of housekeeping notes; we’re going to hold the Q&A until the end. But if you do have a question, you can type it into the Q&A box at any time during the webinar. And finally, this webinar is being recorded, we will send you a link to that recording after the event, probably within a day or two. And with that, I will go ahead and turn it over to you, Tyson.

Dr. Tyson Brown, Duke University: Well, thank you so much. I look forward to hearing your feedback during our presentation. I will go ahead and just start sharing my screen. Again, thank you so much for inviting me to present my work, and I’m really excited to talk with you all today about how we can operationalize state level structural racism and its impact on population, health and aging. And as a race scholar, gerontologist, and population health scientist, you know, the primary focus of my research is on quantifying and mapping structural racism, as well as estimating its impact on aging and health equity. And so today, I’ll be giving an overview discussing what I see as important theoretical and methodological issues, as well as promising avenues to address them, and in doing so, advance the scientific study of structural racism and health.

So, before discussing the role of states, I think it’s really useful to zoom out to highlight how various frameworks can help us better understand how social context influence health. So, the social ecological model emphasizes that population health is shaped by complex interplay of social factors across multiple levels, from individual behaviors to broader societal forces. And this model highlights how health outcomes are not solely a product of individual choices, but are influenced by interpersonal relationships, community structures, institutional policies, and broader sociopolitical contexts. And by analyzing each of these, we gain insights into how policies, societal norms, and community structures can either benefit or harm population health. And this is true for many social forces, including structural racism.

And so, most of the research on links between structural racism and health have focused on structural racism at the neighborhood or the county level, which are really important context and really sort of the micro-level, or rather the more proximate contextual sources or determinants of health. However, other special units and policies such as states have received comparatively less attention. And this is a really major limitation in literature, because U.S. states obviously are important legal, administrative and political units and states have always provided an important context for racial stratification, including the roles that they most obviously played with respect to chattal slavery, Jim Crow and anti-miscegenation laws. So importantly, states continue to have a great deal of autonomy, and they’re heterogeneous in terms of the racialized policies and practices. This is evident with respect to things like disenfranchisement laws, aggressive policing practices, punitive sentencing, as well as the expansion or contraction of safety net resources.

And so, as a result, my research focuses on conceptualizing states as racialized institutional actors that influence population health.

So, in several recent studies, my research team scopes the literature on social racism to really identify the central tenets of structural racism theories and draw upon them to study state level structural racism. We highlight how the analytical crux for measuring structural racism, which is a complex, interconnected and dynamic network, really lies in examining its features and mechanics that undergird racial inequalities.

And so, failure to align measurement tools with these core features compromises the validity of research. Because measures that are incongruent with salient aspects of structural racism can distort findings. So, to address this issue, we draw on interdisciplinary theories and evidence to really dissect core features of social racism, with a focus on their implications for measurement and modeling.

And so, our studies on and the broader literature really underscore the importance of measuring modeling core features of structural racism, including things like the fact that it’s a distributional system, involves relational power dynamics, manifestations of racial inequities, that it’s a multi-level phenomenon operating at macro and micro level contexts, that it’s multifaceted and interconnected in nature. And this plays out across societal domains, that there are specific racial actors implicated, that it’s an institutionalized phenomenon that it involves racial schemas, logics, as well as socio historical context and intersections with other systems of oppression. And so structural racism is embedded in major political, economic, medical, criminal, legal and numerous other social institutions and aspects of society. So, in these forthcoming articles that are listed here, we offer concrete recommendations for conceptualizing, measuring, and modeling structural racism in ways aligned with theory. And so, the aims of these studies is to provide field guides for rigorous, theory driven measurement approaches, proposing best practices for the scientific study of structural racism in health research.

And to provide a couple concrete examples of ways to measure structural racism, as well as its effects on health, I’ll briefly describe several recent studies in this vein. And so, the first one addresses two main research questions. The first is, does state level structural racism across societal remains reflect an underlying latent construct? And latent constructs are phenomena that are not directly observable but can be estimated through statistical approaches that really capture manifestations of the phenomena. And then secondly, the question is structural racism associated with worse health outcomes among Blacks and whites in the U.S.

So, to examine variability in state level structural racism and its relationship with health among Black and white adults, we combined indicators of structural racism from several sources of publicly available data. And then we link these to geo coded individual health and demographic data from the Health and Retirement Study, as well as CDC data on COVID mortality, as well as the Behavioral Risk Factor Surveillance study. And so, this table shows each of the domains and indicators of structural racism that we examine. We use publicly available data to examine structural racism for the year circa 2010, spanning several domains including the criminal legal system, education, economic resources, political participation, as well as residential segregation.

And so, I should mention that this measurement approach is informed by theoretical perspectives as well as previously validated measures of state level structural racism.

So, the next step is to test whether state level structural racism reflects this underlying latent construct. And so, we’re especially interested in measuring structural racism in ways that are in line with structural theories, as I mentioned. And a latent variable approach is well suited for minimizing measurement error and capturing conceptual properties of a complex system that’s difficult to quantify or directly measure, such as structural racism. And so along those lines, the nine indicators of structural racism that I mentioned were used to develop a latent measure of structural racism. And we used confirmatory factor analysis to measure the extent to which structural racism across these domains are reflective of an underlying construct of structural racism and doing so we systematically evaluated model fit using varying model specifications related to correlated errors and also dimensionality. This figure here illustrates the factor structure of the latent construct. These correlated errors are all intended to address common sources of variation that are independent of the effects of structural racism on the various indicators. And so all consider the measurement model that allows for other common sources of variance in the indicators that are largely conceptually motivated, has a good fit with the data, and it generates reasonable parameter estimates. Furthermore, this measurement approach is largely consistent with many of the theoretical tenets that I outlined above. And I should note that we made this measure publicly available from the journals website in case you’re interested in exploring. So now we’ll turn to addressing the second research question, which is how does structural racism shape health among Black and white adults? Eco social theory has become a leading framework for understanding how macro level discriminatory environments impact health, and the theory suggests that structural racism has deleterious effects on Black people’s health. That part’s pretty much straight forward. We would anticipate that from the theory. And there are competing hypotheses about how structural racism may influence the health of whites, with some suggesting that whites benefit from sexual racism, while others are positing that they’re harmed by it, and others suggesting that their health may be unaffected by structural racism. I’m glad to talk more about these competing hypotheses during in more detail during the Q&A, if you’d like.

But let’s go ahead and jump into the results. What’s going on here? I’ll explain it in just a second. But one of the things I want to mention is that, you know, since replication is a hallmark of good science, we examine the relationship between structural racism and six different health outcomes in both the Health and Retirement Study and the Behavioral Risk Factor Surveillance study. For a little bit of context, the HRS is considered one of the premier data sources for studying health among adults over the age of 50 in the U.S. is nationally representative over samples of Black adults and the birth. This is the largest health survey in the in the United States. So, you have over 300 respondents. So, you’ve got tremendous statistical power. And so, we found remarkably consistent results across health outcomes and across the two data sets. And six out of the six cases, you can see that there are that higher levels of structural racism are predictive of worse health among Black people, remarkably consistent. But we see a very different story for whites. And one instance, structural racism exposure at the state level is predictive of better health for whites and in five out of six cases, there is no statistically significant relationship between structural racism and whites’ health. So, you find, you know, shockingly consistent results and just, you know, these health outcomes are some of the most commonly used, especially when studying older adults. And so, I think that there’s this, you know, there’s a real signal that we’re picking up. And we had much more confidence in our findings because it was so consistent across these health outcomes and across these health studies. So, in a recent study, we also examined the relationship between a latent measure of structural racism and Black-white inequities in Covid 19 mortality rates. Right.

So, the regression estimates indicate that the relationship between social racism and Black, white inequality in Covid 19 mortality is positive and statistically significant, both in the bivariate model and net of covariates. And so, this again is a state level measure and collectively the findings you know, I would argue that the collectively our findings across these studies suggest that our latent variable approach has really strong predictive validity and we actually did measure it against benchmarked it against other metrics such as sort of a summative index that assumed equal weighting of the indicators and did not take into account correlations between their errors when we found that the latent measure actually explained more variation in health outcomes and also explained significantly more variation of any of the individual level indicators. And so that again, provides some evidence that there’s really there are some real benefits to taking a latent measurement approach. So, I think it’s also essential to measure and map cultural forms of racism that reflect racial schemas, logics and practices.

So broadly you know, we really need to be considering the roles of things like racialized violence, animus, resentment, hate speech, and biases, all of which have been shown to vary by place including across states. And so, in addition to well-established survey data resources, we should also be utilizing data and methods to capture utilizing, you know, more innovative data measures to capture anti-Blackness through geo coded data from things like internet search engines and computational approaches, scraping websites and even experiments. So, this map shows the spatial distribution of a latent measure that Reid DeAngelis and I are developing using these types of data and measures. And preliminary results show that it’s predictive of population health inequities. And so, we’re really encouraged about the possibility of combining these latent measures of racial schemas and logics, sort of cultural measures with the more institutional measures and looking at how the interplay between them and their relative contributions to population health inequities.

I should also mention that in a recent study published in the Journal of Health and Social Behavior, Patricia Home and Brittany King and I, we introduced a state level structural intersectionality approach to population health. And what it does is it really demonstrates an application of social intersectionality using administrative data sources similar to the ones that I discussed in the previous studies. To examine the relationship between macro level structural racism as well as structural sexism and economic inequality and looking at how they interplay between them, as well as their joint and individual contributions to health inequities across U.S. states. Right. And so, this study, I think, can really serve as a springboard and a data source for similar studies that are aiming to extend this research, in studying how state level structural, intersectional oppressions differentially shape health outcomes for various demographic groups. I should also note that numerous studies also really highlight the dynamic role that policies and politics play in shaping health inequities.

Obviously, Jennifer Montez is a new data set, is an excellent resource for studying the role of states in this regard. There are also some studies by biomedical engineer Jackie John and other colleagues that used novel, a novel database on racism related laws which has been shown to predict health. So, these and other data sources on racial policies such as three strikes laws, welfare reform, banning critical race theory and racialized disenfranchisement can really serve as important resources for research on health inequities. And, you know, the history of structural racism in the U.S. has really important implications for how we should really be approaching the measurement of it and quantifying its effects on these inequities. And there is suggest that historical racism directs, constructs and continues to mold contemporary structural racism as well as health outcomes. And so, in that vein you know, there have been several empirical studies that have shown that polities that had larger enslaved populations in 1860, have greater present-day inequities and poverty and economic mobility and also higher levels of contemporary pro-white bias, and that these can be linked to contemporary health outcomes as well, and that historical redlining practices underlie contemporary residential segregation patterns. This is becoming a well-documented social fact, as well as the fact that New Deal policies expanded the white middle class and are directly implicated in modern Black-white inequities and wealth. And so, it really shows the long arm of history in shaping contemporary health outcomes and moving forward. I think a couple of examples of measures to consider include variation and exposure to things like slavery, Jim Crow, lynchings, anti-miscegenation laws, stunned downtowns, the number of folks who are doing really good work in that space. We can think about exclusion from the economic benefits of the New Deal and GI bills, as well as racialized voter suppression.

And so, in many respects, I think what this literature is showing is that what’s past is prologue. And we’re seeing this with new laws, for example, the disproportionately disenfranchised Black and brown Americans. And in closing, I’d just like to highlight a couple, what I see as exciting opportunities for future research that I think will really advance our understanding of the links between racism and aging, health inequities, which I think can be used to inform ultimately efficacious racial equity solutions. So, for example, future studies should really better utilize longitudinal data to better understand the temporal dimensions of the relationships between structural racism and health such as the potential impacts of things like sensitive periods, durations of exposure, as well as causal effects. Right.

And moving forward, you know, I plan to use system dynamics modeling to explicitly model interdependence between forms of structural racism as well as feedback loops and lagged effects. I think that’s a really exciting area that we can start to really overlay temporal dimensions and a life force perspective with our understanding of the processes that ultimately lead to these wide health inequities that get larger and larger throughout the life course.

And also, multilevel research are really needed in this space in order to better understand the cross level structural races and linkages and the joint effects on racial stratification. So obviously, my talk here has been highlighting the role and really funny evidence of the role of states, which are really key. I hope that made that is clear, but of course, other levels also matter, right? and ultimately, you know, this is multifactorial and we should really be thinking about how structural racism across different levels, including state level influence, health.

And then, you know, as the data ecosystem is rapidly expanding, scholars are increasingly calling for a wider use of new sort of big data sources and social science research. And so, I’d just like to echo and expand upon these calls by recommending the use of these new approaches to address salient new research questions about how structural oppression shapes racial inequality.

And so harnessing digital trace data is especially useful as traditional data sources become increasingly costly, increasingly logistically complex and are becoming less representative of the target populations due to declining response rates as well as other selective forces. Also, moving forward, you know, I’d recommend testing the extent to which structural oppression affects inequality indirectly through intermediary social pathways such as unequal access to resources, things like education, income, health care, autonomy, and also exposure to risks, things like toxins, housing instability, victimization, as well as involvement in the criminal legal system and other pathogenic social conditions.

And so ultimately, this is really important. And to do this, we really need to address the and build upon really strengthen the data infrastructure on linking structural racism to health and the current data landscape for structural racism is rather confusing and scattershot.

As I alluded to at the beginning of the talk, you know, we’re willing to build a publicly available data infrastructure on structural racism to catalyze future research on its effects. And creating a data hub will reduce inefficiencies by increasing data sharing, coordination and innovation and so it’s essential that the data include contextual information at multiple spatial and temporal scales, obviously, including the state level. And I see a number of challenges and opportunities to really build a user-friendly data resource like this.

And currently, the process of linking existing data sets to contextual data can be cumbersome, but there are some wonderful opportunities and some recent examples of innovations that reduce these barriers and make it a lot easier, which Professor Montez will be discussing with us. So, I look forward to the Q&A.

Mark Mather, PRB: Great. Thanks so much, Tyson and as a reminder, if you do have a question, we have a Q&A box. So, I encourage you to type your questions into that box at any time. We’re going to take all of those questions at the end of the webinar. So, I will now turn it over to you, Jennifer.

Jennifer Karas Montez, Syracuse University: Great. Thank you. Tyson, I really appreciate your presentation. I love the historical perspective. It’s so important. And I can’t wait to read the 2025 annual review piece.

So, what I’m going to do with my time is give a high-level summary of some of the work that’s been going on using U.S. states to understand why U.S. life expectancy has not been keeping pace with other high-income countries over the last several decades. I don’t know if you can see this thing here where I’m going to try to hide it. Okay, great.

So, this work I’ve been involved in for several years now with this wonderful team. And I want to acknowledge also the funding that we received from NIA to do this work. So, I want to start off by just talking about why we’re focusing on states and state policies. If our goal is to understand what’s going on for the U.S. overall. Um, Just touch on some of the key learnings that we’ve uncovered over the last 5 or 6 years. Talk about how did we get here? Like, how did state policies end up being so important in explaining U.S. population health? And then where do we go from here? So, why are we focusing on states to understand U.S. Life expectancy. Well, this figure you’re looking at here has a line, a wiggly line for all 50 states. It shows their life expectancy trends from 1959 to 2019. And I pointed out Connecticut and Oklahoma, and I’ll do that a lot during the presentation because there are really interesting case study pretty illustrative of what’s happening. So, you can see these two states that we think of today is wildly different in so many ways, they weren’t always that different. So in1959, these two states had the exact same life expectancy. But you can see they’ve taken very different trajectories over this time period. And you’ll notice that, you know, there are some states, like Connecticut who, you know, are approaching, you know, 80, 81, 82 in terms of life expectancy. But there’s a lot of states that have kind of flatlined, if you will, since the mid-80s. And our thinking, our team’s thinking is that if we can explain why we have this divergence in life expectancy across states and why we have so many states that just really haven’t made progress in decades, then that gives us another piece to the puzzle in terms of why U.S. life expectancy is not doing what we’d like it to do.

So, I want to give you one other view of the same data, and in this view, instead of plotting all 50 states, I’m just going to plot the range in life expectancy across the states for every year. And this is what it looks like. And this data runs from 1970 to 2014. Because the study that I’m using this from examine those years. But what I want you to see here is that until 1984, states were actually becoming more alike in terms of their life expectancy. The range was shrinking. And in 1984, something happens and the range and life expectancy just keeps getting bigger and bigger and bigger. And if I were to continue this chart out through present day, you would see that range just grow year after year after year. So, you know, there are a number of explanations, a number of hypotheses for what might be happening here.

Our team has been focusing on the possibility that this divergence in life expectancy across states might be partly explained by the divergence in policies across states. So let me give you a couple of visuals of how states have diverged in their policies. So, this chart, it’s a little messy at first. It has 50 arrows. There’s an arrow here for every state. It’s not very important to figure out which state is which arrow. What these arrows indicate is how each state overall policy context has changed between 1970 and 2014. So, Jake Greenbank is a wonderful political scientist, created this overall measure of state’s policy context. And so, what I’m showing you here is where each state started on that measure in 1970. That’s the beginning of every arrow. And then where each state ended up in 2014 on that measure. And that’s the arrowhead. And so, what I want you to see is that we’ve got most states moving away from the center in terms of their overall policy context. Okay. So, they’re diverging just like states life expectancies are diverging. And again, I picked out Connecticut and Oklahoma so that you can see, you know, in the 70s, these states weren’t that different in terms of their policy context, but they sure are today. So, you might be thinking, well, give me some examples of how are these policies changed over time. So, I’m going to give you just four examples. This summary measure you’re looking at here has over 120 policies all wrapped in it. I’m just going to pull out four of those, four that we know are important for population health. So, let’s take minimum wage and earned income tax credit. Again, two policies that have pretty good evidence that these are important for population health. You can see in 1990, there’s effectively no difference between these two states. In in 1999, neither state offered an ITC. So, there’s absolutely no difference between these two states in these two very important economic policies. But by 2019, you can see these two states are wildly different in these two core economic policies. Let me give you one more example. I’m going to show you how these states have differed in terms of two very important health behavior policies. So, in 1990, these two states had almost identical taxes on a pack of cigarettes and pretty similar number of laws meant to increase the safety of firearms. But by 2019, these states, again wildly different. And it’s not just that a state like Connecticut in blue is moving in one direction in states like Oklahoma or just stuck. But you can see as states like Oklahoma are actually rolling back some of these policies that we know are good for population health. And you can see this most clearly in the firearm safety laws here, where the number of those laws has been rolled back in Oklahoma. So, let’s go back to this chart then. Now what I want to do is give you one more view of how state policy context have changed during this time period. So, what I’m going to do is I’m going to again take this overall summary measure of states policy context, and I’m going to plot the range across the states for every year in that measure. And this is what it looks like. So again, in 1970 until 1981, states were becoming more alike in terms of their overall policy contexts. I mean, it’s almost unimaginable today. But then after 1981, they become increasingly different, increasingly polarized, increasingly divergent. Whatever term you want to use in terms of their overall policy context. And so, if you were here five minutes ago, you’re thinking, I have seen a pattern similar to this before, and you have in fact. So, what I have here is now overlaying the two charts that show how the range in states policy has changed over time.

And the range and states life expectancy has changed over time. So bottom line, as states policy contexts are becoming more similar so were states. Life expectancies three years after states becoming start becoming more dissimilar in their policy environment, states start becoming more dissimilar in their life expectancy. So, at this point in our team’s journey, we thought we had developed some pretty compelling descriptive evidence that there’s a relationship here now. Is it causal? That’s what we wanted to find out. So, I’m going to walk you through some pretty high-level summaries of what we have. Think we’ve learned so far about whether that relationship is more than just a correlation.

So, we’ve found that actually U.S. life expectancy trends would have been significantly steeper if state policies hadn’t changed the way that they did. And that if we were to change all state policy, so all 50 states, if we were to change them all, to have either a very liberal or a very conservative policy context, we could alter us life expectancy by about 2 to 3 years, which is huge. That would put the U.S. about average among its peer countries, as opposed to being very securely at the bottom right now.

Changing state policies in this way would also alter the number of working age deaths each year by about 220,000, again, a very substantial number. So, in more recent work, we’ve been trying to put a more a finer understanding of where are these effects taking place for which causes of death are these effects happening and can we better understand the time lags under which these policies might have an effect? Do we see that policies have an immediate effect on working age mortality? Do we see that it takes a year or two years? How many years does it take? And so, I’m just going to summarize a piece of those findings. So, what you’re looking at here is how much the mortality rate of working age women would change if a state policy changed. And this is specifically CVD mortality among working age women. So, a lot of dots here. So let me walk you through what’s going on. So, look at the far left under the criminal justice policies. So, our analysis suggests that if we were to examine what would happen to working age women, CVD mortality during the very same year that a state’s criminal justice policies went from very conservative to very liberal. That was a lot of words. Let me say it again. So again, this is what we estimate.

What happened to working age women’s CVD mortality, If a state changed its criminal justice policies from conservative to liberal. So, we find that if we were to examine that in the very same year that that that policy was made, we would get a non-significant change in women’s CVD mortality. A year later, we start to see an effect, and within three years later, we start to see a significant reduction in women’s CVD mortality.

So, what this is saying is that if you believe these counterfactual analyses that it takes a while to see the benefits, the mortality benefits of moving from a conservative to a liberal criminal justice policy environment in the States. I’ll just walk you through a couple of other policies, gun safety policy. We find that we see almost an immediate effect in the reduction of women, CVD mortality when gun policies go from conservative to liberal.

And that effect seems to be stronger with each passing year. But there are other policies like health and welfare where we see an immediate effect, but over time that effect attenuates. So, what we take away from an analysis like this is that. The timing matters in our studies. And we don’t often do a very good job of taking timing into account. But imagine the implications. If I were to have only done this study examining no lag or a one-year lag, I would have walked away saying some policies don’t matter when they actually do or saying some do when they actually don’t matter after a given period of time.

And the other thing to take away from this is that not only do we need to pay more attention to it these lag times, but the appropriate lag time might depend on the specific policy that some policies just may take a longer time period to see a population health effect than others.

Another high level finding from our work is that the policies that have changed and polarized the most since the 80s happened to be the same policies that have the strongest associations with life expectancy and working age mortality, and those policies are mainly around labor and firearms.

And then the last finding I want to highlight, and this is not from our group, but it’s important. And I and I’m anticipating some of your questions later on, is that the growing disparities in working age mortality across states do not appear to be due to the changing socio-economic composition of a state’s populations.

So that’s, again, a very high level, a very selective set of what we’ve learned so far. So, what I want to do now is talk about how did we get here. And I want to do this because I want to make sure you, you leave this session realizing that the changes in these state’s policies, these are not exogenous changes, right? There are forces behind the scenes turning the knobs. So, if we want to move our analysis, you know, up the causal chain we need to be looking at who’s changing the knobs and why are they changing them. So, I’m going to point out, maybe my thing. It’s not moving. Okay.

So, I’m going to point out four interlocking forces. And I’ve got several citations down here. Really great in-depth books that you can read on this by sociologists, political scientists and others, a historian. And if you want just the quick and dirty that the very last article in the Milbank Quarterly covers these, these four issues.

So how did we get here? Four things really come together. One is the devolution of federal authority to the states, where states have gained increasing policymaking authority, especially since the Reagan administration. The other thing that has been happening that has given states this increasing power is there has been a proliferation of states enacting preemption laws to take away local authority, to do any number of things from raise the minimum wage, to mandate paid leave, to banning fracking. And so not only have states been given this additional authority by the federal government, they’ve been taking away authority from the states at the same time. Now, those two trends are not in and of themselves problematic but as a result of that, states have made very different decisions about their policies’ environments.

Some of those decisions have been unduly influenced by corporations, their interest groups and wealthy donors and some of the influences coming from the nationalization of political parties. And what I mean by that is, you know, we used to have a Republican version of Oklahoma and a different Republican version of Texas. But now there’s increasingly a Republican version across the U.S., just like there is an increasing Democrat version of policy context across the U.S. And I’m just highlighting this very quickly and again, I’ve given you some citations if you’re interested in digging into that further.

So, I want to conclude with talking about where do we go from here? And some of these recommendations are going to echo what Tyson presented earlier. I think my mouse is acting up here and I’m just pulling these ten ideas from editorial in the Milbank Quarterly this year on ten ways to better understand how shifting state policy contexts affect Americans health.

I’m not going to go through all ten, but I’m going to talk about some that keep me up at night. One of the things that we have got to do a better job with is giving more attention to policy bundles or indices. There is a very strong correlation across policies within any given state. If you were to tell me a state’s minimum wage, I can tell you almost everything else about that state. I can tell you can give you a good idea of what its tobacco taxes are, or whether it has an earned income tax credit, whether they’re right to work laws. Policies are becoming increasingly bundled. And so, the tendency in a lot of our work is to create summary indices or other kinds of indices, which I think is the right direction to go. But at the same time, I think we need some general guidance on how to use these indices responsibly. And there was a really great commentary by Harper and Andy last year around their concerns of using these kinds of indices. I don’t want to persuade anyone not to use indices, particularly because there is no single policy that can explain the difference between states. We wouldn’t choose a single policy to try to describe why U.S. life expectancy is different than that in Sweden, for example, because they’re just two completely different policy context and the same is true across states.

The other thing that I want to draw attention to, and this is going to echo what Tyson said, is that going forward, we need to pay more attention to lag times. We need to understand how these state level exposures accumulate across the life course. You know, by the time people are, you know, in the 30s, 40s and 50s, they have likely experience multiple different state policy context. They might have moved and so they experienced different context, or they might have stayed in their own state of residence. But, you know, as you saw earlier, states policy contexts are very dynamic and they’re changing.

So how do we capture this cumulative exposure to different contexts over people’s life course? And at the same time, how do we understand how the health effects of those exposures also evolve over time? So, I think, you know, version 2.0 of this work is has got to get just into this messy detail about how these dynamics, how to capture the dynamic interplay across the life course. And then the last point I want to draw on here is that I think, you know, as a group of researchers interested in this topic.

We need to develop an easy to implement method for accounting for inter-state migration. It is the question that comes up any time that those of us who are doing this work present it, and there’s no agreed upon way to account for it, it’s very, very difficult to account for it. In most surveys. You just don’t have the information. But can we not come up with some sort of agreed upon way, you know, baseline way to take this into account so that we can better isolate the effects of state policies on people’s health.

That is all I have. I’m going to stop here and say thank you so much. And I look forward to your questions.

Mark Mather, PRB: Thank you so much, Jennifer. We are now going to move to the Q&A. And so, as I mentioned before, if you have a question, we have a Q&A box. You’re welcome to put your questions into the box at the bottom of the screen.

And I will start with you, Dr. Tyson. There’s a question that came in through the chat asking if you could say a bit more about why different types of structural injustice vary in their geographic distribution. This person would have expected them to align more than they do.

Dr. Tyson Brown, Duke University: Yeah, that’s a great question. So, I’ll start by just noting that, you know, in my research, I argue that because racism is dynamic, flexible and really adaptive to socio historical context, that there are likely distinct contemporary racialized regimes, and that these regimes are characterized by different manifestations and modalities of racism across place. And so, whereas contemporary discrimination, discriminatory, legal and cultural forms of racism are especially pronounced in states in Southern and Appalachian regions. Findings from my research really illustrates how contemporary structural racism that’s manifest in discriminatory institutional contexts and racial inequities, that this is particularly severe in states and Midwestern and Northeastern regions.

And so, although the historical and modern roots of place-based differences in social races have not fully understood, you know, scholars have posited that that really the extreme degrees of contemporary structural racism reflected by racial inequality and institutional contexts in many northern states, them in part from institutionalized policies and practices of social control, racialized social control through exclusion and subordination. So, you can think about examples of resource hoarding, of redlining, of racial covenants and discriminatory policing and that these white supremacist tactics were increasingly deployed after the Great Migration because northern whites perceived the increasing Black population as a threat. Right, and so, given the fluid, shapeshifting nature of structural racism, it’s really important that future research investigate the etiology and consequences of these distinct contemporary racialized regimes across time and place. But that’s a really astute observation and frankly, we don’t know and so this is a really exciting time to be doing this research and I think it’s a really important time as well.

Mark Mather, PRB: For you, Jennifer, there’s a question in the chat, to what extent do changes in interstate migration due to increasing political polarization?

I think they’re talking about people moving because of the policy context. Perhaps, would that lead to a select group of unhealthier people in more conservative states and conversely, healthier people in in liberal states? Thinking about the change in interstate migration over time.

Jennifer Karas Montez, Syracuse University: That is a great question. So, I will say that in the ways that we have tried to account for interstate migration and also the study that I mentioned in the talk, we’ve not found that it is a major contributor. So that being said, I am not sure that that will those kind of null findings will hold up post 2020 due to both increasing polarization and people potentially moving to places that are more aligned with their political values, and the fact that, you know, we’re seeing a lot of people moving to red states, to Texas, to Florida, I mean, even Oklahoma. So, I don’t know, you know, on the whole how that’s all going to play out. But my working hypothesis at this time is that what we know about who moves and who doesn’t move might be different pre versus post 2020.

Mark Mather, PRB: Thank you. This question is I guess mainly for you, Tyson. But Jennifer, you’re welcome to respond in your future directions. You mentioned digital trace data, Tyson, could you expand a little bit more on what that type of data looks like, why it may be a future direction?

Dr. Tyson Brown, Duke University: I’d be glad to. So just a level set. Digital trace data includes things like social media activity, web browsing histories, search engine queries, e-commerce transactions, text messages, emails all where we live our lives today, right? And digitally and so there’s a lot of data out there and in my work, I argue that harnessing the data revolution, which is the rapid, you know, growth in data generation and storage analysis that’s driven by technological advances big data and digitization and transforming how information is used in decision making you know in research and everyday life. Right.

So, I think this is a really important and, and it’s especially critical, to use digital trace data to really capture what we termed as backstage cultural dimensions of racism. Right. And so, you don’t have to rely upon what people responses that they give in surveys because there’s social desirability. There’s a number of reasons that we may be getting not we may not be getting the full picture from survey data, which is still really important and even administrative, that can be really important. But there’s something unique about how we live our lives online that you know, they’re basically receipts. You know your digital life doesn’t lie, right? and we have a lot of digital traces, and so I see it as really, a really valuable way to complement more traditional data sources that many of us as demographers have used.

Mark Mather, PRB: In place and again, for you at this person, notice that there’s not a lot of overlap in the map to measures of structural racism with high values in the Midwest and West, and cultural racism with high values in the southeast and on the state level similar, I guess, to the other question, but how do you envision these measures potentially capturing different pathways for racism to impact population health?

Dr. Tyson Brown, Duke University: Yeah. Well, I guess see my previous response. You know, again, getting back to these contemporary racializing regimes, I would refer to the person who asked the question to the recent study. So, there’s a 2024 article in the Journal of Health and Social Paper. Between this author by myself and Patricia Home and also a couple forthcoming in your articles and your view of sociology and review of public health will be really digging deep with some of these issues and so I think this is really important. You know, the latter part of the question was, you know, what do I see as there, you know, sort of unique or joint pathways in shaping health. Right? So, whether you have sort of the institutional manifestations and you’ve got the more ideological, cultural dimensions and that is an empirical question that we really don’t know, but many of us are working on that. And so, you know, I hope that in a year we’ll have better answer and especially five years from now. But I think that really is one of the frontiers for understanding population health in general and more broadly, and then more specifically thinking about racial inequities in health including at the state level.

Mark Mather, PRB: Your question for either or both of you, is there an agreed upon way to incorporate different races living under alternative government structure like Native Americans or tribal lands, into measures of structural racism and population health when they might not be present in our standard data resources.

Dr. Tyson Brown, Duke University: I didn’t fully understand the question, but I will just note that I think it began by is there an agreement? and I would say no. You know, these are debate, you know, like any fields of science, there are contested debates. There are new revelations, there’s discoveries, we’re always innovating and I think that we’re always learning more about these sorts of racialized practices and processes and certainly I would note that, you know, really there is no one size fits all and that there are real limitations to all the ways in which we measure these things and how folks are coded, whether it’s self-reported, whether it’s by the interviewer, whether it’s, you know, there are other ways of getting at sort of trying to triangulate to figure out someone’s racial identity or status. But, none of them are perfect. And so, this is part of the job of trying to advance the field and do so in responsible manner. So, I appreciate the question.

Mark Mather, PRB: Do you want to say anything to that, Jennifer?

Jennifer Karas Montez, Syracuse University: Sure. I’ll just add that, I mean what the question reminds me of is just, you know, the need to examine heterogeneity more carefully and, you know, the need to go below the state level to understand some of these processes. You know, there the states are just super interesting unit of analysis. I mean, you know, we call them institutional actors. And, you know, I mean, Tyson made a great pitch for why states are important, but they’re not the only thing that matters. And so, I think to get at the kinds of detailed analyses that that question would require going below the state level.

I would also say that what it seems like is that, you know, states and probably also local environments too, seem to matter most for the health of people who are marginalized. We have this term colleges of firewall, right? So that if you have a college degree or higher, it almost doesn’t matter where you live, you’re going to have good health. But with each, you know, lower level of education, that the place that you live matters more and more for shaping your health. And so, but again I mean that those kinds of analyses are going to benefit from going below the state level.

Mark Mather, PRB: Great. And I just had one question for you, Tyson. You had mentioned things like hate speech and racial animus. And I am curious about how do we measure those types of structures, partly because they might be reported differently in different local jurisdictions or not reported at all in certain places. So, I’m wondering, is that where the social media comes in to capture some of those things, or is it a combination of social media and some of the criminal justice data?

Dr. Tyson Brown, Duke University: Yeah. Great question. I think that it’s like you mentioned, you know, I think it is really important to triangulate and use a variety of data sources. They all have their strengths and limitations and certainly reporting on official Bureau of Justice statistics on hate crimes as well. It’s got its limitations, to say the least. And there’s certainly variation across place about how and when they report if they report and so that data you know, it’s got major limitations but I think that we can get at things by looking at the proportion of hate groups and indexing it to the population size. Right?

So, I think that’s really revealing, you know, when we map that data, I think that, as you mentioned also that using things like social media data really can get at some of these sorts of things by whether it’s Google searches or people’s activity on other social media platforms and there’s also experiments that folks have done, including things like the AIT that get at sort of underlying logics and subconscious biases as well as survey data. I think that, you know, there survey data on racial resentment. If you map it, it’s in a rather predictable way, it varies across states in a predictable way and it’s highly correlated with other measures of racial essentialism and norms and things along those lines. So, I think that all of the above, frankly, you know, they all have their relative advantages and disadvantages.

Mark Mather, PRB: Well, we are at time, so I think we need to close here. But Tyson and Jennifer, thank you so much for joining this discussion. It’s an important and timely topic and for those who stuck around, thanks for joining. As I mentioned, this is being recorded. We will send you a link to that recording in the next few days. So, thanks everyone.

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Transcript

Diana Elliott: Great. Thank you all so much for joining us today. My name is Diana Elliott, and I’m the vice president of programs at Population Reference Bureau, or PRB. PRB is a not for profit and nonpartisan research organization that uses population data to improve the health and well-being of people in the US and globally. We are delighted to be hosting this webinar today with the Critical Labor Coalition and our special guest, former Labor Secretary Alexander Acosta. On the heels of Labor Day, we are reflecting on the state of the labor force. Anyone who reads the news these days is presented with an array of data in the US that suggests that any one time that we don’t have enough workers or enough workers with the right skill sets, or we have too many workers in certain professions or sectors. This webinar is an attempt to cut through the noise to present who is in the workforce, why we have long term challenges ahead of us, and some possible solutions.

I am delighted that both former Labor Secretary Alexander Acosta and CEO of the Critical Labor Coalition, Misty Chally, are here with us today to discuss these issues. First, we’ll hear remarks from Alexander Acosta, former US Secretary of Labor. He will present background about the state of the US labor force, drawing upon his experiences as the former head of the US Department of Labor. Next, I will present how demographic trends matter for the labor force now and in the future. Then Misty Chally will present information about the Critical Labor Coalition and why they are working to find solutions to labor shortages and the legislation they are seeking to advance. We will conclude with a Q&A session with all panelists, where we welcome audience questions about the workforce now in the future, and ways we can work towards solutions.

Finally, a bit of housekeeping before we begin. If you have any questions during the presentations, please type them into the question box in your webinar control panel. Attendees will be muted. We will also share a recording of the webinar after the event on PRB’s YouTube channel. And now I am delighted to introduce Alexander Acosta, former US Secretary of Labor, for his remarks.

Alexander Acosta: Diana, thank you. I appreciate the invitation from from you and from Misty to be part of this webinar and in particular, I appreciate the opportunity to be, you know, to to go over the data because I think there is so much discussion and, and, frankly, noise in this space that it’s important to take a step back and just look at that data and say, where does the data lead us? there’s a PowerPoint that I think you have, and I want to start with the first slide if if we could.

So, the first slide is a slide going back to the year 2000. that’s very simple. This tells so much of the story. It starts out with this is the labor force participation rate. All my data, I should say is from either the Bureau of Labor Statistics or the OECD, which is an international organization. These are the aggregators of data that are sort of the gold standard, in my opinion, in labor data. And I think we often focus on the unemployment rate. But what really matters in the long term is the labor force participation rate. Put simply, the unemployment rate is of those who are working or looking for jobs, what percentage cannot find jobs? The labor force participation rate is much broader, it says of the population, of our adult population that is not institutionalized. That is by, you know, excluding individuals who are in the military, who are in jail or in other institutions. Of those who could work, what percentage are either working or looking for work? And as you see, in 2000, the number was pretty close to 68%. And then there’s a pretty dramatic and steady decrease until about 2016 where it levels off, goes up a little bit, and then Covid hits and we haven’t quite recovered to where it was.

The next slide sort of puts it all in numbers with a little bit more specificity. And so, you see that we started out at 67.3%. By ‘04 we dropped about 1.2. We sort of hovered through ‘08. By 2012, we dropped again, 2.5 by 2016. We dropped another point. Between 2016 and 2020, we actually managed to go up. We went counter trend, for a short period of time and and then not only have we dropped again, but if you look at the projections that come from the Labor Department, the, the drop in the labor force, participation is expected to continue, through 2028 and again to 2032. you know, what’s truly frightening about this is that by 2034, the labor force participation rate, in other words, the percentage of Americans that are working or looking for work is going to be about the same level as the worst month of Covid. So if you think back to the worst month of Covid, all those folks that said, we’re not going to be part of the labor market, by 2034, that is going to be the everyday state of play in America, not according to me, but according to the Bureau of Labor Statistics. and the question is why it’s complicated, but it’s easier to say to some extent. Why not?

Moving to the next slide if we could. You know, I put this up here and this is from 20, from the year 2000 to to the year 2015. You know, it breaks different age cohorts down by race. And I put it up there because I think it’s important to recognize that the effect is, is quite comparable, regardless of race. You know, if anything, you see a larger percentage drop among Caucasians than among other racial or ethnic groups. But you see in this slide and the next slide, you see that, you know, race is not really, something that easily explains, you know, this massive, really, really substantial, massive drop in labor participation rate.

Moving to the next slide if we could. And again, the same issue. You know race is not the the explainer if anything. You know overall you see a larger drop in Caucasians than others. But race doesn’t explain, moving to the next slide. So, this is one of my, my favorite slides. Maybe favorite isn’t the right word. I think the most interesting slides here are the Bureau of Labor Statistics. They always do projections going out about ten years, and they break those projections down by age cohorts. And, and you see that they’re overall predicting a pretty substantial decrease in labor participation rate. in four years out, eight years out. And if you look on the website data, the trend continues, and you see that the trend is much stronger with men than women. the drop is much less for for women than it is for men. but you also see that the drop is greatest among the youngest age cohorts. And this matters because we often hear that part of the problem is that the baby boomers are retiring, that we’re- that our workforce is aging. And that is an issue because the baby boomers are a very hard-working generation. And as they age out, we lose a lot of, you know, both in terms of number but also in terms of workforce participation. We lose a generation that worked very hard, that was very large and that heavily participated in the workforce. But we also see that it doesn’t fully explain it because as new age cohorts enter the labor market, the younger you go, the larger the decrease in labor force participation rate. So, there is something about this decrease that is unrelated to the retirement of the baby boomers, or something about how we’re addressing, newer generations that either discourages or does not connect them to the labor force the way previous generations were connected.

Moving on to the next slide, if we could. So, this is, I think, something we don’t talk about enough and something that’s very important. This data comes from the OECD, which, as I said, is the gold standard for international data. They aggregate data from several countries. And this shows the United States when compared against, the G7 nations, and the eurozone nations. And as you see on the far right, this is in 2000 in red, you see the United States, we had the highest labor force participation rate compared to all the eurozone nations in the G7 nations. And I should say that this particular slide, pulls individuals from 25 to 64. And that’s important because we want to adjust different countries have different university systems, different points at which individuals stop being students and, and fully enter the labor force and different retirement ages. And so, the 25 to 64, is an important comparator when you’re looking internationally because you’re sort of cutting off the two age extremes to really prevent different retirement systems and different university systems from affecting the data. So, in 2000, we had the highest labor force participation rate compared to all our competitor countries.

Let’s look at the next slide though. So here we see by 2008 the United States the red bar was was pretty much right in the center compared to the eurozone countries. And let’s look at the next bar. The next slide I’m sorry. and so, this is 2016. And in 2016 you see that the United States now is one of the lowest rates of labor force participation rate compared to the eurozone countries, you know, and we’re far to the left. We’re, basically fourth from the bottom after as I look closer, after Italy, Greece and Belgium and all the other countries had a higher labor force participation rate. And I think this is important because much of what is happening here is not attributable to a broad global change but is really attributable to something happening within the United States compared to our competitor nations. Either we have done something to change our percentage and lower our percentage, or they have done more to correct the downward trend that I think we’re seeing globally. Because we have fallen behind quite substantially. You know, from being number one to being fourth from the bottom compared to the G7 and the Eurozone nations. And so, I put this out there because I think long term, you know, we can talk about solutions and there’s some solutions in the short term. Part of the issue here is that, you know, businesses want solutions now. They don’t want to talk about societal trends that might take 5 to 10 years to fix. And I understand that because businesses need workers now. And when you talk to Congress and when you talk to policymakers, sometimes it’s easier to present solutions that you can pass a law tomorrow and say, we’re going to have this influx of workers, but I don’t think we talk enough about this, this 20 year trend that, you know, that stopped for a little while, but has now restarted and and is going in the wrong direction because, you know, the United States should not be fourth or fifth from the bottom. We should be at the very top of this.

And so how do we change it? You know, and one final point. I’m not adverse to short term solutions. We need short term solutions, but we can’t implement short term solutions without paying attention to this long-term trend. If today we were to apply a labor force participation, the labor force participation rate that we had in the year 2000, right, we would have 16 million more workers. 16 million. And so, while we can talk about the unemployment rate being lower than it has been historically, for, you know, over the course of 20 years, it’s up a little bit now and it’s, you know, on the upper trend. But it’s you know, in the grand scheme, the real employment rate as a percentage of population is lower than it’s been in a long, long time, lower than it’s been in decades. And those 16 million individuals that are not engaged with the labor force really matter.

We are a different nation of seven out of ten people working to support the three out of ten that are not. Then if only six out of ten are working to support the four out of ten who aren’t. Not simply in terms of our population dynamics, but in terms of tax structures, distribution of tax burden, ability to repay debt, not to mention, you know, the impact that has on GDP. And so, I think this is an issue that we need to address in the long term, you know, with much more specificity. And with that, I’ll, I’ll yield the time. And I look forward to hearing from my fellow panelists.

Diana Elliott: All right. Thank you so much, Secretary Acosta. Really appreciate your remarks. Working at PRB, where we think a lot about demographics and population trends, it can be somewhat frustrating to see news stories that have such short-term focus. Right? Much as Secretary Acosta was suggesting so understanding point in time, employment is incredibly important for getting a pulse check on the economy. It tends to overshadow the bigger picture story.

Next slide. For example, the unemployment rate is followed very closely in the news cycle because it’s an important piece of evidence about whether or not, for example, we’re in a recession. But the larger context is not always presented fully in the news. As of July 2024, the unemployment rate was 4.3%. This is not as low as it was a year ago when it was 3.5%. But it’s still better than what economists consider to be full employment. And that detail isn’t always shared in the news stories. But the unemployment rate, again, doesn’t tell the full story. We’ve had a longer-term trend where there are more job openings than unemployed people, and even if some of these job openings are ghost jobs, something you’ll also hear about in the news or postings that employers don’t intend to fill. We can safely assume this 1.4 million gap between jobs and workers is not all ghost jobs. So actually, back to the previous slide, please. So, the unemployment rate is also a lagging indicator and is not terribly future looking. It all misses the nuance and context around who isn’t working and why, but demographics can fill in some of this information as I’ll walk through. The U.S. has had a rapidly changing age structure and changes in mortality and illness that may be contributing to long term challenges in the labor force. Further, policy decisions in the U.S. may contribute to reasons why not everyone who wants to work is actually working.

Next slide. So, as was hinted previously in the in the prior prior remarks, one of the biggest shifts in the U.S. and one that is changing the labor force right now is how we are aging. Between 2000 and 2023 and the 21st century alone, the U.S. median age has increased by 3.8 years. If you lined up every person in the U.S. from youngest to oldest in 2023, the person in the middle would be 39.1 years old. In part, this is because baby boomers, the large cohort born after World War II between 1946 and 1964 are aging. This is affected and is currently affecting the labor force because baby boomers are retiring. To put this into perspective, as of 2022, 57% of baby boomers were over the age of 65. And we know that by age 65, 90% of Americans are. Previous slide, please. 90% of Americans are already collecting Social Security. We also know that most retirees report having retired at age 62. This means that most baby boomers are retired. The youngest of baby boomers turns 60 this year, meaning all are eligible to access their retirement savings without penalty. And by 2030, most will be over the age of 65 and will have exited the labor force. One of the themes you may hear about in the news is the prediction that older people will live longer and work longer, but the evidence so far suggests that hasn’t come to pass for the majority of older Americans. While Warren Buffett may be hard at work at 94, the data suggests this isn’t the future for most people.

Next slide. So, another way to look at this is through the age dependency ratio, which looks at the share of those aged 65 and older relative to those of working age, ages 15 to 64. Since mid-2000, the age dependency ratio has reliably gone up every year. In short, we have a growing number of retirees, which has implications for Social Security and public pensions, for example.

Next slide. An important reason why this ratio is shifting is because our birthrate has declined in the U.S. since 2000, the total fertility rate has been well below the replacement rate. Why is 2007 a significant year for thinking about the labor force? Because those born in 2007 are now 17 years old and entering the labor force, the provisional fertility rate and 2023 total fertility rate was 1.6 births per women, down 2% from the previous year. As context, the replacement rate is generally considered to be 2.1. Put simply, there are too few young Americans and future workers being born to replace retirees. In the news, you may hear complaints about how young people aren’t working. I would argue that’s an incomplete statement. In fact, there just aren’t as many young people to fill roles, which makes workforce training programs all the more important in the larger U.S. context.

Next slide. And the U.S. is not alone in confronting these challenges. Our peer countries are also facing a shrinking share of the working age population. The share of the working age population in Japan has dipped below 60% through a combination of factors increased longevity, fewer births, and tight immigration policies. And there are adaptations to that new reality underway. The U.S. and Canada have both seen a decline since the mid 2000, and Canada remains slightly above the U.S., in part because they’ve implemented various policies to try to change that trajectory.

Next slide. Unfortunately, we also need to confront that deaths among working age adults have risen in the U.S. in recent years. Since 2010, as a result of various conditions, there have been a decrease, a decline in the number of working age adults in the U.S. Covid-19 certainly exacerbated this. In 2020, it’s estimated there were 58 excess deaths per 100,000 people ages 15 to 64. So excess deaths are not just from Covid-19, but from other illnesses that went untreated because of pandemic lockdowns. Further, long Covid symptoms may be depressing labor force participation, similar to general trends with Americans with disabilities. Workplaces may not be accommodating people with long Covid optimally, and others with long Covid may be leaving the workforce to handle their symptoms. One study estimated that 1.6 million workers were missing from the workforce in 2021 because of long Covid symptoms. So, because so little is known about the trajectory and treatment of long Covid symptoms, it’s unclear how permanently this will affect the labor force in the long run.

Next slide. This graphic from Paris 2022 publication “Dying Young,” authored by Richard Rogers of the University of Colorado at Boulder and coauthors, shows that the U.S. really stands apart from other peer countries for the probability of death among teenagers and young adults in the U.S. This suggests that there are health and safety policy challenges in the U.S. that are contributing to these sad and tragic outcomes. And other countries have done a better job creating safer environments for their young adults and accordingly, their future workforce.

Next slide. Demographers also think about immigration and how it matters for our labor force. Immigrants and U.S.-born children are a significant share of the overall labor force. but in recent years, immigration policies have contributed to backlogs, which made things worse during the pandemic. While things have mostly returned to pre-pandemic levels, there remain persistent problems with issuing work permits and visas to immigrants who have entered the country legally. For context, in 2023, the overall population added 1.6 million people. This is despite a falling birth rate. The census attributes this increase to the resumption of post-pandemic norms around immigration, as well as fewer deaths following the pandemic uptick.

Next slide. Beth Jarosz at PBB analyzed the most recent Census Bureau projections in a blog published in 20th November of 2023, and describes how the most likely scenario for the future population of the U.S. is for us to reach a high point in our population around 2080, and then to begin slowly losing population with us reaching the year 2100 with about 366 million people. For perspective, a baby born today would be 76 years old in 2100. And these numbers in part reflect our slowing fertility in the U.S. However, if immigration were to slow or to be halted in the U.S., we reached these inflection points sooner, potentially within the next 1 to 2 decades.

Next slide. In fact, she shows that within 20 years the main series or the most likely scenario for the future shows that within 20 years, deaths will outnumber births. This is all accelerated with the curtailment of immigration from current levels. Next slide. But let’s move away from a doom and gloom scenario, because policy matters tremendously in terms of how we confront these demographic challenges, we’ll think about that with respect to the U.S. labor force.

Next slide. So one way to confront the demographic challenges is to think about who in the working age population would likely be more engaged with work and how we can address those barriers. One group is women, particularly those with young children. The U.S. is notable among our peer countries for a lack of family friendly policies. This limits women’s full labor force participation. That said, women’s labor force participation is now above pre-pandemic levels at 77.6%, but it is still lowest among those with young children. For perspective, Canada’s labor force participation rate for women is 84.9% and is notable for women with young children. The Canadian government has invested billions in recent years to cut childcare costs for working parents. One of the stories you may hear about in the news is that men’s labor force participation rate is also down. That is true from a historical perspective, but it remains higher than women’s rates. men, for example, have a labor force participation rate at 89.1%. Missing from these news stories is why there’s even a gap at all between men’s and women’s labor force participation rates, when women are now outpacing men in their educational training, and the U.S. states are often policy laboratories for what could be. One example to elevate here is New Mexico and its shift to prioritize early childhood education and care. They created a state level department, increased investments in early childhood education, and expanded subsidies for families. This could be a state to watch in coming years for policy examples that help working families and improve parents’ engagement in work.

Next slide. Another group that could be better engaged with the labor force are people with disabilities. In fact, this group of workers saw improved employment during the pandemic, in part because remote work enhance their abilities to engage with work. Between 2021 and 2022. There was a notable increase in their employment and a notable decline in their unemployment. That said, for people with disabilities, their unemployment rate is still two times higher than those without them. Studies have shown that accommodations matter for the employment of people with disabilities. Nearly half of needed accommodations are free, and for those with a one-time cost, the expense is typically $300. So again, states offer examples for policy ideas to engage people with disabilities who are eager to join and be a part of the labor force. For example, Ohio established the state’s vocational apprentice program in 2019, which are paid apprenticeship opportunities within state government. This not only helps people with disabilities enhance their resume and potentially find a permanent state government job, but it also helps to fill gaps within state government offices.

Next slide. So, let’s reflect on what we know about the state of the U.S. labor force. Births have slowed in the U.S., and there is neither a growing cohort of young people nor older Americans who will be tomorrow’s workers. Challenges such as mortality and morbidity present uniquely American challenges in our labor force. As we look to the future, we’re confronting a demographic future where there are fewer workers amidst an increasingly aging population. But policy can intervene to better engage workers who have been sidelined and want to be more engaged in work. There are examples happening in other countries, and even within the U.S., that suggest ways to attract, retain and train the workforce amidst overarching demographic shifts in the labor force.

Next slide. So, thank you. And now at this point, I’m going to turn it over to Misty Chally of the Critical Labor Coalition to additionally share how her group is working on legislative solutions to these issues.

Misty Chally: Thank you, Diana, and thank you for everyone who took the time to join our webinar today. Just waiting for the slides in a moment. And while we wait, I would just like to mention an add-on to the Secretary and Diana’s comments about the workforce. I think also what we’re seeing is the workforce, the nature of the workforce has changed, with a lot of people working from home and, you know, having flexibility as an Uber driver and setting their own schedules. We’re seeing a lot of people leaving places of employment where you need in-person attendance, if you will, a set schedule, somebody to be in a restaurant or a hotel or a retail location, where you actually need people physically there. And so that’s why when you go to a restaurant and you know, there’s a long wait, but you see a lot of empty tables, it’s because of the labor shortage, because there simply are not enough workers in those in person needed areas, to fill those spots. So, want to just to add that to the conversation and yes, AI does help in some ways, and definitely contributes, but you cannot replace all workers with I although it does help the employers and the workers in many ways. So, it looks like we’re we’re back up. So, thank you for letting me give my little personal opinion on that.

My name is Misty Chally, executive director of the Critical Labor Coalition. My background is in representing franchisees and franchisee associations. And so, this issue came up when I was talking to a number of different franchisee associations. called the Critical Labor Coalition, and they represent everybody from Planet Fitness and Domino’s to Burger King and Meineke. So, all different industries. And we were talking about, you know, what are our key issues, regardless of industry. And the issue was the labor shortage. Everybody was and continues to have an issue with the labor shortage. and that’s really where the Critical Labor Coalition was formed.

So next slide please. So, I formed a Critical Labor Coalition in July of 2022. It’s a nonprofit 501(c)(4) to address the issues of the labor shortage. We seek legislative solutions to address labor shortage, understanding that there is no silver bullet here. I mean, there are different ways to approach it. and that’s what we do. Our members are trade associations, corporations, individual business owners. And I should note that we advocate for bipartisan policies, that incentivize individuals to return to work and that grow the workforce. And how we do that is by focusing on different communities of workers. How do we get them into the workforce? Everybody from guest workers to seniors to, entry level workers to veterans, to those in the Second Chance community, the disability community and caregivers. We look at them individually and collectively to determine how do we get them to return or enter the workforce.

Next slide. These are our members right now, as I mentioned, trade associations, individual employers like Chipotle, the Restaurant Association, hoteliers, um staffing services, the um Amusement Park Association, food distributors. I mean, everybody of every industry is still having this problem. SHRM, representing the human resource community of everybody continues to have this issue. And so, I am honored to have them as members of our coalition.

Next slide. So how do we get something done? How do we address this labor shortage? Well, the Critical Labor coalition focuses on two issue areas. One: How do we grow our workforce? And two: How do we promote tax incentives to get those in the country already in the country, incentivized to enter or reenter the workforce? And I’ll go into these, individually.

So next slide please. So, when we’re talking about what are the tax incentives, CLC uh supports a number of different tax incentives. one being a bill that would expand the work opportunity tax credit or WOTC, and that is a tax credit for employers to hire from, certain communities that face roadblocks to entry. That bill was initially or WOTC was initially passed in 1997 and hasn’t been updated since. So, this bill would increase the percentage of the credit from 40 to 50% of up to $6,000. Again, these are not silver bullets. These are not significant amounts of money, but they help get people back to work. And then it has a provision that would provide additional support if those workers work at least 400 hours or stay in their employment. EITC for Older Workers Act. EITC stands for the Earned Income Tax Credit, and this is a tax credit that would expand to include seniors over 65 without an eligible dependent. Right now, to qualify for the Earned Income Tax Credit, you have to be part of a specific community similar to WOTC and earn under a specific amount. But right now, if you are older than 65, you can’t get the earned income tax credit. And so, what this bill does is it eliminates the top age restriction for EitC eligibility. And the third one, the credit for Caring Act is bipartisan bicameral bill. And it gives a tax credit to people that are family caregivers, those that go to work, come home and have caregiving expenses that they then have to go and take care of a loved one, which is very broadly defined. and so again, it helps those people that have to go to work and then come home and take care of a loved one. And I should mention, our Coalition works with what we call strange bedfellows. So, while we represent the business community, we’re working with AARP, on these issues, as well as nonprofits, antipoverty centers like Golden State opportunity, out of California and where we want to show Congress that this is not a partisan issue. Businesses support this. AARP supports this, antipoverty group supports this. This is just a workforce issue.

Next slide please. And then when we focus on workforce growth how do we get more people here? Again, we are working with groups like Refugees International, the Asylum Seekers Advocacy Project and other groups to promote these pieces of legislation that will help get more workers here, one being the Essential Workers for Economic Advancement Act. Right now, there is no real visa program for those that are in nonagricultural less skilled positions. There are seasonal workers, but our members like restaurants and hoteliers and others, they need people year-round. So, this bill would introduce an H-2C visa program, that would allow for individuals to come over. It’s a nonimmigrant visa program, and work in the country, get some experience based on need. and there are economic triggers to make sure that those workers are needed, that there is low unemployment in the areas, and that the employers have been looking for somebody to fill that position for a certain period of time as well. The Asylum Seekers Work Authorization Act, is a great solution, I believe, to get people back into the workforce that are already here. Again, a bipartisan, bicameral bill, that would shorten the waiting period for asylum seekers to receive work authorizations. as many of you know, when asylum seekers come here, they have to wait 180 days to even apply for a for work authorization. This bill would reduce that deadline to 30 days and then they could apply and start working. and so, this bill would get the people who are staying in hotels and being subsidized by the government to actually work in those hotels who actually need the workers, and they want to work, we want them to work. So, it’s common sense, a bill that we really would love to pass Congress. The Senate and the House bills are, are two different versions of the same bill, but we support both of them because we just want people to get back to work.

Next slide. And just some ways in how we do that. We do congressional briefings quite frequently. That right there is the future of the workforce caucus briefing. On your left and on your right. We did a briefing for the New Democrat Coalition. talking to them about workforce issues. And we do many of these every year.

Next slide. Just a couple other things. We had the pleasure of having Diana speak to our group and provide, data and information, really, really interesting data. To our group, we do many, many hill visits to House and Senate offices. and we do briefings with groups like the Problem Solvers, and other coalitions. whose goal is to pass bipartisan legislation. We do webinars like this. We did a webinar on fair chance hiring, second chance hiring, with, the American Probation and Parole Association, which was, great to have them on board.

Next slide. Finally, we do digital ads in Politico and Bloomberg. And this on the top is an ad that we put in a number of different electronic media. And it’s just an astounding number, as Diana mentioned, if every unemployed person had a job, we would still have over a million unfilled jobs. And that’s kind of a startling number for some people and really kind of hits home to what the problem is.

Next slide. And just as an opportunity, I was on a podcast that will be available tomorrow, but wanted to give you guys a sneak peak. The Friday Reporter is a great podcast that goes into some of the issues that are going on. in DC, a lot of reporters, and congressional staff, are subscribed. So if you scan that QR code, you can get a sneak peek of what we were talking about on this podcast, which is more in depth discussion of the labor shortage.

Next slide. And I would just conclude by saying, you know, we welcome everyone to the conversation. So please feel free. We would love for you to follow us and check out our website. talk to us more. That’s my email address. and and get involved in the conversation. We certainly need the help. And again, thank you all for joining. And I’m going to send it back to Diana, and Secretary Acosta to answer some questions.

Diana Elliott: Great. Thank you. and just a reminder to put questions in the Q&A. I also have a few questions where I’m going to use, you know, sort of moderator’s privilege and ask a question of my co-panelists. So first off, I think I’d love to hear from both of you. You know, we’ve heard a lot about challenges right now. are there bright spots that you see on the horizon for our labor force? in the wake of demographic change in the wake of structural changes that we’re seeing?

Alexander Acosta: So, let me take it. Take it first. if I could. I do think there’s a bright spot in that. I think this is, you know, the first time that I sort of addressed the issue and I focused my personal view is that a lot of this has to do with our education system. I saw a lot of heads nodding, and I’m seeing more and more heads nodding. You know, I, I had early on as secretary and meeting with, community members from a city in Texas and a businessperson said, we need more welders and I’m willing to start a welder out at 60,000 right now. And the president of a community college said, that’s great. We’ll start a bachelor’s degree in welding. And I’m thinking, excuse me. The answer to more welders is we’re going to start a bachelor’s degree in welding. Is that really the case? You know, I think starting in the ‘70s, for all the right reasons. we started subsidizing education, particularly college education, in the matter of trillions. But along the way, we forgot that there are all these folks out there that aren’t going to college.

And if you were to break down, I showed a lot of data. If you were to break down the the data from the Bureau of Labor Statistics by college, whether you’ve attained a college degree, whether it’s, more than high school or high school, only you see that the biggest drop in labor force participation rate isn’t among the college students. It’s among those that don’t have college. And it’s really among what we’ll call the service workers, the construction workers, folks that work with their hands. And along the way, we’ve done three things. One, we say that college education is education at the Department of Labor. And if you don’t go to college, you get workforce training, I’m sorry, call it education at the Department of Education. And if you don’t go to college, it’s workforce training at the Department of Labor. Why is learning to be a welder any less an educational experience than going to college and learning to be a nurse’s aide? It is not. And language matters. It’s all education.

Two, we subsidize college education to the trillions of dollars, but if you want to learn to be a welder, you have to pay for it yourself. All these college loans are not available. All the Pell Grants are not available. And that matters. And so, we are biasing folks in favor of jobs that may not be their first line of preference. I gave this talk in Boston once, and the person running the audiovisual came up to me afterward and said, you know, I went to, I forget if it was Boston College or Boston University, I’m still paying off the loans. And then afterwards I had to go and get educated to run audio-visual equipment, because I make more running audio-visual equipment than I do from my college degree. And not only do we subsidize them, but now we’re forgiving all those college loans. But what are we doing for all those folks that that are working with their hands?

And then finally, I’d say even the way we talk about this. Right. You know, how often in our communities have we heard we have a health care crisis? We need to expand our nursing schools or medical schools. and we do, and I have no issue with that. But then how often have you heard we don’t have enough folks to build those hospitals to, you know, to work inside those hospitals as service workers. Do we then say we need to go out and create job educations for them, or do we talk about immigration as a solution? Do we really treat all tracks equally and say, is the goal a family sustaining wage, or have we started biasing the conversation in favor of those that have our backgrounds? All of us on this talk on this panel went to college is our tendency. Just think about this from the perspective of the college graduate. And, and if you look at the labor force data, you see that the biggest declines are not among the college graduates, but among those that didn’t go to college. And what are we doing to address them?

Final point, and this is where I think the business community and I disagree a little bit. I have no issue with short term solutions, but if short term solutions bring in more workers from abroad, you’re driving down wages. And that’s discouraging a lot of Americans from joining the labor force. And so think back 20 years ago, how many neighborhood kids would go and, let’s say, mow lawns and and are they doing that now? And if they’re not, why are they not doing that? Is it that the wages have not kept pace and that therefore what what economists would call the reservation price of labor and a lot of these service industries, are really to some extent reduced because of the immigration flows? Because, you know, according to, to the data that we saw, if we have low immigration, we’ll have 12 million fewer workers. But if we return to the 2000 labor force participation numbers we’ll have 16 million more workers. And so, to some extent, the short-term solutions undermine the long-term policy shifts that sort of my perspective.

Diana Elliott: I think I can piggyback off of that with a bright spot I see which prior to coming to PRB, I worked on apprenticeship programs, and I feel like apprenticeships are a bright spot for helping people who, perhaps cannot afford to do not want to go to college right away, or that’s not something that they’re planning to do to have that training program sort of with the employer, have that combination of employer based learning and learning in the classroom is really a tremendous benefit. And I’ve been really encouraged by an uptick in apprenticeship programs, for example, to that welder who or that, you know, the welder who needed more welders? I would say. Have you considered, have you considered an apprenticeship program or sponsoring apprentices yourself? In, in the past, right, post-World War II, we had more employers who took an active role in training, and that kind of faded away. And there is a role for employers to be more involved in training. Misty, do you have a bright spot? Before I go to some of these great questions coming in from from, participants?

Misty Chally: Yes, and I would like to respond to some of the, the income and wage questions, but I will say that, bright spot, I think whether because there are many expiring tax credits at the end of next year or because Congress wants to get something done, I do think we are going to see legislation that will help address the workforce shortage pass next session. Because it, honestly, it has to. A lot of the provisions passed in the Tax Cuts and Jobs Act expire at the end of next year. And so, you are seeing a lot, even now, of members organizing themselves and discussing how to help, and the Critical Labor Coalition is certainly part of that discussion.

Alexander Acosta: If I could, Diana, I know that there are a lot of questions, but to respond a little bit to, to your, I think, point about apprenticeships, which is absolutely correct. And it’s a bright spot. You know, one of the weaknesses is that we’re asking employers to step up and fund these apprenticeship programs. Yet we fund college education, right? We don’t ask hospitals to fund the cost of educating nurses. So why should we ask welding companies to fund the cost of educating welders and one substantial difference between us and a lot of Europe is Europe is much better than we are at treating all types of education horizontally equally. And so, you know, community colleges, you know, aren’t what they once were. They’re focusing much more on college, you know, on full college degrees rather than vocational.

There’s a fascinating school in San Antonio. It’s called the Construction Career Academy. It’s a public school, and it’s a magnet program, just like we have high achieving Stem magnet programs. and they have more students and more families applying that they can fill. And every student graduates with the focus on either pipe-fitting, on carpentry, on construction management. And I forget the fourth and the, the fascinating part about it is they then teach math in the context of, how do you keep your books in English in the context of how do you write a business proposal? And you have students that might not otherwise be engaged in high school, fully engaged in high school. And those students have amazing success. And when I visited, the principal said, every year we have X number of students that graduate with scholarships and go on to college, and Y number of students that graduate with job certifications that have a job. And I thought that that equating of the two career paths, the two tracks, the family sustaining wages was wonderful. But why am I only aware of one public school district that has that?

Diana Elliott: Excellent. Um, fair point. Misty, there is a question that feels designed for you to address based on your experience with the coalition. So, it says, what is your opinion on the role of wages to incentivize people to enter the labor force?

Misty Chally: Right. And thank you for that. And I think Secretary Acosta and I will disagree on this, but, you know, coming from the franchisee small business world, I will tell you that the average starting wage, and don’t quote me on this, is about $20 an hour to work in a Burger King. And there’s a reason for that because there are not enough workers. So, they will, their income has increased, their salary has increased, their wages have increased. They’re getting a lot of our members to provide benefits like savings plans, college tuition plans, all of those. And I will say that, you know, the service industry, honestly, I think gets a bad rap for, for being kind of a starting job. I will tell you that many of these jobs, if you have no experience, need to put something on your resume. Want to get started? You can start. And I know many franchisees have started as a dishwasher and if you are a hard worker, I will tell you you will move up in that, in that business, in that restaurant, in that hotel, very quickly. And they have their own training programs for individuals that want to do that. So, they do provide many opportunities that people don’t often see to people that need jobs.

And I’ll, I’ll further say, that the wages issue, and I know it’s been front and center. It, there are, there are resulting effects from an increase in wages that I honestly didn’t understand until I spoke to franchisees that were suffering from this. So, let’s say you are a McDonald’s franchisee, and you raise the wages of your workers, your entry level workers, which means you then have to raise the wages of those managers and the like. And as a franchisee, you are, what you take home is the bottom line, right? What the franchisor takes is the top line. So, if you are paying individuals more, then you’re taking home less. And honestly, if you earn one franchise, this is not, you’re not buying yachts and sailing along the Riviera. And then you’re talking about raising the price of a Big Mac. So, when we’re seeing people complaining about a Happy, or not a Happy Meal, you know, an extra value meal being $15, $20, that’s, that’s a reason why. And so, what do they do? They can go get a kiosk that will be cheaper than paying for somebody to stand and take your order. So, there are a lot of different effects of raising wages. And while I understand that argument, you know, there are, that may actually decrease the number of available jobs in the U.S. So, that is my two cents and you’re seeing it in California where, you know, there’s a law that requires, I think it’s $20 an hour for quick service, and all the franchisees I know are switching to kiosks because they need to make a living as well.

Alexander Acosta: So let me let me just respond, Misty, because, because you said that we might disagree, and I don’t disagree with your, your specific point. You know, national franchises pay very well and and one of the results that you saw with the minimum wage in California, where a number of restaurants are closing down, switching to kiosks, I agree with all of that. My point was a broader one. And, and I think it applies less in the franchise area than other industries that, simply, if we believe in the free market, we need to be equal opportunity free market, you know, folks. And if we believe in the free market for goods, we also have to believe in the free market for labor. And at the end of the day, you know, while legal immigration is necessary and brings incredible, incredible people and, and knowledge to the U.S. –  and this is not an anti-immigration statement because I think legal immigration is critical. The reality is that if we focus immigration on just, we need to fill the service sector. So, let’s bring in folks to fill that in.

To some extent, supply-demand means we are intervening in the free market for labor. I don’t think, you know, personally, I think one of the key drivers for franchises is not just wages, but all the regulations and the benefit costs, you know, around hiring a person that can, you know, almost increase the cost of a hire by 50, 60, 70%. And there’s so many other issues around hires, particularly, you know, in franchised as the franchise or to get liability for their franchisee that it makes hiring the franchise world very expensive. So, I don’t think we disagree with respect to, let’s say, the McDonald’s, which is the example that you used.

Misty Chally: No, I agree with that. And I think what you have to look at, what we used as a tool is look at the profit per employee, look at the industries that are not making a lot of profit per employee and see if they can handle, you know, any type of additional regulation, legislation, price increases and the like. So, thank you for that question, Diana.

Diana Elliott: Yeah. Thank you. I want to note that we are actually over time, but looking through the questions that people sent in, although we may not have asked your exact question, I think we touched upon a host of issues raised from vocational school apprenticeships, the wage challenges, to even robotics or kiosks being used. So absolutely, I encourage everyone to keep the conversation going via social media. Um, stay tuned. I think there’s a lot of material here for us to think about a post-event blog as well.

Keep asking your questions. We would love to think more about this and respond to you on social media. And if you haven’t already, go to prb.org. Consider making a donation so we can keep fantastic panels like this going. We’d love to do more of this. So, thank you so much for tuning in and joining us. And I want to thank Misty and Secretary Acosta for participating and really kicking off our Labor Day week in the best way I could imagine. So, thank you to everyone for joining and for asking great questions, and we hope to see you soon. Enjoy your afternoon.

Alexander Acosta: Thank you.

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Transcript

Beth Jarosz, PRB: Welcome, everyone. I’m Beth Jarosz, Senior Program Director at the Population Reference Bureau, and I want to welcome you all to today’s discussion.

As we were preparing for this webinar, I started to write a really formal introduction to this talk. But as I was writing, I kept thinking about my grandmother, Alice. Her story began almost a century before the examples gathered in Dr. Calarco’s research but mirrors many of them so closely: pressure to get married, poverty, violence, and very few resources to teach out there.

It’s been generations. The same patterns still play out today. And it’s not like we don’t know these things. Researchers have been working for years to understand how policies can uplift people or leave them behind. We know that policies in the U.S. have a history of burdening women with caregiving responsibilities and offering them limited protections relative to peers and many other nations.

To be clear, we’re using the word women today in a gender-expansive way that encompasses cis women, trans women, people with a uterus, people who’ve had hysterectomies but identify as women, people who are parents, and those who are child-free. Under that umbrella, we find a group of people who tend to be marginalized by U.S. policy, with marginalization that cuts much deeper for Black women, Indigenous women, Hispanic and Latino women, disabled women, and trans women, to name just a few.

Today, we’re going to unpack some of the ways in which women are asked to hold it together. For the discussion, I’m joined by an all-star cast: Dr. Jessica Calarco of the University of Wisconsin–Madison; Dr. Tiffany Green, also of the University of Wisconsin–Madison; Dr. Karen Benjamin Guzzo of the University of North Carolina at Chapel Hill; and Jocelyn Foye of the Womxn Project. We’ll hear from all four panelists and will round out the hour with Q&A.

If you have questions, please type them into the Q&A box. I’ll ask as many of your questions as we can during that Q&A portion. Without further ado, I’m going to invite Jess to begin.

Jessica Calarco, author of Holding It Together: Thank you so much to the PRB team for inviting me. Thank you all for being here today.

And thank you also to the, uh, you know, um, the panelists who are helping to flesh out this topic with more details and insights from their expertise of Karen and Tiffany and Jocelyn. It’s a pleasure to be here with all of you, and I’m so grateful for your work, um, engaging with this material and being part of this conversation.

Um, and thanks, a note of thanks also to the research team that contributed to the work that I’ll talk about today, which included, um, a very large number of graduate and undergraduate students and staff members who helped me produce the research that I’ll be sharing in my talk today.

So I’ll start off here by alluding to or kind of building on what Beth mentioned, this idea that other countries—other, especially high-income countries—have invested in social safety nets to help people manage risk. They use taxes and regulations, especially on wealthy people and corporations, to protect people from poverty, give them a leg up in reaching economic opportunities, and give them the time and energy and incentive to participate and contribute to a shared project of care.

In the U.S., we have instead tried to DIY society. We’ve kept taxes low, we’ve slashed huge holes in the social safety net that we do have, and we’ve told people that if they just make good choices, they won’t actually need government support at all.

Now, the problem with this model is that you can’t actually DIY society. Essentially forcing people to manage all that risk on their own has left many American families and communities teetering on the edge of collapse. And yet, as I’ll talk about today, we haven’t collapsed in part because we have disproportionately women being the ones who are holding it together, filling in the gaps in our economy and the gaps in our threadbare social safety net.

So to illustrate what I’m getting at here, let me tell you the story of a mom that I’ll call Brooke. Brooke was raised in a conservative, white, working-class family in rural Indiana, and her parents had a volatile relationship when she was growing up, and given that upbringing, Brooke never wanted to have kids of her own. But then, like many young women, she ended up accidentally getting pregnant in college.

Brooke and her boyfriend Brendon initially planned to get an abortion, and Brendon’s parents even offered to pay. But then Brooke’s parents found out, and Brooke’s mom persuaded Brooke to keep the baby, promising that she would help both with raising the baby and also with helping Brooke finish college.

Once Brooke’s son Carter was born, though, Brooke’s parents told her they couldn’t afford to pay or help her pay for both child care and for college, and in the wake of that decision, Brooke ended up dropping out of college, moving herself and Carter into a women’s shelter and enrolling in welfare. And because welfare came with work requirements, Brooke also took the first job that she could find, which was a part-time minimum wage job in retail that she hated. And she eventually found a full-time job at a child-care center, but that job also paid only around minimum wage. That said, it did come with free child care, and so this was appealing because at the time she was paying almost as much for child care as she was for rent.

And so at the same time, even when she got promoted to assistant director of the center a few years later, Brooke’s salary was still only $25,000 a year. And given the precarity of that situation, Brooke thought about trying to go back to college to, to get a nursing degree. But Brooke just couldn’t figure out a way to make it work. She didn’t trust her parents to watch Carter, so night classes weren’t an option, and quitting her job, even with how little it paid, seemed too risky. So Brooke just kept working at the child-care center, and she was still working there five years later and still hadn’t finished her college degree.

So Brooke is one of the hundreds of mothers that my team and I interviewed for this book between 2019 and 2022. We conducted more than 400 hours of in-depth interviews with moms and their partners from across the socioeconomic and racial, ethnic, and political spectrum. Most of those families were initially recruited through prenatal clinics in Indiana, so I also conducted two national surveys, each with more than 2,000 parents of kids under 18 from across the U.S.

And what I find in the data, and what Brooke’s story illustrates, is that women’s unpaid and underpaid labor helps to maintain this illusion of a DIY society. It makes it seem as though we can get by without a sturdy social safety net. Brooke’s story also illustrates a second piece of the equation here, which is that to facilitate this kind of exploitation, the U.S. has tried to trap women in motherhood and leave them with nowhere to turn for support in holding it together for their children and nowhere to hide when others ask them to hold even more.

And I talk in the book about how this system of exploitation is, is particularly damaging for low-income and middle-income women and disproportionately for Black and Latino women and women from other racially marginalized groups. In the absence of a decent social safety net, women in these groups can be easily forced into having or raising children or more children than they planned. And once they’re caught in that kind of motherhood trap, they can be easily forced to fill in the other gaps in our economy and also in our social safety net.

So to that end, to give you another story, I’ll talk about a mom I call Patricia. Before the pandemic, Patricia, who’s a Black mom, was still married to her husband, Rodney, and they had three kids, a toddler and two in elementary school. At that point, Patricia was working full time from home as a customer service rep, and Rodney was working full time in construction, and they were earning less than $30,000 a year combined.

Patricia, unlike Rodney, had some college education and she might have been able to find a higher-paying job, but she’d taken her customer service job, even though she found it repetitive and demoralizing, because it was the best remote work job that she could get before the pandemic. And being able to work remotely meant that Patricia didn’t have to pay for afterschool care or make alternate arrangements if the kids got sick.

When the pandemic hit, though, that arrangement ultimately meant that Patricia and Rodney never even talked about who would care for the kids when, you know, schools and child-care centers closed. That responsibility just fell to Patricia, and Rodney kept leaving the house every day for work.

Now, this kind of pandemic parenting took a huge toll on Patricia. The kids were constantly interrupting during her work time, leaving her frustrated and overwhelmed. She talked about the guilt that she felt, saying, “When it’s time to clock out, I need to not clock out mentally as a mother too.” And given that guilt, Patricia decided in the fall of 2020 to cut back to just four days a week of paid work. She figured it would give her more time and energy to focus on the kids, and she also hoped it would give her more time to rest because she had recently and unexpectedly become pregnant with twins.

What ended up happening, though, was that Patricia’s extended family saw her extra day off as an opening to ask for her help with car rides. Patricia was one of the only people in her extended family who had a reliable vehicle at the time, and she and her family were living in Indianapolis, which has been rated as the worst major city for public transit in the U.S. And so Patricia said yes, even when she explained that, she said, “your whole day that you had to yourself ends up being dedicated to running errands for someone else.” And she told me, she said yes because she had, you know, she knew her family had nowhere else to turn. The buck sort of stopped with her. And she also worried that she might need help herself someday.

And unfortunately, that someday came when Patricia and Rodney ended up divorcing just before the kids, the twins, were born in 2021. At that point, Patricia had to lean on those same people who leaned on her, and after her C-section, for example, she needed someone to drive her to doctor’s appointments, and she was grateful that she hadn’t pushed them away before.

And so Patricia’s story gets at this idea that, you know, our attempts to DIY society have, have decimated families, and particularly families that have been systematically marginalized in our society. And in that context, it’s often impossible for women not to get stuck filling in the gaps in our economy and in our social safety net, because we’ve really left them with nowhere to turn for support and nowhere to hide when others ask them to hold even more.

Now, within this system, it’s important to acknowledge that, that more privileged women have it easier because they can afford to offload some of their responsibility they’ve been handed by dumping it onto others who are more vulnerable than they are.

And in the book, I talk about a couple that I call Holly and Kathleen. They’re a white, same-sex married couple, and when their daughter Willa was born in 2019, they planned to split paid work and care work evenly. But the child-care crisis kept getting in the way. Without family nearby to help and with huge wait lists for care, their best option, child-care wise, was a part-time spot that wouldn’t be available until Willa was 9 months old.

And so to make it work in the meantime, Holly and Kathleen decided Holly would work for pay part time from home, while Kathleen worked for pay full time, in part because Holly’s job as a data analyst didn’t pay as much and was able to be done remotely, while Kathleen’s job in law enforcement, you know, had to be done outside the home and paid a whole lot more.

So that arrangement, though, got increasingly difficult as Willa got older, and Holly couldn’t wait for Willa to start child care. But then almost as soon as that spot opened, COVID closed the center, and they’re just right back where they were before.

And, you know, this caused deep frustration for Holly. And she actually went in and complained to her, tried to go in and complain to the center director. But what she learned in the process was that the center couldn’t afford to recruit and keep staff, as she learned, for example, that, you know, her child’s previous teacher didn’t have health care benefits and was still struggling to pay off medical debt that she had accrued, you know, years before the pandemic started.

And hearing those stories left Holly feeling guilty. She told me, “Kathleen and I just feel really guilty about being complicit in this thing where it’s like we have all these women of color watching our kids, and we’re not really taking good care of them.”

And, you know, that guilt of complicity weighed heavily on Holly, but she also recognized that, that she and Holly needed reliable, affordable care if they were going to be working full time and especially if they wanted to pay for IVF to have another kid. And so she talked about how, you know, “we have more than we need right now, but it could change at any moment without that social safety net. So you’re like, I guess I should just hoard it in a giant pile and sleep on top.”

And so as we see in Holly’s story, some women benefit from this kind of exploitation of women who are more vulnerable because that exploitation makes it possible for them to afford to outsource help with care. And yet, at the same time, and as we also see here, even relatively privileged women are drowning because our DIY model has left all but the wealthiest families with more responsibility than they can manage and because what’s left over disproportionately falls to women, even when men could do more to fill in the gaps.

And on that front, and I’ll quickly tell the story of a mom I’ll call Virginia, who’s a tenure-track professor at a research university who makes $75,000 a year, and her husband is a middle school math teacher who makes $45,000 a year. And despite being the primary breadwinner, Virginia is still the default parent for the kids. She’s also the default caregiver for her aging parents, even though her brother could be stepping up to do more, and it makes it tremendously difficult for Virginia to be able to feel as though she can concentrate enough to do her work, her research. She said, “I do actually have a brain. I love thinking, and I’d love to be able to do that again sometime.”

Um, at the same time, she also balked at the suggestion from her employer that she should just be taking more time for self-care. She said self-care is just a way that institutions have offloaded their responsibility of enacting humane work. Um, and she said that what she really needed was institutional support. She said, “I need the child tax credit back. I need a financial cushion. I need time and reliable care for my kids. I need consistency, I need institutions to step up and be humane.”

And essentially, I mean, Patricia, or Virginia’s lament here makes clear that we already know what the problem is, and we already know the solution. And so the solution is to build the kind of safety net that would actually protect us all.

But we haven’t built it, and I, and I argue in the book that we haven’t built it because, you know, billionaires and big corporations and their cronies, or who I talk about in the book as sort of the engineers and profiteers of our DIY society, have us right where they want us. And because they’ve promoted a series of myths that help to dissuade us, to help, to delude us into believing that we don’t need a social safety net, and to, to divide us by race and class and gender and politics and religion in ways that prevent us from coming together to demand the kind of social safety net that would better protect us all.

So I’ll leave things there for now, just to ensure that we have lots of time for other discussion. But I’m looking forward to the, to the questions and also to the, to the discussion with the whole group. So thank you.

Beth Jarosz: Thank you so much. Um, and I’m going to invite Tiffany now to speak a bit about her research.

Tiffany Green, University of Wisconsin–Madison: Thank you so much for having me here today. Congratulations, Jess, on your new book.

Um, I’m going to talk a little bit today about, um, some work that my team and I have been doing on a policy called birth cost recovery, or the birth tax, and just really thinking about its implications for caregiving. Um, a special thanks to the people that have funded this research, including the Wisconsin Partnership Program, uh, the Wisconsin Department of Children and Families, and the Centennial Scholars Program. So many people on my team to thank, um, including, uh, Klaira Lerma, who’s not pictured here, my research director; Frank Lewis, Obi Anaya, and Mikaela Miller, who are RAs as well; and also the many community partners that have been involved in this work.

So, what is birth cost recovery and what does it have to do with what we’re talking about today? Um, birth cost recovery is a policy primarily practiced in Wisconsin, where states draw upon a certain interpretation of federal Medicaid law that allows them to pursue, um, the Medicaid birthing costs, um, that, that people pursue. So if I have a baby and I’m on Medicaid, uh, the father, um, the non-custodial father would be asked to pay part of that cost.

And, how does this work? Um, basically, a person discovers that they are pregnant. Uh, they may or may not decide to enroll in prenatal Badger Care or Medicaid is what we call it here in the Badger State. Um, a person gives birth. Now, the state cannot withhold, uh, birthing coverage if the father is not declared. However, there is an automatic referral system in the state where if someone has a Medicaid for part of their birth, labor, and delivery costs, it automatically gets referred to child support.

Um, after that, the courts determined, um, one within the context of that child support order, if birth cost recovery or the birth tax should be incurred. Um, and that can be, that can be used to garnish a person’s wages, etc. And this is very much separate from child support, and it does not go towards the maintenance of the child. Um, if the birthing parent refuses to declare who the father is, the state can take away Badger Care or Medicaid after the 60-day period is over and they are otherwise eligible.

And so why does this matter? Well, for someone like me who studies structural inequality, this matters a lot. Because of structural racism, Black people and Indigenous people are far more likely to have their births covered by Medicaid, both in Wisconsin and the rest of the United States.

Um, I first learned about this policy from Rachel Azanleko, who was a former MPH student here who really focused on thinking about the impacts of birth cost recovery on outcomes. And she told me that, and as an economist I got excited, that there was a huge policy change in Wisconsin, which I’ll talk about in a minute.

But this is something that’s also coming up in the context of discussions with communities. This idea, particularly among Black communities, that this is a policy that magnifies financial instability for families. It penalizes birthing parents with health care coverage loss if they don’t declare the father. And it deepens many men’s struggles to financially support their children and strains family dynamics. So, you know, if there are strained family dynamics that that caregiving work almost certainly is going to go towards the birthing parents or mothers.

So in January 2020, Dane County stopped collecting new birth cost recovery funds. And we did some work to think about what the impacts might be on families. We found that there was an increase in child support that went to the birthing parent, and this was particularly true among Black families.

But one thing we found is that we weren’t hearing a lot about the Black families that were actually affected. And so in this, in this work through the Wisconsin Partnership Program, we decided to really try to document the experiences of the team and eventually create a quantitative survey where we could kind of assess how people’s experiences with birth cost recovery were affecting their mental and physical health.

Um, we started with birthing parents, and I’ll talk just a little bit about what we found. Um, and we also will be interviewing fathers as well, or non-birthing parents. Um, how do these birthing parents think that birth cost recovery has affected their lives? It’s dads not having money for necessities or extras. Negative impacts on bonding and, and these inequitable effects, particularly among Black Wisconsinites.

And so what this boils down to, again, is that it makes sure it helps to ensure that fathers are not able to fully participate in their children’s lives because of this extra cost that’s incurred. Um, here’s one quote from some of the qualitative interviewing that we’ve been doing. We interviewed, uh, I think 24, uh, birthing parents at this point.

“Yeah. I mean, that could be challenging for the 5-year-old.” So, so they’re talking specifically about birth cost recovery.

“I can’t give you extra money for school clothing because I got to help pay the birth expenses. Hey, I don’t have—let’s say I was to run into a gym where I needed $25 for gas. The funds is so tight that they’re not even leaving room for the fathers to do anything extra or curriculum activities, because they’re getting this money, taking out of their checks every two weeks or every week for child support.”

A second quote from a respondent: “If men didn’t have this birthing fee right off top, that would make it a better relationship bonding for the mother, the father, the child. Men would be able to do more, provide more, and it’d just be a healthy family overall.” So again, these quotes really embody the fact that this, this particular policy, far from being sort of these individual-level choices, has the capacity to frame what can be offered, fathers are able to offer children, and the stability of family units.

Um, just so you know, there have been some more recent policy changes. I feel like it’s a moving target for us. Um, Milwaukee County has stopped taking fathers to court for birth cost recovery. And Dane County also is, is working on forgiving back pay, as is Milwaukee. So there’s been a lot of change just since we started studying this policy. And we’re working to try to understand how this shapes family dynamics and caregiving within families.

Um, now we are focused on interviewing Black fathers now to understand their perceptions of the policy and understanding how this affects how they see fatherhood and their ability to support, uh, child, child experiences in their growth, and really trying to understand the short- and learn long-term effects of these policy changes on all Wisconsinites, but specifically Black Wisconsinites.

And I’ll end there and kick it over to the next person. Thank you so much.

Beth Jarosz: Thank you. And Karen, I will invite you to share about your research next.

Karen Benjamin Guzzo, University of North Carolina at Chapel Hill:  Great, great. Thank you so much, and I’m really pleased to be here. And thank you to PRB for putting this together. Uh, and thank you Jess for writing this book.

And so I’m a demographer, and so I study population-level changes in behavior. And my particular area of research, uh, is childbearing, uh, looking at birth rates and trends over time, differences across different groups, um, the factors that predict whether people have children.

And so what’s important to me and some of my takeaways from this book or that related it back to a larger issue some of you may have heard of, which is that the U.S. is at record low fertility rates. Uh, this has caused considerable alarm and for all sorts of reasons, and maybe we can get into this later. Um, but different groups are alarmed for different reasons.

Uh, and so the question has become, geez, why aren’t women having births? And this is, I get this question a lot from journalists. And really, it’s tightly tied to how we think about women and birthing people. And you know, what we expect from them, how we judge them, and what we do or do not owe them and provide them as a society. And so when we’re talking about birth rates declining, um, to me, this is very much a story of damned if you do, damned if you don’t.

So for years the U.S. has had higher fertility rates than other countries, many of its pure nations. We, so we kind of aim for what’s called replacement level, which is about two births per woman. This allows women basically to replace themselves and their partners, and, uh, absent immigration, this keeps the population stable. And so with the U.S. was above this rate for, for quite a while when many of its pure nations were not.

And, as such, the U.S. was kind of able to ignore the social safety net, the kind of things Jessica talks about in her book: things like affordable care, affordable and accessible child care, lack of paid parental and family leave, um, having a functional health care system that everyone could access regardless of income or employment status.

And so low fertility, low birth rates, was really not on our national radar. Um, any woman can probably tell you it’s certainly on the individual people’s radar. So lots of women were, “So when are we going to start having kids? When are you going to start having kids?” Um, but this wasn’t a national conversation because what we are, the conversation we’re actually having as a country was who shouldn’t be having children.

And so the U.S. has generally had very high teen birth rates and high unintended pregnancy rates relative to our peer nations. Uh, and as it turns out, those teen birth rates and unintended pregnancy rates were actually propping up our overall fertility rate.

And so, since the 1990s, under the Clinton administration, um, we had the emergence of, um, different efforts to reduce teen and unintended pregnancy. Uh, so in 1996, we saw the emergence of the National Campaign to Prevent Teen Pregnancy, um, come out. And then later expanded to include, um, teenage and unintended or unplanned pregnancy. Uh, it since changed its name again.

Um, and so in the 1990s, teen pregnancy rates were at, um, sort of record highs, but only in terms of recent memory. Because if you go back to the 1950s, during the baby boom, teenage birth rates were much, much higher. But they were the right kind of birth. They were births to people who were married, and we weren’t worried about those.

So what happened in the 80s and 90s is that birth rates were increasingly teen birth rates were to low-income women who were unmarried, women from racially minoritized populations. And these were the wrong kinds of births. And so we were very worried about those.

Um, and so, um, we had all sorts of campaign ads to reduce teen and unintended childbearing. So you might remember from just a decade ago, New York City ran these fairly horrific ads, um, targeting teen moms and trying to shame them into not having, um, children.

Um, and then even at the federal government level, we have official policies. Uh, every 10 years, the federal government publishes something called the Healthy People objectives or Healthy People initiatives. And, and these are kind of health, public health goals they’d like to reach over the next decade. And for a long time, those have included, uh, reducing teen and unintended pregnancy rates.

And so I say all this to say, over the past 10 years, basically since the Great Recession, it actually happened. We’ve seen this long-term decline in teen pregnancy rates, but now we’re also seeing a pretty sizable decline in births to unintended births that would be characterized by people themselves as happening maybe later in earlier than they would have wanted. So now that people aren’t having those births, this is essentially good news.

So when reporters ask me, you know, “What’s happening with birth rates? Why aren’t people having kids?” I’m like, this is a success story. This is a story in which young people, those are, those are the people who typically, if they had a birth, would consider it sort of earlier than they would have wanted. This is a good news story that people are able to better control their reproductive lives so that they can have children when they want them, under the context in which they want them, and to have as many children as they feel personally able to have.

Um, and so this is a good news story, but part of this good news story, the background to this is that we have been preaching for years that it is irresponsible for people, but really for women, for young women, to have a child when you’re not ready: you don’t have a good job, you haven’t finished school, you don’t have a good partnership, you know, you can’t afford to live on your own, you live in an unsafe neighborhood.

So we’ve been preaching this for years that you shouldn’t have a child if it’s, if you’re not in the right circumstances. And so the decline in unintended fertility in some way it’s very good. And the decline in birth rate is because of sort of declining teen and unintended birth rates. But we need to think about the other side of the story.

Um, since the Great Recession, our society, and that of other societies, I’ll be honest too, who also have more of a social safety net, um, a lot of these societies are not providing people, young people, a sense of security and optimism for the future. I mean, all for all intents and purposes, having a child is a future-oriented decision. And so people need to look to the future and think, “Okay, I can do this, and I’m going to have a good life, and I can provide my children with things.”

And so to me, it’s, it’s baffling that people are baffled that we’re not having, young people aren’t having kids today, that they are waiting. And because they’re holding up their end of the bargain, the bargain that we’ve been preaching for, you know, 15, 20, 30, 40 years really: don’t have kids, don’t have kids if you do not have, you know, essentially all your proverbial ducks in a row.

But the other half of the bargain is that society needs to create a set of conditions in which you can reasonably predict for the future that you’ll have enough money, you’ll have a good job, you can afford health care, you can afford to find a safe place to live. You can have a good partnership. And so people aren’t having kids because those things don’t look like they’re happening for them in the future. Um, and, of course, without an adequate social safety net otherwise, it’s just simply too risky to have children in some ways.

So most of my research really shows that it’s not that people are saying, “I don’t want kids.” They’re saying “I want kids, but not now. I want kids if—.” And they really are thinking quite rationally about what they want in the future, what they think childbearing for them should look like.

Um, and so if you’re a woman, childbearing is incredibly risky. So it starts in pregnancy. We monitor what you eat, what you drink, how little or how much weight you gain. If you have a substance use disorder, uh, and you’re pregnant, you could go to jail or risk losing your child rather than getting help. Um, if you’re sick during pregnancy, you know, God bless you. Um, because we don’t know what meds might work for you because we actually don’t study, um, women, pregnant women have typically been excluded from medical trials.

If you have a condition that threatens your pregnancy, um, or threatens your life and you live in certain states, uh, again, you might literally be risking death because health care professionals cannot or don’t feel as if they’re allowed to treat you. Um, even before some of these recent changes we’ve seen in abortion law, uh, your chance of dying during pregnancy, during childbirth, or thereafter was much higher in the United States than elsewhere.

And then, of course, if you make it all through that, and you have a child, and you’re on your own to figure out if you can take time off. We do not have paid family leave in the United States. So people go back to work much sooner than they would like. Um, but if you’d like to stay home and recover from childbirth, you know, bond with your baby, you’re going to have to figure out how to do that on your own. You’re going to have to fund that on your own.

If you do go back to work, um, you’re going to have to find someone to care for your child. Um, and we have such a huge problem with child care affordability and accessibility, and this has really been accelerated and magnified during the, um, the pandemic and post-pandemic years, uh, where we’ve seen a real decline in child-care slots.

So you have to go back and try to figure out who’s going to watch your kid for you, and can you afford it? Um, if you do have a financial setback of some sort, you know, you’ll have to navigate our patchwork safety net programs. Um, and those, there’s a lot of sort of administrative burden there, and it often seems like they’re designed to turn you down and humiliate you in the process of getting them.

Um, even for advantaged women, you have these sort of do-it-all norms, uh, and you’re going to be struggling to find child care during summers if your kids are school age or before and after school. Um, you are worried about social mobility, so parents feel like they have to do everything right and get their kids into all the right programs. Um, if you can afford not to work as a mom and you choose to work, you’ll be judged for that, and you’ll face this constant feeling of neither being good enough at work or at home. And these are all just really gendered things.

And so when, when people ask me, “Why aren’t people having kids?” I’m like, well, they’re making really rational choices about what’s available to them. What’s the safety net look like? What does my own future look like? Does it look safe? Secure? And mostly they’re saying no, it doesn’t. It doesn’t look like that right now. And so people are waiting longer and longer to have kids. And sometimes that might mean they end up with fewer kids or not having kids at all.

And so this is not a story of individual women saying, “Oh, I just don’t like kids.” I mean, of course, some people probably say that, but really it’s a story about young people as a whole looking around and saying, “There’s— the conditions in which you’ve told me I’m supposed to have kids don’t exist for me, and I’m not sure they will.” And so this is very much a story about what is our social safety net look like for people and families, but particularly for women who are making these decisions.

So I think I’ll stop there, so we have chances for someone else to weigh in.

Beth Jarosz: Thank you so much, Karen. And last but certainly not least, um, we want to, we’re talking about all of these challenges, the social safety net and sort of policy changes that could be helpful. So we’re going to wrap up with a little bit of discussion about, uh, how policy can change. So Jocelyn, turn it over to you.

Jocelyn Foye, Womxn Project: Thanks. Hi, everyone. How do you do? My name is Jocelyn Foye, she/her.

I am located in, um, Providence, Rhode Island, um, which I relocated from Southern California. But to give any of you a sense who aren’t from these parts, um, Rhode Island is the smallest state in the nation with only 1.1 million people living within our borders at this time. Our census says that we are a 77% white-identifying population, which if anyone studies census work, they’d understand that that’s not the right number for minority spaces. But, um, it’s an important one to name. And then also, we’re the third most Catholic state in the nation, which means we have an incredibly powerful, um, bully pulpit for the, for the bishops here.

And so when I moved here from Southern California, um, what I found really quickly was how restrictive the policy was for a state that people often say is a blue state when you see it on the map. And when we’re looking at presidential elections, it always goes blue. Well, we’re very purple, and it’s important to name that as I talk about this work, because, um, my organization came out of a place of recognizing that with Trump coming in as his first presidency, we had concerns.

A number of us who were doing policy, and I come from a background of being an artist, a spectacle-based artist and a design professor, and we wondered if we could put together policy strategies and inclusive installations that were spectacle based and activating of community to be welcomed into the process of how to do art and activism with us. So these are some images of ways we did the work. Um, and it’s, there’s a lot of pictures on our website. So we, we welcome you to take a look at it.

But the reason I think I was invited here was because the Womxn Project. Um, and I want to say to woman with an X when we originally named ourselves, was to be an inclusive organization to include all folks, of all folks who wanted to get active with us, to join it. Language has recently changed, and so we constantly are in a mutative form of how do we rebrand to be in alignment with inclusive, inclusive work?

Um, so, um, we came on the scene after 24 years of essentially what was the Roe bill in Rhode Island. It was, um, fought for, for 24 years and had no success. And so with our style of activism, what we did is we created this community quilt. And we wondered if by going into different areas across the state, and we had conversations with people about, were they aware of their rights? Were they aware that after, um, if Roe should be overturned—and mind you, we started this in 2017—um, that based on the constitution of our state, we would see that, um, providers would be tried as murderers.

And I went to an event in Washington, D.C., where I sat with some women from Alabama, and they said, you know, “Rhode Island and Alabama aren’t very different, are they?” And I was like, oh, tell me more like, what are you thinking? And what they said was, is that we both are run by the mob, which is true, and we both are, um, are going to have abortion providers tried as murderers based on our states’ constitutions.

So our group was like, okay, how do we bring more people to the table? Let’s look at the way marriage equality was done nationally. And we started doing one-on-one conversations, house parties. We started going into spaces where women were collecting, book clubs, sewing groups, you name it, and we started asking people if they wanted to make a quilt square with us. And the quilt square became essentially their own signature of a petition.

And as a lot of us may know, the history of quilts says a lot about, um, memor—  like memorandums or histories of passage of people’s lives. But it also is a, is a, um, history or a path of understanding of where to go.

So what we did is we ended up building this giant quilt, and we had master quilters across the state helping us build these sections that we carabinered onto one another, and we moved around and we would display in our state house. And for anyone who’s a visual interests learner, installation art, this thing kept getting bigger and bigger, and we had security guards really angry that we had this mass thing.

But what happened was a ton of people across the state felt really this was their thing. They all were working on it. It was a very collaborative effort. And what really happened was, is we got to have 2,500 small conversations with people who made those squares with us that were part of those quilts, and that had the networking effect that women do do so well, or small communities that are unique and tight with one another.

So it became an intersectional project in a lot of different ways because of where we were invited. And we intentionally designed it so that different spaces made it their own. People built different methods of this, this style of work together.

And we were able, after three years, to pass the bill, which was turned into, they named it the Reproductive Privacy Act. Um, and we did it because we built community momentum, and we got people to a point where they not only understood what was at risk through conversations and networking, but also they learned about the education of how a bill becomes a law. And they learned that they wanted to get involved and they wanted to see this bill through.

People felt a level of ownership. And so when I talk about us as an organization, the part that’s hard for people to wrap their heads around it is, is that we stemmed from grassroots organizing. We still are. Um, but we also shift policy. And we do that by way of, of basically the people power.

And often when you talk to organizational leaders who say, well, what is your piece? What makes you different here? Um, unfortunately or fortunately, it is the fact that I’ll walk into a room with legislators or the governor, often not comfortably, they’ll see me and they’ll be like, oh no, she’s here, because I bring sort of this level of question of what is the action or the behavior that I’m representing, but also how many people are, are coming with me.

And so what it’s done is, is in this movement, this intersectional movement of  “women’s work” or organizational, um, like, uh, patriarchally like suppressed spaces. What we’re doing is, is we’ve pivoted from not just working in the abortion space, but we’ve also been invited and have board members who are identifying in the space of the LGBTQIA space.

So after two years of passing the Reproductive Privacy Act through, excuse me, because of COVID, we passed essentially the Hyde Amendment in Rhode Island to be overturned. And so that meant that Medicaid recipients and state workers then had that included in their insurance policy, which, when we think about it, if you pull back on a lens, um, a lot of people will say abortion is been taken over by white women, second-generation feminists. And I can’t argue against that. But we looked for ways to make it everyone’s work. And with the second bill, it was an equity piece. It was like every, if one person has access to this, then everyone should.

And so now we’ve gone into the same sort of work in a similar way. But we’re not talking about abortion because it’s never really been about abortion. Roe was not about abortion being overturned. It was about taking away our rights. And so, in a medical way, and so we’re now looking at we just passed a bill this year, which is incredible because there’s really no good news in this horizon, but a provider shield bill.

And so we now have we just today, I just came from the signing of our governor where providers who are giving, doing abortions or who are doing gender-affirming care will be protected from any out-of-state attacks that they may receive from states so that those providers can be taken care of, as can the patients, which is not something we always get to talk about. So our work is this like modeling of policy mixed with community action.

And I think that, um, there’s a lot to say further, but I’ll stop. Um, we are, I will say this too, in, in just full disclosure, we’re an organization that started as a C4, not-for-profit, which is unusual. It’s not a C3. A C3 is tax exempt, so it’s not allowed to talk about policy as a lobbying thing. Well, we started as the opposite, which is a lot harder in America. People don’t like to fund this type of work.

But what it allowed us to do was it was tool, we had tools in our toolboxes that were different, so we were able to drive billboard trucks around our state with faces of General Assembly members on it that said, this person doesn’t believe in the right to abortion in your district. Here’s their phone number. Call and ask them why. Because it became an accountability process.

And, um, and we built massive coalitions around this work because people saw the value in it and for their communities as well. And so we’re growing while trying to figure out how to, you know, keep pushing the envelope. So I’ll stop there.

Beth Jarosz: I feel like I, we could continue this conversation for two more hours. Um, but we’ve got, we’ve got about 20 minutes now for questions, and we’ve had a lot of really fantastic questions, um, come in through the chat. So, um, I think I, I had prepared some questions, but I think the one theme that sort of has come across several of the questions that have come in is, what would an improved social safety net look like? And I’m thinking each one of you probably has a perspective on that. And we’ll go kind of in the same order we did. So Jess, Tiffany, Karen, and Jocelyn for that one.

Jessica Calarco: So I mean, I think that’s a great question. And I think the kind of social safety net that we need, in my view, is one that helps to essentially take care out of the for-profit market. That’s one piece of it, in the sense that so much of the unpaid, underpaid labor that women end up doing, women hold almost 70% of the lowest wage jobs in our economy. And often those are jobs where women, especially women of color, especially women from more marginalized groups in our society, are pushed into doing these kinds of low-wage jobs because someone, they’re not, they don’t work within our profit-driven model.

And so ensuring that that taking that work out of the market, whether that’s child care, home health care, the, you know, health care in general, that removing that from the profit pressures can help to then pave the way for the second step, which is about ensuring that the care, the care work is equitable and funded to the level where it can be both equitable and sustainable, essentially taking care of the people who care. And that includes both paid work and unpaid care work in the sense of things like unpaid, or things like paid family leave, things like paid vacation time, things like limits on paid work hours like they have in places like France, to ensure that everyone has the time and energy to contribute to this shared project of care.

So those are sort of, you know, two key components, um, kind of ways to think about the social safety net as opposed to, you know, specific programs. Um, so it’s about sort of, you know, giving people a backstop and also making sure that people have the time and energy to, uh, you know, take care of each other and take care of themselves because we can’t outsource everything, even with a sturdy social safety net.

Beth Jarosz: Tiffany, do you want to add to that? What’s, what would the safety net look for you?

Tiffany Green: I don’t have much else to add. I think high-quality child care is, is a key thing where, where child-care workers are paid well. We know that child-care workers were at the front lines during the ongoing COVID-19 pandemic, and many quit, um, during, during that time. So making sure we have high-quality child care where the people taking care of our kids can actually afford, um, that high-quality child care is really key. Having, um, paid parental leave is really important.

But I would say even within the context of our institutions, many of us are at universities—I’m tenured now, so I will say this—um, a lot of the care work is put on, um, you know, faculty assigned female at birth. Let’s, let’s be really clear. So we have a pervasive, um, um, the thing where we put care work upon women and other people assigned female at birth within all of our institutions. So I think we need a full-sale overhaul, uh, a wholesale overhaul of what that looks like.

And the other thing I would say, I always think about the non-sexy things, and so one of those things is our tax system. I’m not an expert in that. But I’ve, I’ve been very convinced by my colleagues who are experts in the tax system in thinking about how we can use that to, to reduce poverty, because, again, many of the most impoverished households are headed by women. So things like the Child Tax Credit were very effective at, uh, at improving things, making sure we have, um, an equitable system so that people, people that, households that are headed by women, um, will not be as poor, I think is really important, other than, you know, burning down the patriarchy.

Beth Jarosz: Yeah. How about you, Karen? Anything to add?

Karen Benjamin Guzzo: Yeah, so I want to comment on something that I think I showed up in the Q&A a bit, which is that people sometimes say, oh, well, other countries have some of the social safety net things you’re talking about. You know, some of the Scandinavian countries have great leave or great child care, and their birth rates are also falling, or what’s happening, um, in East Asia, where the birth rates are extremely low and they have some generous policies.

Part of the problem, though, is that you need all the things, but you also need social change. Um, and it’s not enough to, especially for some of the East Asian societies, to say they have a generous maternity leave policy, um, if women are actually still expected to come home and do all the work, uh, and their husbands are not doing anything, or you still have a culture in where, um, working all the hours is how you actually get ahead in your job. So it’s not enough to have just any one of these things.

Um, but I would also say even if birth rates don’t go up, they are the right thing to do to have, you know, a strong maternity and parental leave policy, to have adequate child care. Um, it is, I think it’s important to have these things because it does improve the well-being of, of our families. And I think that is really where we all want to end up, where people feel like they can live the kind of meaningful lives without this level of stress.

But going back to the culture thing, and one of the things I find is a sticking point sometimes in conversations I’ve had in research I’ve done, which is that women feel as if they’re doing everything and their husbands are like, “But I’m doing so much more than my dad. I’m doing so much more than the earlier generations did.” And the women that they’re partnered with are saying, “But you’re not doing as much as me.” And so people are sort of talking across each other within relationships, but we don’t recognize this sort of care work and value this.

So there’s been this movement. Um, I think Richard Reeves is sort of the kind of most proponent, biggest proponent of this is, how do we get men, how do we help men out? But one argument he’s making is we’ve got to get men to understand that care work is important and meaningful. Um, and help them make, you know, firm relationships with their children, with their friends so that they can engage in this care work that makes everybody better.

And so we need a social safety net, but we need the cultural change that supports using a social safety net and that a social safety net is an investment and not some sort of extra expense that we’re doing because women aren’t doing their jobs.

Beth Jarosz: Thank you. And I actually think that answers one of the other questions that have come in. So the person who asked the question about how are men being called in, if that’s, if you want to continue on, repost that question in the chat. And then Jocelyn, do you have anything you want to add about the safety net?

Jocelyn Foye: The only, yeah, I mean from my lens as it would make sense then is, is that from a social safety net too, we need to be supporting not-for-profit organizations that are doing a lot of this work. Um, it’s the second largest industry in the United States, which is not-for-profit work, but how, um, those organizations struggle and actually exist within spaces where they’re in competition with each other is really difficult.

Um, and so I would just say for those with the means, it’s not always about money. It’s also sometimes, which we often talk a lot about, what it’s about, um, finding your superpower and what can you contribute to the work. Um, often for people who have the means, yes, money is a really helpful tool. But for people who time is of the essence, you have children, you, there are organizations that invite you to do some of the work with, um, them with your children, and more and more not-for-profits are making that a part of the process. Um, but also organizations are looking for people who can do work in ways that are very creative.

And so I’m just putting out there I think that, again, I come back to I’m not thinking of the folks who were trying to just get by, but I’m thinking of the spaces that are places where people can add a little something. Um, I think it’s important to name, and I, I don’t have a stat that’s as, as recent as I’d like, but Ms. magazine has been putting out research about what kind of not-for-profit funding exists in the United States. And in 2020, it was only 1.6% of not-for-profits were being funded that supported women and girls, specific not-for-profits. And so when we look at how support is existing out there, I think we could all do better. Um, and I think we make assumptions about that.

But I go back to I’m a designer. I always offer my resources as a designer. I can’t offer my resources as a, as someone who makes money. And so I try to fit it in when my kids go to bed before I go to bed, if I can. And I think that that’s a way to think about certain models. Again, a privileged model nonetheless. But if you had the time, what could you offer?

Beth Jarosz: Thank you. Um, and taking it in a slightly different direction and sort of a question that I had prepared, um, but then Tiffany sort of spoke to in the chat just now is that, you know, the underpinning this assumption is the idea that, um, that people should be having more children. Um, and is that really even a, is that really even the right assumption?

I know, um, Karen and I have been chatting about this a little bit too, that, and Karen, maybe you want to kick that off, that, that just that underlying assumption of is that even the right question, like is, is the question how to, how do we increase birth rates? Or is the question about making sure we have a safety net because that’s the right thing whether the birth rates get there or not? But also how do we push back against this idea that like people having kids is the way to solve our economic problems?

Karen Benjamin Guzzo: Sure, sure. So, um, I’ll just sort of lay my, my, my position clear, which is I’m not worried about our fertility rates. Uh, I worry about fertility in the sense of we have people who say they’d like to have kids and feel like they can’t have the kids that they’d like to have under the conditions they would like to have them. That is a societal failure to me that we have people who want to have children and feel like they can’t. That is a problem we need to fix. Um, but birth rates in themselves don’t concern me.

Uh, you know, if we’re worried about, you know, we talk about Social Security or, um, the labor force or something like that, or even worse, you know, nation-states. I can tell you how little I care about nation-states. Um, but, you know, things like Social Security, we have other means. We could, we could, we have other policy-level levers, um, but expecting people to say, oh, I should have children so that, um, future generations can, so that my kids 20 years from now can pay into Social Security to help fund retirees at that point is sort of nonsensical to me when we have levers like, we could raise the Social Security cap, um, you know, we can change our policies in terms of immigration. We, uh, we can, there are things we can do. And as automation changes and jobs change, do we need as many workers?

Um, and so we need to we need a wholesale sort of reimagining. And do I think it’s going to happen? I don’t know about that, but, um, but this idea that birth rates are going to be the thing that save us as a future just does not resonate with me, because it’s not just about birth rates. Let’s be really honest. It’s about the right people having births. Um, it’s not just we don’t want more immigrant births, so we don’t want births from poor people. We want a very specific group of people to have births. Um, and ideally, they should stay at home with their kids and get out of the labor force.

And I mean, it’s, there’s a whole level of things that, you know, probably aren’t worth getting into right now.

Beth Jarosz: And, Tiffany, since you were the one who put that comment in the chat, is there anything you want to add to how we think about the sort of social structures about who’s the right person, or, you know, that it should be going up?

Tiffany Green: Yeah, I mean, I think it’s very much grounded in the eugenics of, of, of earlier and I guess present times that the people that need to be having births are white cisgender women and other people should not be giving birth. Um, so I teach a lot about that in my classes, and I think it’s really important to sort of question our underpinning ideas of why we, we think people should be giving birth.

Like Karen, I don’t care about birth rates. I care about people that, you know, from a reproductive justice standpoint, the right to get pregnant and stay pregnant is really critical. And we know that social structures, uh, are very much against, for example, Black people, uh, getting pregnant, whereas during enslavement, um, the idea was for Black women to get pregnant and to, to perpetuate the institution of slavery. So there is no neutral way of thinking about birth rates, uh, in, in that context.

So in total agreement with Karen and just adding that extra historical context.

Beth Jarosz: Thank you. Um, and then there are, there are so many good questions. Um, and I have to pick, we probably have time for one, maybe two more. So I am going to go with one, um, that, uh, Jess, throughout the book, there’s this theme that good choices aren’t enough to save people, um, that, that there is this sort of social belief that, oh, well, you know, if that person had just done x differently, then y wouldn’t have happened. And you lay out a really clear case that that is not really how things work. Could you expand on that just a little bit?

Jessica Calarco: Sure. I mean, this is basically the idea that correlation is not causation in the sense that certainly there are, um, choices that people can make in our society or some people can make in our society, things like getting married, you know, delaying childbirth, uh, going to college, finishing a college degree. You know, these kinds of choices correlate with better outcomes. You know, more economic stability, lower risks of poverty, better health outcomes.

But that doesn’t necessarily mean that it’s those choices themselves that lead to those better outcomes. And it ignores the role of privilege in facilitating people making those kinds of choices. As Karen was talking about before, we’ve set people up to understand that you should really only be bringing a child into the world, or you won’t be, the only real way to not be judged for doing so is if you’re doing so in the right kind of context.

And the same is very much true for marriage. The same is very much true, I mean, for college. I talk in the book about how just going to college, especially for women given gender pay gaps and given the way that we, you know, differentially value gendered work, it doesn’t necessarily pay off in those kinds of ways.

And so we have to be very careful about that kind of messaging that just tells people to make good choices. And that’s really the whole, um, the basis of this DIY myth that I talk about.

Beth Jarosz: Does anyone else want to speak to that question?

Karen Benjamin Guzzo: I would just chime in to say some of the stuff that was in the book that I’ve seen in other places, which is you make the right choices and something catastrophic goes wrong and there’s no safety net for you. You have a sudden illness, uh, your spouse dies. All your good choices don’t mean anything, you know, because you’re on your own again, because there’s no safety net.

So, again, making these right choices, it’s no guarantee that things will work out. And so the amount of luck people have, um, in their lives is sort of underplayed because the people who’ve done well don’t like to think of themselves as being lucky or fortunate, but they are just one sort of bad mistake or bad, you know, car accident away from something catastrophic happening. But we don’t think about it that way. And we tend to say, oh, you must you must have made bad choices to have ended up this way.

Beth Jarosz: Um, I don’t think we have time to address this one, but I just want to note that a couple of people have mentioned in the Q&A that there’s also, we’ve talked a lot about child care, but similar patterns play out with elder care and with other family caregiving responsibilities. So I think it’s sort of just a resounding acknowledgment that that is true, and that when we talk about these roles that society plays on women, we’re talking about all of those, um, even if we’re focused on the child care piece today.

So the last question I want to leave with, um, is we’ve talked about a lot of what’s wrong. Um, we’ve talked about a lot of the challenges and the holes in the safety net. I want to just ask, is there anything that makes you optimistic about the future? And we’ll, we’ll go in reverse order this time. So we’ll do Jocelyn and wrap up. Jocelyn, what makes you optimistic?

Jocelyn Foye: Sure. Um. So, uh, the Womxn Project lately has been doing a lot of organizing at school board and town council levels, because that is a space where a majority of women are taking in, taking on the roles of those leadership positions, at least in school committees. But typically they get kicked. They decide not to continue in government because, frankly, it beats them down.

Um, what I will tell you is, is, well, we’re fighting against a lot of the hate group organizing ourselves in terms of how it’s impacting bodily autonomy and freedoms. Um, I will tell you that when people in their communities find out, so in Rhode Island, people don’t think it’s as present here. And so I would say that representation of the different states that is here in this panel, that’s a very different type of thing. But for this particular state, when people find out that there is things, there are certain things happening in certain areas close to them, people aren’t shying away from it as much as we expected. They’re actually asking, how can I help?

And so my talks have been very much around maybe it’s not direct because that puts you in direct conflict with people or vulnerable with people who are in your community directly, maybe at the supermarket. But there are different ways to engage. And I’m seeing a lot of innovative thinking and a lot of, of hopeful thinking, and that gives me hope that whatever happens on the other side of this, um, presidential election, that the network we’re building within our state, within these different communities to defend, um, their school boards and town councils that we’ll have a network of people that are working together to do something as simple as, how do you support people if Medicaid goes away?

And so there are different methods of behaviors that people are analyzing and turning to for their community health centers to do that. So again, I think hope is coming in like, who are the heroes? And it’s everyday heroes that we’re seeing, and it is moms, and it’s birthing people who are just like, you know, not, not on my watch. And so I think that that’s an important place to be and to hold on to is hope.

Beth Jarosz: All right. How about you, Karen? What gives you hope?

01:00:18
Karen Benjamin Guzzo: Young people. Um, they are very, they, they’re very clear that they, like, they think about parenthood a lot and what we owe kids. And they’re not willing to, to take it for granted that things will work out okay. They’re like, well, what do I need to do? And so they’re very conscious about, about having kids and about what their futures look like and how what they need to do to make it to, to, to make a better future for themselves and the, and the kids they’d like to have.

And so I’m always impressed by the young people I talk to. And I say, I sound so old when I say that. But, you know, my students in college, like they are really deliberate about thinking about their futures and what they want, and they want to make sure that they have those. So, so it’s not people aren’t taking childbearing too seriously, it’s that they’re taking it very seriously and they’re not willing to do things under, you know, less unsuitable conditions. And I think they’re going to work for those.

Beth Jarosz: Thank you. How about you, Tiffany? What, what gives you hope?

Tiffany Green: You know, um, so prison abolitionist Mariame Kaba always talks about hope being a discipline. And I think that is what I try to do.

You know, I work in reproductive health and equity and justice, and there’s a lot to be depressed about. But I think for me, it’s staying in the work and seeing that no matter how, how, you know, we despair, there have been people that have been working in reproductive justice for a long time. There have been people that have been working to, to expand access to child care for a long time. There have been people that have been fighting for all of the things that we’re talking about, and that progress is never, was never going to be linear.

So I think really for me, it’s staying in the work and working to uplift those people who are doing that work that keeps me hopeful.

Beth Jarosz: Thank you. And last but certainly not least, Jess, what gives you hope?

Jessica Calarco: Yeah, I mean, I think one thing that gives me hope, in addition to what’s already been mentioned, is that we got really close with Build Back Better, and we actually learned some really important lessons from the policies that we put in place during the pandemic: things like the Child Tax Credit, things like universal free lunch, you know, from the Medicaid expansion. We learned from these policies that we can do large-scale social programs in the U.S. despite our size, despite our political variations and all of the other challenges that we’re up against.

And the other thing that gives me hope is that, at least for now, we still live in a democracy, which means that we have the chance to, that we don’t actually need to persuade everyone, that we, if we can convince enough people to reject the kinds of myths that are designed to delude and divide us, then we actually have a shot at electing the kinds of policymakers who have the potential, at least, to fight for a stronger social safety net.

And so I think it’s those are the kinds of pieces that give me hope that we got very close and that this is possible if we just have enough people who are willing to reject some of these ideas that help us stay stuck in the status quo. Thank you.

Beth Jarosz: And thank you all so much. This has been—I don’t know if you can tell from the reactions that are coming in through the chat here with the hearts and the clapping—this has been an absolutely fantastic conversation. And thank you all for your time today. I truly, truly appreciate it, and we will post the recording soon.

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Transcript

Mark Mather, PRB: Okay, well, I think we should go ahead and get started. Hi, everyone. Thanks for joining today’s webinar on ACS resources, shortcuts, and tools. I’m Mark Mather, and for those who don’t know me, I help manage the ACS Online Community website and other activities in partnership with the U.S. Census Bureau.

I am very excited to introduce the three speakers in today’s webinar. Lillian Kilduff is a Research Analyst at PRB and will provide a brief overview of the ACS Data Users Group and Online Community. Following Lillian, we’ll have Mary McKay, who’s a survey statistician in the American Community Survey Office. Mary is going to show you how to access the ACS through the Census Bureau’s API and microdata extraction tool, also known as the MDAT. And then we have Kevin Kane, who’s a program manager with the Southern California Association of Governments. Kevin is going to describe how he uses R and the tidycensus package to access and output ACS data.

A few housekeeping notes. We’re going to save the Q&A until the end. We do have a large number of participants. We encourage you to use the raise hand feature in Zoom, and then we’ll try to unmute you to ask your question, but you can also feel free to use the question box at the bottom of your panel there, and you can type in your questions at any time during the webinar.

Closed captioning is also available as an option at the bottom of your screen. And in addition to our three panelists, we also have several other Census Bureau staff members on standby to answer your questions today. And finally, this webinar is being recorded, and we will send you a link to the recording after the event. And with that, I’m going to turn it over to Lillian.

Lillian Kilduff, PRB: Thanks, Mark. I’m going to be talking about the ACS Online Community today and also showing the new upgrades. If you haven’t already seen to the look and feel of the website, I’m going to go ahead and share my screen real quick. Right here. Okay. Sorry about that. Okay. Um, so I’m going to provide the brief introduction to the ACS Online Community.

So here’s an overview of the presentation today. First we’re going to do a quick recap of the American Community Survey itself. Then we’re going to talk about the ACS Data Users Group and Online Community. Then we can go over the tabs of the ACS Online Community, and that includes the discussion forum, the ACS resources, webinars, and conferences tabs.

After that, we’re going to talk about the ACS Online Community itself. So behind the scenes, how many members do we have, threads and replies, page views, response rates, and then also talk about the discussion forum topics that often get viewed. We’ll go over the site upgrade if you haven’t already seen the changes and talk about how to join the ACS Online Community.

So just to review, if you’re new to the American Community Survey, people use the American Community Survey to get, uh, data on the demographic characteristics. So that would include social characteristics, economic, housing, and demographic. And you can see some of the examples in those parentheses there. The data products include one-year estimates, one-year supplemental estimates, five-year estimates, and you can access those through many tools including tables, the summary file, and PUMS.

Here is a quick hierarchy of the geographies available. So we have from the nation down to block groups.

When it comes to the ACS Online Community, this is a partnership between us at PRB and the American Community Survey Office at the Census Bureau. The ACS Online Community’s purpose is so that ACS data users can share tips and tricks, questions, materials, and then also we post announcements about things like today, the webinar. Membership is free and open to all ACS data users and new ACS data users. The group is led by our steering committee, and we try to pick a steering committee that represents all different data users, local governments’ data users, geography, geography data users. And we just had a new steering committee this this year.

So I’m going to show you the home page. Okay. This is fine. Here is the home screen of the new ACS Online Community. Here is just what I talked about, the purpose of it. Here’s some quick facts about it. And we also have the most frequently asked questions. That’s based on questions from data user surveys and also from the most viewed and interacted discussion forum post. You can view more FAQs on the FAQs page from there. We also have latest discussions, people who are posting in the ACS Online Community. We have a link to the Census Bureau website.

The discussion forum is the main part of the ACS Online Community. Here is an example of a discussion forum post. So a data user is asking a question, and then we get a reply from another data user. You can upvote replies, and if you become a member of the ACS Online Community, you can do things like uploading, replying, and adding to the discussion forum. Here you can see the views, replies. You can also add tags to new discussion forum posts. And then we have more information over here.

Next is the ACS resources page. Here you can see a lot of different links to ACS resources under these helpful headings. If you aren’t already familiar, the ACS handbooks are a great place to start, and we also have handbooks that are catered to certain data users.

Here is our webinar page. So this is the webinar we’re having today. And then we also have links to past webinars with recordings, information, and even the slide decks.

We hold a biannual conference every year. The latest conference was the 2023 ACS Data Users Conference. We have the agenda from that. That includes the recordings of the presentations and also the slides as well. We have the previous conferences, and those include that information as well.

I’m going to go back to my PowerPoint now.

Again, this is the discussion forum. Here is an example of a notification of a Federal Register Notice. That’s one of the examples of a discussion forum post that’s helpful to ACS data users.

Okay, so behind the scenes we can talk about the membership. We have over 5,600 members as of the end of May. Here you can see the fiscal year 2022 and 2023, and membership can vary over that time. And usually when we, when we have events like conferences or a new series of events called ACS on the road—we just went to the Texas Demographic Conference—we can see an increase in membership.

There’s a lot of discussion forum posts, and they get a lot of replies. Here again we have, uh, the total number of the threads and replies across the two last, last fiscal years.

And here are the number of page views that the ACS Online Community gets. If you’ve ever googled a question about the American Community Survey and its data, a lot of times the first Google result is the ACS Online Community itself. And you can see that overall, uh, with the last fiscal year, the page views and the ACS Online Community have increased.

The great thing about the ACS Online Community is that we do have a great response rate. So you can see that just within one day, if you post a question or an announcement or a comment, you get a pretty good, uh, you know, response rate.

And here are the top 10 discussion topics. We get a lot of questions about calculating margin of error, especially, uh, zip code–level geographic questions.

So onto our site upgrade. This is how the ACS Online Community used to look. You may remember it this way, but now live on the site, we have this new upgrade that’s, uh, more intuitive and more modern in the look and feel. This is how the discussion forum used to look. And now here is the upgraded website.

So finally, how do you get involved with this site? You don’t need to be a member of the ACS Online Community to view the posts, but you do need to be a member to post in the Online Community, comment, uh, and also upvote. You can tailor the email notifications that you get, so, uh, to new threads and comments. And these are all optional. So if you’re hesitant about joining the ACS Online Community because you’re worried about a lot of email notifications, you can cater those. You can also bookmark discussion forum threads so you can reference those whenever you have questions about a certain topic.

And again membership is free and signing up is very simple. First, you click on the sign up button in the top right and then just answer a few questions. We use this information so that we can better cater to different data user groups.

Finally, there is a picture of one of the ACS data users conferences, and please give us your feedback or suggestions.

Thank you so much. Here is my contact information if you ever have any questions. And I can either answer the questions or direct you to someone who will know your, the answer to it.

Mark Mather: Great. Thank you, Lillian. Next up we have Mary.

Mary Ana McKay, American Community Survey Office: Hello? Hello. Okay. All right, I can share my screen once Lillian is done sharing hers.

Lillian Kilduff: Yep. Um. Stop there.

Mary Ana McKay: Perfect. Knock on wood. Awesome.

Okay, so hello, everyone. My name is Mary Ana McKay. I’m a survey statistician with the Census Bureau’s American Community Survey Office. I’m here to highlight two data products and tools that you may be familiar with or you’ve never heard of before. And just a little bit of housekeeping, I’m going to apologize in advance if I speak quickly. I just have a ton of information that I want to share with you all, and I’m very excited to be here. I’m excited that you’re all here.

So without further ado, let me get started. I want to give a broad roadmap of what I’m going to be presenting during this workshop. So to start, I’m going to dive into the ACS Public Use Microdata Sample, or PUMS. This portion is going to cover basics. Then I’m going to run through the Census Bureau’s tool to access these data, and then I’ll wrap up that section with some resources for you as you dive in on your own.

And then immediately following the PUMS, I’m going to jump over and give a very brief introduction to the application programming interface, the API. We won’t go too much into details, but you will learn the basics, so you’re hopefully able to build off what we do today as you go off onto your own data journey. And we’ll go through an example API call, and then I’ll share just a sample of the many, many resources available to you as an API data user before I turn it over to Kevin for the last leg of this workshop.

So before I dive into the PUMS and API, I want to remind everybody about data.census.gov. It’s a really powerful tool for you as you grow your ACS data accessing skills. So many of you here today are probably familiar with data.census.gov, which is the primary way to access data from the American Community Survey, 2020 Census, and more. And I’ll be sprinkling my use of it throughout my two demonstrations, but it’s not the star of the show, so I’m kind of going to run through them a little bit more quickly than I would otherwise. But in an effort to be brief, I will let you know that there are a variety of how-to materials, video tutorials, webinars, and FAQs to help you use data.census.gov.

And I’m going to step aside again and just mention there are links at the bottoms of a lot of my slides. I have a colleague who will be sharing some of them in the chat, but also the PDF version of this presentation is going to have clickable links too.

So the ACS Public Use Microdata Sample can be overwhelming, but we’re going to briefly cover basics to start to get you familiar and hopefully comfortable with this powerful data set.

And I want you to think about these questions: What are your main goals when accessing ACS data? Are you primarily accessing pretabulated estimates? Are you finding that the data you need are not published in these estimates? And what about when you’re looking at cross tabulated estimates? How do you primarily access ACS data? Are you using data.census.gov or a third-party tool such as Social Explorer? What do the data look like on a daily basis? And finally, with the tool or tools you are using, what limitations do you face accessing ACS data?

So these questions might have different answers depending on the day or the data you need. So in some cases, the tool that we are going to explore will be the best option, but other times another method will work better. It’s all about the best way to address your needs. And I always check data.census.gov—I’m going to say this constantly throughout my portion—just to see if there’s pretabulated estimates for the data product and the geography of interest. But in cases that I need something a little bit more specific, I’ll hop over to PUMS.

So, for example, today I’m curious about poverty among veterans by age, and I know I can find tables in data.census.gov that might get close to what I need but not quite exact. And luckily, PUMS is going to be able to step in and get us the table that I want.

So I want to introduce a few PUMS basics before we work on an example. And finally I will share some resources that you can access on our website.

So again, when I say PUMS, I am referring to the Public Use Microdata Sample. ACS data products are released about one year after the data are collected, and the PUMS is a publicly available subsample of ACS records. The one-year PUMS estimates are a subsample of data collected over a calendar year, 12 months, and they constitute approximately 1% of U.S. households. Whereas the five-year PUMS combines data collected over 60 months, or five years, and they constitute approximately 5% of all U.S. households.

Additional restrictions are added to protect data confidentiality, such as including broader categories of data or grouping together extreme values in the form of top and bottom coding. And you’re going to see a couple examples of this top coding in my demonstration.

PUMS files allow data users to calculate their own estimates and margins of errors that may not be available on data.census.gov. Statistical software is recommended when working with PUMS data unless you are working with our microdata access tool on data.census.gov, and this is the tool that I’m going to be demonstrating today.

So here are some examples of why you might want to use the PUMS. These data come in handy when you are looking for cross tabulations that might not be part of the standard table packages released in the ACS. For example, you could be looking for specific poverty thresholds or income levels for veterans at a specific age ranges like I am today. Again, always check data.census.gov and the pretabulated estimates. They may have exactly what you need.

This information is going to be a little bit heavy, but I want to mention it before we continue. So PUMS data provide individual records that data users must aggregate to form estimates. Unlike in data.census.gov, there are no pretabulated data. Weights are included on the PUMS files so that data users may create weighted population estimates. If you are working with housing records, you will use the housing weights. And if you’re working with person records, you’re going to use person weights.

When working with a merged file that includes both housing and person records, person weights should be used to produce estimates for person characteristics. Housing characteristics cannot be tallied from this merged file without taking extra steps to ensure that each housing weight is only counted once per household. In today’s example, I am using all person records.

And then replicate weights, those numbered one through 80 are used for calculating replica estimates needed to calculate standard errors. These standard errors are necessary in order to calculate the associated margins of error or MOEs, and we won’t be going this in-depth for this presentation, but there are guided examples that I can direct you to for more.

The five-year PUMS is the equivalent of five one-year files, so again includes about 5% of all U.S. households. So people often ask, and you may be wondering, what is the benefit of the five-year PUMS? So there’s some nice standardization for the five-year PUMS that you can’t necessarily get by merging five- to one-year files. For example, there are new weights that are produced for these records so that the weighted population matches the latest population estimate. Dollar amounts have an adjustment factor to standardize them to the latest year, so that no one is comparing varying levels of inflation. Other coding schemes are updated, such as ancestry and occupation, so you don’t have to recode those yourself.

I’m going to focus on a limitation data users might experience someone accessing PUMS, and that’s geography. To ensure the confidentiality of ACS respondents, the Census Bureau has to balance geographic detail with detail in the data. There are more than 250 variables on a single PUMS person record. This means that we cannot identify as many small geographies in the PUMS as users might hope. We can put the region, division, and state on the file, but the only other geography is something called a Public Use Microdata Area, a PUMA. PUMS is not designed for statistical analysis of small geographic areas, but the PUMAs can still be used for focus analysis in counties and cities of about 100,000 people or more as well as many metro areas.

So I want to spend a little bit more time here on PUMAs. PUMAs are areas with a population of, again, at least 100,000, which is large enough to meet disclosure avoidance requirements. PUMAs are identified by a five-digit code that is unique within each state. These geographies are redefined after each decennial census and are defined by either the state data center or, in some cases, the Census Bureau’s regional geography staff. For example, the 2020 PUMA definitions were introduced with the 2022 PUMS files.

As with many geographic concepts, seeing PUMAs on a map may help you understand them better. So as you can see, some PUMAs are small and others are large, because, again, PUMAs are built on population and not geography. The smaller PUMAs here on this map are mainly concentrated in the Buffalo and Rochester regions of this map, and some counties in this region that have smaller populations are combined together as part of a multi-county PUMA.

So I use data.census.gov here to visualize geographies. This is a screenshot that shows, um, the PUMAs that make up Marin County, California. So as you can see, there are two that make up the county. So you can combine data from both to approximate estimates for the county. The primary difficulties occur when we get further away from urban centers to counties with smaller populations, which are then again combined with other counties to make PUMAs. And in these cases it becomes less feasible to infer data about the individual county. Furthermore, while I am showing you an example here of PUMAs that adhere to county boundaries, it is not actually a requirement that PUMAs be designed that way, although it is recommended.

And I want to acknowledge really quickly that some of you might know that data.census.gov now has an address lookup option in the search bar. I just want to let you know that right now, PUMA geographies do not pop up when you use that option. I just tried it before, but hopefully someday you’ll be able to put in an address and see what PUMA that falls into.

All right, let’s get our hands dirty with PUMS data. And to start, I’m going to heed my own advice and go directly to data.census.gov. I’m going to first see what tables I might find. And again, I’m going to zip through this because I want to focus more on the microdata access tool. I’m going to use the advanced search feature.

And again, today I’m interested in poverty among veterans by age. I’m going to apply two filters: “veterans” and then I’m going to select “poverty” to see what tables come up. I’m going to click the search bar. And I see here there’s actually a table age by veteran status by poverty status. And it’s a little bit more detailed; it also has disability status. But it does have generally what I’m looking for. So again I said poverty among veterans by age.

But as I’m looking through this table, the age ranges are not quite what I’m looking for, and I’m actually interested at below, at, and above poverty. So this just has two thresholds; I want to add a third. So in any other day but today this table might actually serve the exact purpose I’m looking for, but now I’m going to use the PUMS data to get what I really want.

I’m going to click on the logo to go back to data.census.gov home page, and on the top right, you probably can’t see it, there’s a little button that says apps. I’m going to click on that. And it’s this first option here that says microdata. So this is what you’re going to see. The default data set is the ACS one-year PUMS. And the select vintage is 2022. And perfect, that is exactly what I want. I’ll click next so I can select my variables.

So before I select my variables, I want to search for what they might be called. I know I want poverty, I want veteran status, and I want age. So I like to use the label option here—and I’m going to zoom in, I might have to zoom in and out—I like to use the label here to use keywords to see what pops up. And we also have PUMS documentation with data dictionaries, so you can do the same thing before you get into this tool.

So for the first one I’m going to type in “poverty,” and I see this income-to-poverty ratio recode; I selected this for, uh, today’s demonstration because this is the poverty variable in PUMS, so I want to show people how to use it. It does give me a little bit of a warning here that the variable is continuous, but we’re going to make a custom group with this variable to be able to put on our table, so we don’t have to worry about that quite yet.

And so for my veteran’s variable I’m going to type in “veterans” or “veteran.” And I’m going to open the detail of the three variables that show up. And this isn’t quite what I’m looking for. This veteran period of service is a little bit more detailed. I just want to know if a person has ever served in the military or not.

So now I’m going to try typing another keyword. So I’ll do “military.” And luckily for me I have this military service. Let’s cross our fingers. And yes, okay, this is exactly what we want. We have a value 2 that says “On active duty in the past, but not now.” So that’s how I’m operationalizing veterans. I’m going to select this variable. So now I have two. And my final one is age. So it’s right here at the top. It’s going to give me that same warning that the variable is continuous, but that’s totally fine.

So from here we have our three in the data cart. We’re going to click on View Table and see what we have to start with. So for most situations simply selecting the variables is not going to be the last step for you, for your table, unless by some chance it’s laid out exactly how you want it and the categories are exactly what you want.

So at first glance, there is a lot going on, and I’m going to rename the table just to keep myself organized up here. You can go in and change that title as much as you want, but I’m just going to do “Poverty x Age for Veterans,” so that’s just going to keep it organized in my head as to what we’re doing.

So we see that the default table has military, that military variable on the columns. We have nothing on rows. And then we have two variables here in the values in table cells. Then in this drop-down this is the first thing I’m going to change. I’m going to click on this and select Count. So this is going to give us a value for how many fall in each category.

So I’m going to organize to make variables, and then I’m going to put them so we have our universe limited to just veterans. And then I’m going to create grouped categories for age. And then income-to-poverty ratios on the columns will be three thresholds. Or I’ll make a threshold of three.

So to put in simple terms, our universe is going to be just veterans. My columns are going to be the recode of that income-to-poverty ratio. And then finally the rows are going to be simplified categories of age. And what’s great about this tool is you can organize and flip-flop your rows and columns super easily, so if you don’t like what we have planned, we can change it when we’re done.

So we’re going to start first with making our universe what we want, which is just veterans. So I’m clicking on the variable. I’m going to deselect everything that says Include in Universe. And I’m only interested in Value 2: “On active duty in the past, but not now.” I’m going to select that option, and I like to click into View Table just to see kind of what we’re working with with every change that I make. So now I see my universe is only limited to my definition of veterans.

So now let’s move on and make the age category. So I’m going to click on the Age variable. I’m going to click on Create Custom Group. From here we’re going to use the Auto Group feature. I’m going to change the start age to 17 because that’s generally the cutoff date to join the military. And then for this, this is an example of a top-coded variable, we have 99. So anybody who’s 99 years or older is going to be in this category. And then I want groups of 10 years. It’s not going to be perfect with the values that I have, but for what I need, this is going to be fine. And I’m going to click Auto Group, and you see that it makes those groups for you.

The last thing I’m going to do is there’s a Not Elsewhere Classified category. I’m going to click on Edit Group. These are all the values that aren’t in the groups that I just designated. I’m going to toggle to show off the table. So I’m going to toggle that on, and you have to click Save Group. So now this isn’t going to show in my table. Let’s view the table and see what we have. It doesn’t show up, but we’re just going to click and drag, and to keep myself organized, we have the rows is what we’re going to have for age. So I just clicked it and dragged it over to On Rows. And we’ll see. Now we have account for the people who are veterans in these different age groups.

And the last thing we have is to make the poverty variable. So again I’m clicking on the POVPIT variable. And just to look at this, it is continuous. And I want to explain a little bit more about what the numbers mean before I go in and make my custom group. So for this variable, less than 1 or 100%, because this is a percentage, is below poverty; 1 or 100% is at poverty; and above 1 or 100% is above poverty.

So these are the actually the three categories I’m going to create. But this is an instance where you can really go where your research question or your need takes you. For example, I know that 200% poverty is a threshold a lot of data users need, and there are limited options on data.census.gov. So using PUMS here is, you’re going to be able to get that.

So the calculation for this specific variable is simply to divide income by poverty thresholds, which are determined by number of children, sze of family, and inflation. So for this I’m going to click on Create Custom Group. I am not going to use the Auto Group feature. I’m going to dig in right here where it says Group Label. I’m going to start with Below Poverty. And again you can go in and change these group labels. Um, as you’re going through, if you want to relabel it, you’re able to do that.

So I’m going to click on below 501%. The bottom value I want is zero. And then the top value I want for this one is 99. I’ll click Save Group. So it makes that for me I’m going to click back into Not Elsewhere Classified. Let’s do at poverty. And this is going to be a single value. You can do that. So just when we’re looking at estimates, note that this only has one single value in it. So we have 100 to 100, Save Group.

And then finally we’re going to have above poverty. We’re going to select the remaining of the between 101 and 500. And then since this is another top-coded variable, I want this 500% or more because that’s above poverty. I’ll click Save Group. The last step similar to that Auto Group you’re going to click into, Not Elsewhere Classified. I don’t want this on my table so I’m going to toggle it off, Save Group. And now we’ll view table.

So again right now POVPIT doesn’t show, that Recode doesn’t show. But I’m going to click hold and drag on to columns. I can actually take the military variable off the table because it is my universe. I don’t need to have it on there. It’s included. And here is the example of the table. So now I have the poverty thresholds for different age ranges among veterans.

So I didn’t dive into this. But I want to mention that you can click Change Geography up here at the top. And you see that we have the geographies that we talked about. And the default is going to be the United States. And since PUMAs, the Public Use Microdata Areas, have populations of 100,000 or more, all of them and all of these geographies are going to be included in both the one-year and the five-year PUMS. So from here you can click, download, and share what you’ve made. And remember that you can calculate the error with resources available on the ACS website.

So now I want to go briefly and share some few links with valuable resources for you. So I do my best learning when I am practicing. So if you’re like me, I like to follow along with webinars that have some activities to check, and I put together a list of videos to see step-by-step directions for various aspects of the MDAT tool. So the data gems are going to be shorter, more brief videos, whereas the webinars go into a little bit more detail.

And I’m going to make a plug for the PUMS documentation page. I did mention it, but we didn’t go into it. It has all the resources you’re going to need for every data release. You can explore user guides, data dictionaries, and more. And this is also where you’re going to find directions for calculating variances.

And finally, I think a really great resource that we spent a lot of time perfecting, and Lillian talked about it briefly, are the data users handbooks. We do have one for PUMS users, and I also don’t want to spoil the next part of my presentation too much, but you can find the PUMS on the API.

Um, and with that, that’s the worst segue I’ve ever had, so again, I apologize, but now we’re going to jump immediately into talking about the Census Bureau’s application programming interface. So let’s take a deep breath and move on to the next part of the workshop.

So I want you to think again about the same questions we, we had when we were exploring PUMS data. So what are your main goals when accessing ACS data? Are you primarily accessing pretabulated estimates? Are there a few variables within a single table that you find yourself going to more and more? And what about variables across different geographies or across years? How do you primarily access ACS data? Are you using data.census.gov or third-party tools such as Social Explorer? And what do the data look like on a daily basis? With the tool or tools you are using, what limitations do you face accessing ACS data? Being able to answer these questions can determine if the API is a good option for your needs.

Now on to the basics. When you use the API, imagine that you are in a strawberry field since it is summer. The strawberries are data points you seek, and in order to go get them, you are going to be running calls or going around the field and picking the ripe strawberries. Data.census.gov itself is a fellow strawberry picker. What we are doing today is just a smaller example of what data.census.gov does through its website. We are trying to directly access the data in a very simple way.

So some of you may be creating dashboards on your websites that users will access to get different data to display, given certain criteria. Others might be trying to make data visualizations, and there may be some of you who are using R to run analysis. It’s also okay if you are none of these types of users. The API can still be a very simple process to get the estimates that you want.

As I was just describing what uses the Census API might be for, here are some more specific examples. What if you simply need just one variable, let’s say percent below poverty level for individuals under 18 and nothing else within the table? What if you wanted to grab all the census tracts within a county in Delaware? How about an estimate for an individual below poverty level at the census tract, county, state, and national level? It could just be that you have a data point that you’re trying to easily access year after year. I’m going to show you some ways to simplify that process for you using the API. And I will say this, and I’ve said it several times before using the API, consider checking out data.census.gov.

So with that let’s run through an API call. These are the ACS data tables that you can find on the API. In data.census.gov, the second column here is what the table ID starts with. For our example today we’re going to be using subject tables from the five-year estimates. So we’re going to be using this here. So after you put the beginning of the call, you’re going to put in the variables the tables and the geographies you want, but we’re going to get there in a second.

We’re going to start with data.census.gov, like I’ve said a million times already. And just for the purposes of time, I have screenshots here. So I typed in “poverty” because that’s what I’m interested in for this example. I found Table S1701. And then I limited my geography to Wyoming County, New York. That’s my hometown is there. And this is a smaller county, so it’s going to be the five-year estimates. It has a population of fewer than 65,000 residents, so we’re going to be using the ACS five-year estimates.

Now on this table I see, and I’m sorry if it’s hard to read, we have below poverty levels. So we have the estimate and the margin of error. That’s what I’m interested in. Just those two pieces of the entire table. This table also has percent below poverty level, which is a measure I would prefer, especially if I’m going to be comparing with other counties of varying sizes, but for this example, I’m just going to stick with the estimate and its margin of error.

I’ll mention one cool thing about data.census.gov, there are many, but if you look along the top of your table, there’s actually an API button now that you can click and it’ll create the call for the table that you’re looking at. So this can be really helpful if you’re using the filter options to select geographies, and you might just want that entire table you’re looking at. You can also use it as a starting point to build off. If you want a little bit more detail with your call. And I highly recommend always working off an example when you’re working on calls; it makes it a lot easier than building from the ground up.

So we only want two variables: the estimate and then the margin of error. And what I’m showing here is the entire call. But we’re going to dissect it before running and seeing what happens. I use the slide a few back to figure out what table type I had. And then I did a few additional steps, using some web pages to figure out (1) the variables that I need and (2) the geography.

So to start to break it down, this is the base for all Census API queries. This second set pulls out the data product year, 2022; the program, ACS; the date, the data set, ACS five-year, so this is the 2018–2022 ACS five-year; and then, finally, the table type, which is subject. And again you can refer back a few slides to see the base of all the table types. That slide will get you the portions up until this point. So once we get to this after ?get, that’s where the customization gets started.

So this pulls out, this is where I’m picking the variables. And how did I get here? We’re going to hop over to the website, and just for transparency, I’m using Google Chrome because that’s what I prefer to use when I’m doing API. So I’m going to census.gov/api, the main website, and I’m going to scroll down to latest available available APIs and view all available APIs. From here you see what’s available. I’m going to click on American Community Survey, in theory. And we divide it by the different data products, um, which I find they’re all pretty similar for all of them. So it’s easy once you know how to use one, you can jump around and use the other ones.

So we’re selecting the five-year data. We release this for every data release. So we’re here in 2022. I’m going to scroll down, and I find Subject Tables. So this is again the same for all table types, what I’m doing; you just have to make sure that you’re following along with your table type.

So the first thing I’m going to start with is the second bullet down: the 2022 ACS Subject Table Variables. I’m going to click on the HTML. So for API, Ctrl+F is going to be your best friend, if it’s not already. So I’m going to click Ctrl+F on my keyboard. And we’re going to type in “poverty” because I want to overwhelm you briefly with what shows up.

So as it’s loading, in theory, we’re going to have thousands of options. So it’s loading, um, there’s so many of it that now it doesn’t want to do it. So there’s actually over 3,700 results on this page for poverty. And that’s a lot to go through. So I’m going to show you a little bit of an insider secret, or at least that’s what I like to call it.

Um, I’m back on S1701. I’ve magically loaded it for us here, and I’m going to talk about the different columns. So this is a column set 1. We have the total. And then for this table, there’s a column set 2. Now what does that mean? We’re going to go back to this table, the variable lists. And if I start to scroll down, you hopefully can see that there’s a table ID, then there’s an underscore, and a CO1 that corresponds with column 1. So I can use this as my base to Ctrl+F again. And since I’m looking at S1701, I’m going to type that in. It’s going to jump me to the first time that that shows up. When I do the underscore, it’s going to jump me to the section for this table.

And I know I’m looking for the second set of columns, so I’m just going to write in CO2. And luckily for me it’s this first estimate in column set 2. So we have below poverty level population for whom poverty status is determined. Then the one that ends in E is going to be my estimate, and I want that margin of error, and you should too. That’s going to be the one that just ends in N.

So let’s hop back over to the slides to see what I did here. So I have the two variables that I found and I put them in here. I also put Name here. So to make sure that I get the geography names when I run the call. But this is not a necessary component of your call. I tend to use it just to confirm that I have the right geography, so I can run it with that, confirm I have the right geography, and then you can run it again without if you don’t need it for the larger purposes of your call.

One thing I will note, you separate the variable names with just a comma. if you add a space or an additional character, you are going to get an error when you run your call. So working backwards, if you get an error, double-check your call and make sure that there’s no spaces in between the commas. You can pull up to 50 variables with this method, and if you want more than 50, it’s likely that you just have to pull the entire table and then work from there.

I also want to mention one more thing. You can pull variables from different tables of the same type. Say, for instance, you want to pull all of the same variable in a table series for different race iterations. So we have detailed tables for the different race and ethnicity iterations that end in A through I. You can pull the same variable from those different tables.

I also want to jump back to this name variable and give you a little bit of a warning. So it does cause a shift in Excel, especially if it’s a geography within a geography. And you’re going to see this when we open the file from our example here. And I’m not sure if this happens with every table type, but just keep that in mind that I know for a fact that we do not recommend using it for group calls, particularly with data profiles. So just keep that in mind that it can get a little bit messy. But again, I like to have it as a little check for me.

So before I move on, what happens if you want all variables in the table? What if you want the entire S1701? You can use a group call. So I have that down here. Um, you can also use data.census.gov if you have the geographies you selected already. That API button is going to do exactly what this is going to do for us.

So now we have the last part, which is the geography. And in many instances you will want to limit to a specific geography. And in this example I want one county. And you may be wondering how I got these numbers. And I did not, in fact, memorize every county code for every state to figure this out. I’m going to share another secret, and I think this one’s a little bit more exciting, but who knows? You’ll have to tell me.

So we’re back on the ACS five-year API page, and we’re still in the subject table section. I’m going to click on the fourth bullet down that says Examples. So this breaks it up by geographies. And since I’m looking at state and county, I’m going to look at the example API calls that I have here. And fortunately for me I’ve used this so much that it’s already, um, calling itself out.

There’s one here that has a wild called, wild card or the asterisks for county and state. So if I click on this, it’s going to actually give me, um, and hopefully let’s, that we’ve zoomed in, it’s giving me all counties in all states. It does have a random variable. Um, just to call it out again, as an example, you can leave that in there, or you can delete it with the comma and just have name. So now you have the call to get all of the counties in all of the states.

And again, your best friend, at least for now, is Ctrl+F. You’re going to start to type in your geography of interest. And luckily for me, the first Wyoming on this list is actually Wyoming County. So I can use context clues here and see 36 for all of the New York counties that shows up. So I know that’s my state code. And then the second three digit code, 121, is going to be my county code.

So now we have all the pieces we need. I’m going to jump back. And we have the &for county 121 and &in state is 36. So the nice thing here is that you don’t have to remember the little syntax components, the codes. If you follow an example, you’re going to be able to always have access to what you want, and then you can customize from there.

So much like getting the full table, that group call, you can get full geographies. So what if you wanted all counties within a state? You can use that wildcard in your calls like we just did. For some geographies, as we just did to get our geocodes, you can do the wild cards for both components. It’s really trial and error.

So let’s take this call. I’m going to copy it from my document, and I’m going to run it in the browser. So I copy paste it, and now I’m going to run, and this is what we have. So we are getting the number the estimate of those in Wyoming County in New York who live below poverty with the corresponding margin of error. And we see we have the name here, we have the estimate, the margin of error, and then the state and the county codes.

So I want to just show you back on this slide that your output might look different than what you see here. Sometimes it’s the browser you’re using or the settings. But it’s okay, because when you download it, it’s all the same.

So jumping back over to the browser, if all you needed was the estimate, you can stop here, but you can also download it. And what you’re going to do is you’re going to right click. You’re going to click Save As. You’re going to name your file. And this is important, you’re going to type in the file name .csv. The last step for the Save As type you’re going to select All Files. So you’re going to click Save. And it’s going to download that CSV. And I’ll open it up just to show you what we have.

So like I mentioned briefly, or maybe not briefly, I think briefly, name does cause a shift, especially when you have a geography within a geography. So I had a county within a state. So here it shifted my variables, and all I’m going to do is highlight these. I’m going to cut and paste to move them over. Um, so that is just what you’re going to look like, what it’s going to look like when you download your file.

So hopefully that was not too overwhelming. Um, and that was just a little bit of a breakdown of what the API is. So really quick, I now want to share some resources as you go on your own. But don’t worry, I do have contact information so you can always be connected with our team if you get stuck.

So when you’re on your own, start with checking the example calls to get yourself started. I sound like a broken record when I say that. That’s what we did today. So I want to emphasize how useful they can be and how much time you can save. You can always edit them to fit your needs, but having the base like we walked through can be really helpful.

Unfortunately, some variable names change with every data release, so variables are added and subtracted from tables, so it’s important that you check the variable names if you’re looking at data year after year, to make sure you are extracting the same data variable. It’s super easy when you use that variable list, so I always just open that HTML as soon as I get started, as you saw in the walkthrough. And then the other one is that Examples page. So these are the two that I use when I’m customizing the components of my call.

And one thing I want to mention is keys. Um, some of you may be wondering what or why, and a key is essentially just that: a way to open the door to more calls. Without a key, you are maxed at 500 calls a day, and if it’s just you and your organization running calls here, there, a key isn’t necessary. But if you are creating a dashboard that’s going to get a lot of traffic, you might consider a key. It’s completely free, and it takes mere moments.

Um, and I will mention that if you’re going to use the R package tidycensus, you need a key. And Kevin’s probably going to repeat that as well. Can’t do it without a key.

Um, this is just a start regarding the resources. Again, this PDF is going to be able to be clickable if you can’t get access, um, in the chat to the links. So there’s a lot on here. And if you’re lost I can always connect you. The last two in this webinar list, um, are going to be a good run-through of an example similar to what we did today with a little bit more detail. And I also included some resources for using open-source data and programs, which is really helpful if you’re using the API.

One really unique and valuable tool we have to offer is the Slack channel. There are Census staff that engage on their every day to help with data user questions, especially if you’re accessing data through different ways such as R or Python. And finally, as I mentioned, tidycensus, it’s a great R package to use with the Census API. It is not maintained by us, but it has great resources to guide you.

Um, and I finally want to mention a few final things before turning it over to Kevin to wow us with his expertise with tidycensus. There is a team at Census that has live workshops to go over that MDAT tool and the Census API. I highly recommend you sign up if you’re curious to learn more about either. These are great for both beginners and advanced users. Please consider joining the ACS Data Users Group that Lillian highlighted at the beginning of this workshop if you aren’t members already.

And I know these were very quick demonstrations of the PUMS and API, but you can email our team at acso.users.support@census.gov if you have any questions in the future. Thank you so much. And Kevin, the floor is yours.

Kevin Kane, Southern California Association of Governments: Well, goodness, Mary, thanks for such a thorough and comprehensive, uh, you know, overview of both PUMS and, uh, Census API calls. Hopefully I can build on it. Um, doing these is kind of your job, for the most part, I just kind of, uh, do this as somewhat of a service to a degree.

I’m Kevin Kane. I’m the Program Manager for demographics and growth visioning here at the Southern California Association of Governments. Uh, why do I do this, uh, type of, this type of a webinar? Just, you know, um, I find it extremely useful to kind of have effective workflows, certainly in my field, which is regional planning and demographics. But, uh, I also teach this material to a course at the University of Southern California.

So, um, you know, bottom line, uh, I find, Mary’s API call workflow, uh, to be really useful, but you are a little bit limited in terms of the replicability of it, um, by putting calls into a URL. And, uh, she gives me a hard time every time I follow her after a webinar, um, because of what I’ve titled this, uh, “R tidycensus: Your graceful exit from data.census.gov.” And what I’ll share with you here is basically the workflow that I kind of developed once data.census.gov, um, started a few years back in order to just kind of help, uh, you know, be a little bit more replicable.

Uh, Southern California Association of Governments has 191 cities under its purview across six counties in Southern California. So we’re working with a lot of county-, place-, uh, and tract-level data longitudinally, uh, and kind of that’s buried within either PUMS or other detailed tables. I’m sure that’s the workflow for a lot of folks here.

So, um, I’ll be very brief in terms of, uh, slides here, but, uh, really, what I want to mostly show to you is a demonstration. Um, because frankly, it’s not possible in 20 or so minutes to actually get into R or RStudio or a coding environment. But basically what I’m going to pick up where Mary left off, uh, and wrap that within an R, or a code-based workflow.

So R is an open-source, uh, programming language. RStudio is a freeware wrapper of it that just makes it a little bit easier to use. Um, I’ve included here some very easy installation instructions, uh, for you, uh, like teaching in this because, uh, it’s not a commercial product. You can take it to wherever you work, uh, and not have to worry about a license.

The second thing that I’ll say is I’ve posted a lot of training materials here on this GitHub, uh, website here. I’m not sure who, uh, you know, the level of folks are GitHub users or not. I frankly just use this for file transfer. I am going to have to confess, I’m more of an intermediate-level user of this and frankly of some of the R packages. But like all of us, you know, hey, we’re, we’re doing this to do our jobs better.

Um, so what I’ve done here is included a package which I call the kind of a half-day R introduction. There’s also a video where I did the full webinar for this, uh, if you like the workflow. Um, I would say it probably would take you about a half a day, roughly, to get through it and to actually learn R to a point where you can use the Census API usefully. Um, if you hit this code here, you can download a ZIP file containing all of this. The key file is one that has a dot R at the end of it. And that’s what we’re going to be kind of going through mostly today.

Um, switching back here to kind of all the information you’ll need. Um, Mary already gave you a lot of the Census API information, so I won’t repeat that. Um, uh, there’s a full recording, uh, of, of the webinar that takes you through how to actually get up and running in our studio so that you can get to the point where we’ll start here today. Um, and also the details on Kyle Walker is amazing, tidycensus package, uh, which, although not maintained by the Census Bureau, uh, clearly is good enough to make a make a guest appearance in a Census Bureau closing slide. So, uh, certainly has kind of revolutionized how I interact with American Community Survey material.

So, um, how to get up and running here. Basically, uh, I’m going to open up this particular dot R file for you in our studio. If you’ve gone to the GitHub page that I shared with you before, uh, and I’m sure perhaps, uh, if you do want to follow along, maybe I could task Lillian, who has this slide deck to toss it into the chat for folks. Um, but if you’re, uh, I’ll just go through a couple of ways to, uh, to kind of access and use code here.

But, um, at the, at the bottom bullet here, uh, is what’s in this, Rbootcamp file. I basically have 10 modules here. Module sections 1 through 6 are just basic data usage skills and visualization skills using R. I’m not going to go over those today. I’m going to skip them and start with section 7, which is how to use the Census API. Um, and then I’m going to provide you with section 8, which is basically a replicable code block for doing those API calls. Uh, once you’re, uh, kind of up and running in R, you can use that to basically declare whatever variables you want, geographies, etc., um, and get them in, in a nice tabular format, in Excel format, even a shapefile format, if you like to do that.

Um, and, uh, new since last time we’ve done this, I’ve added a little bit of a code block to get longitudinal ACS data if you want the full series from 2005 or 2009, uh, when when ACS one and five years started respectively until now on the same thing. Uh, and then a new little section here at the end on, um, doing a tract-level map of something in your census place or in your city, uh, as, uh, Lillian shared in one of her earlier slides. I’m going to nab it here, um, you know, a lot of kind of how you interact with this, the API is, as Mary also said, uh, it follows the Census Bureau’s geographic hierarchy. Um, you know, and there’s, there’s a difference whether you’re on kind of this main vertical or if you’re off the main vertical.

Um, you know what I tend to focus on, uh, are counties or, you know, as kind of a reflection of the overall trend or census tracts to kind of be reflective of neighborhood-type dynamics. ACS oftentimes does go down to block group as well, but you tend to get those high margin of errors, which, uh, you know, well, I’ll leave it to you to decide the level of importance of the margin of error for your for your, uh, for your workflow.

But one of the challenges is that, um, cognitively, uh, and electorally and everything like that, places are pretty important census places, uh, which are basically cities, towns, CDPs, etc., are really, uh, you know, how people interact with information. So if you’re looking to get an understanding of how a phenomenon, uh, is dispersed across the neighborhoods of a city, you really need this tract-to-place relationship. So I’ll go into that a little bit, um, as I do the demo.

Um, apologies. I’m not really able to see the chat right now, but, uh, please, please holler if any issues. And thanks, Lillian, uh, for putting those, uh, those links up there.

So I’m going to, uh, go over now to RStudio, where I’ve just opened up Rbootcamp, uh, 2024.R. So really basic two ways, two main ways to enter code. On the righthand side here I’ve got a script file, which is, um, I prepared this, this one for you here. It’s about 500 lines or so and goes through those 10 modules. You can update it, change it, change things, um, and using this nice hashtag here could kind of comment something out. So, for example, line 22 here, um, the command is Print; I’m gonna print something, and then I made myself a little note behind the hashtag here.

On the left side is actually where you’re executing code. It’s got this little triangle called a chevron and a blinking cursive. So if I want to use the Print command to say “hello world,” which is sometimes what folks do when they start a new programming language, it’s going to return to me a line that says “hello world” back, because that’s what I asked it to do. Um, certainly when we get a little bit more sophisticated with our calls and things that we want to put into the console here, uh, typing it is not going to be efficient. So that’s why we have the script file up on the righthand side here.

So long as your cursor is on a line or has highlighted a portion of code, there are a lot of easier ways to run that code. The first one is to go up here to the top right and hit run. It’s going to do the same thing. Or if your cursor is just on it and you hit Ctrl+R if on a PC, Command-R on a Mac, or in some instances it’s Ctrl+Enter. I’m not sure exactly why people’s computers all have slightly different setups. That’s going to be the other way that you can run this line of code.

The second thing that I’ll mention about kind of RStudio in general, um, in terms of this workflow, is to just be really careful what you’re working directory is. What that means is a file path on your computer somewhere where you’re saving data, where you’re saving images, where you’re saving your output, or sometimes reading in data as well.

Um, there are a few ways to do this. Um, you can, uh, if I type “getwd,” it’s going to get my working directory. Goodness. The default is, uh, what appears to be somewhat something of a My Documents on a C drive. Um, I can go up here to Session, Set Working Directory, and choose, uh, where I want to pull information from. Or I can declare it in the code here. I’ve already written it down here is “setwd.” So if I “setwd,” um, something I’d like to do kind of early in the workflow, uh, I’m going to be working with this folder. Um, and you can see it’s in Dropbox, Rbootcamp as, as the folder.

So, um, that’s just the absolute basics again. Um, if you want more information, you know, certainly I would suggest downloading, uh, the package from GitHub, including this dot R file following along yourself or following it along in the video link there. And right now I’m going to scroll down to the fun step to actually the, uh, using Census API here in R, which is, uh, what I have as section 7 here.

So, um, the way that, uh, R is, is useful is that it kind of has a lot of base functionality kind of built into it. And then it’s very customizable. Folks have built, um, tons of different packages in it. And the one that’s really helpful is called tidycensus. I’m also going to be using a few other packages here to be able to work with spatial data and to do some other data manipulation.

Um, when you install it, you have to do two things to use a package in R, first you have to install it, and you just have to do that once. But then every time you open R or RStudio, you do have to kind of invoke the package or activate the package. So you install it with this line here, Install Packages. And I’m not going to run that because it’s installed already on my machine. But I am going to highlight all of these and activate these four packages here by running this line of code. So this is basically telling our studio, hey, add this new functionality to this instance of the program that you’re working on.

Mary already mentioned getting a Census API key, which you will need. Uh, it takes, she said, mere moments to sign up. I think it takes probably like 2.5 seconds perhaps. Uh, and that, that is an alphanumeric code that’s a little bit ugly here, but, um, it allows you to actually use this because you are going to be iterating and pulling a lot of things. Um, it’s nice not to overwhelm the, uh, the, you know, our, our federal government’s, uh, servers, uh, the Census Bureau.

So they’re, uh, the first thing that you’ll have to do is to enter your Census API key here. And tidycensus has a command called, you know, what do you know, Census API key. So you put it in here like this and hit Run. Here’s my Census API key and boom, you’re done. Um, it gives you a new flashing chevron. Uh, so that means it’s taking the line of code, uh, effectively.

So, um, really we’re just working with a couple of key commands here. Um, as Mary had mentioned earlier, there are a lot of things available through the Census API, the Economic Census, the decennial, various other programs that the Bureau has, and ACS being the key one.

In tidycensus, you’ve got decennial and you’ve got ACS. So “get_decennial” is the command here for how to how to get something from the decennial census. And this gets decennial census command takes a few different arguments. And you can see what I’ve set up here in line 405 is, well let’s see, I want state-level geography. So I want state-level data. I want this variable. We’ll get to how you search for variables in a little bit. You know a little bit already.

Um, I want the census summary file, and I want from the year 2000. So I’m going to run this “get_decennial” command. And then what this equal sign does is it puts it in an object or thing or a, you know, something that you can call back called medrent00. I’ve just called it medrent00. I could call it whatever I want. So I’m going to run this line here, and what it’s doing there, uh, for that a quarter second is it’s actually getting the data. And now if I just type that run, oh, um, it’s going to show me the median rent across all the 50 states.

Uh, I can make it a little bit easier by using the view command and view medrent00. What that will do is pop it up into something that looks a little bit more like Excel or tabular data and see that, um, goodness, in Alabama in 2000, rent is probably a heck of a lot less than it is today. Um, quite a bit higher in Alaska. So, you know, this passes the smell test. Always a good check. Uh, when you’re, when you’re doing a new data extraction process.

Um, so that’s useful. Um, you know, you can certainly there’s, there’s commands, right dot CSV commands to save this in Excel. You know, if you really want to, you can just grab and copy or what have you, uh, from here. But R has a lot of really nice visualization capabilities, so it’s nice to be able to take advantage of them.

I’ve left you with a few examples in this code here that you can, you know, certainly, uh, you know, modify the name of the, the variable, the data set you’ve extracted or the variable or change some of the other parameters. But if I run this line here, it’s going to make a nice little bar plot, um, of states by rent. And you can see here. Oh, Hawaii is quite, by quite a bit the highest. And this is alphabetized, um, well, not quite alphabetized by FIPS code, but, you know, thereabouts.

I’m going to close this here, and, and I’ve made a slightly fancier bar plot here with some bells and whistles by sorting the data, adding some color, adding a label, adding some guidelines. And I can highlight all of this and hit Run or Ctrl+R or what have you. And it gives me a really nice little bar plot here of state median rents in the year 2000. Again, seeing how it varies from a high of Hawaii to a low of North Dakota. Um, did not expect that to be lower than in Puerto Rico even, but goodness.

So, uh, here. So that’s, that’s just the way to kind of get a little bit of a visualization. And I haven’t uploaded any data into my program, which you usually have to do. Um, as long as you have the internet and a Census API key and tidycensus, uh, as a package installed, uh, you’re able to just extract it in one clean flow.

Now, in order to find good variables to use, uh, Mary already gave a little bit of a tutorial to that, but, um, you can do that within tidycensus if you want to. So, um, load variables is a, is a command here. And I’ve just asked it to look at 2022, five-year ACS, um, and put it into an object that I’ll call “acsvars” and, um, oh goodness, I have 28,152 entries for, for, uh, you know, explicit ACS variables that are coming in through what I imagine, uh, Mary can correct me if I’m wrong, what I imagine are the detailed tables rather than the summary tables.

Um, in any case, uh, this is a little bit cumbersome, you know, certainly. Um, and Ctrl+F is one of your friends. You can write this to a CSV here as comma-separated values file and, and open it up if you want to. But in the GitHub site I’ve included, um, my little cheat sheet. Um, if it’s useful to you, happy to share. But these are my top one, top most commonly used 125 ACS variables with their code and a somewhat intuitive abbreviation, um, that I’ve, that I’ve, uh, renamed it, “totpop,” for example, or median age. Um, this includes just some of the, the age structure, basics, race, race, ethnicity, commuting, educational attainment, income, and housing. Just to give kind of a smattering. Um, so if you want to start there, um, that’s, that’s not a bad way, at least, at least in my view.

So, um. Right. Uh, so, so now that we’ve found some good census variables to use, and we’ll scroll down just a little bit here and try to assemble, um, some tract-level variables for a county. Um, now this is the kind of the main command here. It’s get underscore ACS and you pass it a lot of information. I want tract-level data. I want the state of California, Orange County, and this variable here, 25035, which is the median age of the housing stock in each tract. You’ll notice that I’ve also added this argument called geometry equals true. This will also extract the data as spatial data so that you can visualize it right here in R. Or you can export it as a shapefile if you’re a GIS user.

So, um, it just takes maybe two or three seconds or so to get all the tracks, uh, in Orange County, California. Um, if I look at what this is, “head” just gives me the first five rows of any given data set. Uh, let’s see, I’ve got a GEOID. This looks like my FIPS code. I’ve got estimate, which is actually the value I’m looking for. So this tracks median housing home year, built year was 1971, 1959. All right. So this passes the smell test. Certainly these are reasonable values especially in the western United States.

Um, so I can do just a little bit of manipulation, renaming it old age. Um, you know, getting rid of the old one. And if I want to see how many rows there are, take a quick look and see that there are 614 tracts in Orange County, California. So now I have a good understanding of, of the rows and columns, which at the end of the day, that’s all data are.

What if you need more than one variable? Um, tidycensus will extract it for you, but it’s a little bit trickier because it does it long. Um, to show you what I mean, I’m going to, um, make a list of three variables: population; housing stock age, which we already did; uh, and median household income. And I can extract those in one single call by, uh, declaring this list that I made as the variables that I want. So I’m going to call this one TR underscore plus. Again, it just took a second.

And if I want to see how many rows are in underscore plus, oh goodness, it’s 1,842. Well I know there are 614 tracts. So, um, I can take a look at it and see that, hmm, this is not stacked in a terribly intuitive way. I’ve got three records for each tract, and each one’s for a different variable. Kind of a pain in the butt when you want to do math, compare it, put things as a rate, uh, put them on a map, uh, or anything like that. So, um, you know, if you really want to use it, you can use something called the match command, which is described in the earlier sections that I totally glossed over. Uh, and, and do a subset of this lengthy file and then and then bind it to your original text file. So now I have 614 entries here and eight total columns. I’ve got one for home age, total population, median income. My apologies to the Bureau for omitting the margins of error here, but you can grab those as well, especially for tracts. Mea culpa.

Um, some of the other nice features within R is that you can actually just plot this as a map using one of the, using what’s called the SF package. So if I hit line 450 here, sorry, um, uh, goodness, I can get a nice little map already of the tracks in Orange County. And again, uh, let’s see, we’ve got 1940s, 1950s here, kind of in the North Side. This is downtown Santa Ana, the older neighborhoods of city of Anaheim. Those look a little bit older, uh, then used to get to the south, to Irvine, to Laguna, Niguel, Coto de Caza. These are the newish developments up in the hills. You can see that reflected in the more curvilinear boundaries but also in the, the newer home ages there.

So, um, neat little trick there. And if you are a GIS user, you can use this “st_write” command here. Um, whoops. To write an entire shapefile. Um, now this is, uh. Let’s see. What did I call it? I called it orange underscore merge. So if I go back to here now, I have four files here I’ve seen if you’re a GIS user, you know, you’ve got somewhere between three and eight files typically together in a shapefile format. But now I can use this in GIS. I have orange underscore merge. All right.

So, uh, racing along right here. Um, hope folks are getting a little bit out of this at least. But what I’ve built here in section 8, um, is a way to group a lot of variables together. Uh, like I said, it’s a little bit clunky to extract variables one by one because they’re stacked long. So you want to make a loop and, uh, loops are, you know, a little bit more advanced coding skill. Uh, but I’ve built this to hopefully make it so that you can just enter your parameters here, um, and, uh, and then run this big block of code in section 8 and then get a good data set.

So I’m going to ask the audience here for somebody to put in the chat a state and a county, like not a tiny county, at least the medium-sized one. You know, five more seconds before I use Tampa. Okay. Sacramento. Let’s do, let’s do Sacramento okay. Thank you.

So Sacramento County, California, my state equals CA. My county equals Sacramento. Let’s see. Let’s I’ll run the first chunk of this. And the first chunk. The way I’ve set this up is it’s just grabbing total population B01001 underscore 001. And then what I’m doing is taking this whole big list of 125 variables that I’ve shared with you earlier in this spreadsheet here. Uh, and then I’m renaming them to something that’s a little bit intuitive. Um, not perfect, of course, but, uh, you know, if you follow a logic, uh, you know, commute, walk, uh, median household income, you know, female aged 5 to 9, etc. Uh, you know, should be logical. Select all of this, even do a little bit of math on the end of it. And it’s really only going to take probably a few seconds to extract this for, um, 125 different variables for, um, the tracts in Sacramento County.

All right. There we go. I can view this. I just called it D to keep it a little bit easier. Uh, and now you can see all the tracts, uh, total households, median age of 29. Goodness, that’s quite a bit under median. So that must be a young area. Um, race ethnicity, variables, etc. Um, how I put them up, I’ve got 135 total columns in this, uh, in this data frame right now. I can write it to a CSV right here. Whoops. I called it Hillsboro, Florida. Sacramento. Don’t get confused now. My Hillsborough file is messed up, but, uh, that was, uh, that was from somebody else. So Sacramento tracts and ACS can just open it up in Excel in a comma-separated values format, um, and, um, manipulate that however you like.

So there you go. You’ve got, um, uh. Uh, you can also write it to a shapefile here. Um, Again, make sure you name it the right thing so you don’t forget that that’s Cook County, Illinois. Um, and, uh, you know, you can do some plotting. Um, here is median median home value in Sacramento County. I’m not super familiar with the urban geography of Sacramento, but I’m assuming this is a little bit more kind of an inner ring neighborhoods in the downtown core and then the fringe, you see some higher income as well. This is all in the SF package. So there are a lot of parameters that you can do here.

Uh, the nice thing is, well, by doing this workflow is that you can just do math right here. So what if I want to know if the the share of commuters who work from home. Uh, a question that we get asked all the time. Uh, so I could just do the, uh, number who work from home divided by the total population of commuters. Do a little math here and then plot that variable. So, okay, the work from home share in Sacramento County is way high out here, fairly high in somewhat of the downtown core, and a little bit mixed. Again, you can do quite a bit of a different analysis here if you’d like.

Um. And then if you want to plot the variable a little bit more neatly, um, I’ve got median home value pulled up here with the Jenks optimization so that it gets some nice natural breaks. You can do a reasonable looking plot just right here in R without having to open up GIS or anything else.

Two more quick tricks here before the getting in under the gun at 12:30, uh, Pacific time. that is, um, is a task we often need is to get longitudinal ACS data. Um, I find this a little bit tricky, um, because you do have to iterate quite a bit. Um, can somebody, let’s see. I’m going to pull, um, Milwaukee County, Wisconsin, from, from the chat here for this example. But basically what I’m doing here, um, is I’m making a sequence of all the ACS years that are available. Um, sending, I use a lot of one-year data because I tend to work in big counties. Um, so it’s a little bit tricky because it didn’t exist for 2020. So you have to make sure to make a list that has that gap in there. Um, five year, that’s not an issue.

But in any case, um, what I’ve kind of given here is a not quite as sleek of a, of a loop as, as earlier, but a mechanism to, uh, go through and enter whatever I’d like to here, Milwaukee County. So, um, this is going to take a couple of seconds, in fact, to run this because it’s pulling, um, well, that’s what I’ve come across. Oh, I don’t think that. I think there we go. So now you can see as this runs here in the red text, it’s 2008, 2009. It’s just looping through, uh, all of the available ACS years to get me, um, two variables here. I put them in. I kind of snuck it in here. One is, it’s what I just showed you earlier, the number of people who work from home versus the total commuters. So, um, and what this can give you right here is total commuters in 2005, the number who work from home, and then a really nice time series of how work from home has evolved since the ACS started collecting data on it, uh, in 2005.

So again, you can write that, you can use it later. Um, I can plot it here, make a little plot and see. Goodness, that’s what happened here during COVID. Uh, and then in the most recent year, a little bit of a dip. I can make a better line graph that I’ve put a few bells and whistles into. Uh, whoops, I forgot to change this to Milwaukee County, Wisconsin. I’ll do that in just a second here. Um, and I can even make a, um, a comparative graph. Change that to Milwaukee, just so I don’t get confused. So an example of how to do a little bit of these edits here.

And what I’m also going to do is I’m going to, I’m going to make a comparative graph here. I’m going to also extract Sangamon County, Illinois, which is Springfield, which is kind of a smallish mid-sized city. Uh, and then, um, and then run through this again. And once I run through this again, I’ll be able to have a graph that compares two different places in their work from home trajectories, which is kind of interesting. And this is probably the slowest part of the Census API, at least the way I built this here.

All right. So now I can see Milwaukee County work from home. Goodness, shot up during COVID and went down, but a much smaller, um, you know, uh, metro area, uh, had not only a lower level overall but didn’t see a kind of a drop in 2022 as a return to office happened. So again, just an example of some of the analysis you might be able to do with this.

I’ll share one final tip and trick in the last couple of minutes that I have with you here. Um, and it’s something that we just, just figured out. Um, my colleague Echo Xiang, who’s also on the call, and I, um, is to do a tract-level map of something in a single city. So while I’m doing this, if somebody can, um, tell me a city and the county it’s in, uh, to make a tract-level map, something that actually has not just a few tracts, something that’s a little bit at least medium size.

And this is going to, um, uh, this is going to require a few new packages: terra, readr, and mapview. All right. Let’s do, uh, let’s do, um, Oklahoma City. Actually, it has city twice. I’m not 100% sure it’s going to work. Um, how about, um, Tempe, Arizona, Maricopa County. Tempe, Arizona.

Um, I’m just going to work with median household income right now to show you this. And, um, you know, also one, one thing that I’ve given you here, um, in the GitHub is a file, that’s a relationship file developed from geo core that I use to relate tracts to census places, because, again, it’s not on that main spine of the census geographic hierarchy. Um, so, you know, it gives you the percentage, you know, tracts don’t necessarily nest within cities or places. And this, this tells you, for example, uh, Autauga County, Alabama, which we always see when we’re doing census work nationwide. Uh, nine, 98.42% is in this tract, and 1.5% is apparently outside of Prattville, Alabama. Um, so just, that’s all to say that you can define a threshold, um, to kind of get rid of some of the superfluous stuff that’s, you know, 99% outside of the city.

So I’m going to declare a place, a variable household income. I’m going to make sure that I asked for Maricopa County, Arizona. Uh, solicit this tract data here. Make sure everything works. Okay. Looks like it all works. And then I’m going to use this neat mapview feature here, see. All right. Some, some issues here. So I’m going to go back to, uh, press the old Riverside County, California. What is this for? Apologies for the work. If you troubleshoot, I’m sure.

All right, here we go. A dynamic map of Riverside County, California, by median household income. Uh, mapview even allows you to hover and see what the household incomes are. You can do a pretty yeoman’s job of exporting the image. And, uh, there you go. There is your analysis.

So anyways, check the GitHub. Um, hope this was a helpful demonstration. A little bit sloppy, albeit, but, um, uh, enjoy. And thanks for participating. I think I’ll turn it back to, uh, Lillian and/or Mark for the kind of the closing.

Mark Mather: Great. Thanks so much, Kevin. Um, we are we, it’s 3:20, it’s 3:29 East Coast time. So I know we’re almost at the end of the time for the webinar, but, um, and this was an incredible amount of information. So just as a reminder, we will be sending out a recording and the slides that have all of the relevant links. I think that, um, flew by in many of these, in many of these presentations.

Um, I think because of the time we are going to officially close the webinar, but the panelists have agreed to, I think that you all agreed to stay for a few more minutes. If anybody wants to stay behind, uh, more informally and ask them some questions, we can, um, unmute you and, um, you know, five or 10 more minutes, I think, and we can, uh, turn off the recording so we can just speak more informally. But, uh, with that, I do want to officially close the webinar. I’ll stop recording. And thank you all for joining.

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Transcript

Beth Jarosz, PRB: Hello, everyone. I’m Beth Jarosz, Senior Program Director at the Population Reference Bureau and Vice President of the Association of Public Data Users. And with both of those hats on, I want to welcome you to what will be a very engaging discussion.

As you all know, it’s been nearly two years since the Dobbs v. Jackson Women’s Health Organization decision changed the abortion health care landscape in the United States, and researchers have been working to understand the implications of Dobbs on access to care, birth rates, health, and other outcomes.

In addition to hearing a bit about that research, today we’re going to tackle questions like: What are the barriers to conduct abortion-related research? What have we learned from the data so far? What are the data gaps, and how can we fill them?

To help answer those questions, I’m joined by an all-star cast: Abigail Aiken, Associate Professor of Public Affairs at UT Austin; Jane Seymour, Research Scientist at the University of Wisconsin–Madison, Collaborative for Reproductive Equity; Alison Gemmill, Assistant Professor at Johns Hopkins Bloomberg School of Public Health; and Laura Lindberg, Professor of the Rutgers School of Public Health.

We’ll hear from all four researchers and will round out the hour with a Q&A. If you have questions, please type them into the Q&A box, and I’ll ask as many of your questions as I can during the Q&A session at the end. So without further ado, I’m going to invite Abigail to begin.

Abigail R.A. Aiken, University of Texas at Austin: Thank you very much, Beth. It’s wonderful to be here with everybody today. I’m just going to share my screen so you can see my slides. And then I’m going to give a short, 10-minute overview of some of the work that we’ve been doing trying to measure self-managed abortion and shield law abortion provision in the post-Dobbs landscape.

I want to say that the work I’ll present to you is the result of a lot of people’s work. So everybody here has been involved with Project SANA, that’s our project, the Self-managed Abortion Needs Assessment Project, at some point over the past five years. And so want to, um, say thank you to everybody who’s been involved in trying to get an effort to look at the who, what, and why of self-managed abortion in the U.S. off the ground. When we started this project back in 2018, we knew so very little in the research sense about self-managed abortion, and we really come a long way since then.

So to be clear on terms, I’m mostly going to be talking about self-managed medication abortion this afternoon. And that’s the process of obtaining medication abortion pills. It could be mifepristone and misoprostol or misoprostol alone, and managing your own abortion outside of the formal health care setting, so with no U.S. licensed provider or clinic involved. And, of course, self-managed abortion can also be done via other methods: herbs, botanicals, self-harm. There’s lots of different ways. It’s really a spectrum of things. Most of what I’ll talk about today will focus on medication self-management, but in the Q&A, I’m also happy to talk about some of the other methods as well.

So self-managed abortion is really hard to study. It’s hard to study because by definition, it’s something that’s happening in private settings. It’s usually in people’s homes. It’s not something where there’s an administrative record that you can request or track easily. And so since 2018, we have been thinking hard in Project SANA about how to, uh, count self-managed abortion, how to explore self-managed abortion, how to get a sense of how often this might occur and why it might occur.

And a lot of work has been done since then, and we really have focused a lot of our work on the nonprofit organization Aid Access. And that’s because since 2018, Aid Access has been providing self-managed medication abortion through online telemedicine. Now, the model of Aid Access has changed in recent times, and we’re going to talk about that later in the presentation. But for about five years this was considered self-managed medication abortion because it was happening entirely outside the formal U.S. health care setting.

We formed a collaboration with Aid Access, having worked with their sister organization, Women on Web, in Ireland and Northern Ireland prior to 2018. And so we were able to look at the trends in the number of people that were making requests to Aid Access. We established the safety, effectiveness, and acceptability to the user of this model. Um, please check out our papers if you’re interested in that.

And we also had a look of, at the question of, Would we expect there to be a relationship between abortion bans and self-managed abortion? You can imagine that when states put, um, abortion restrictions in place and people have less access to clinics that they might more often look to self-manage outside of the formal health care setting. And it’s also evident from our research and the work of others that people sometimes also self-manage from a point of view of being their preference. It’s not just an alternative to lack of clinical access; it’s also something people might prefer to do for a variety of reasons.

So the first part of what I’m going to talk about looks at this question of is there a relationship between SMA and abortion bans? Because leading up to Dobbs, we wanted to know, can we use data from Aid Access to find out whether when states ban abortion post-Dobbs, are we going to see an increase in people self-managing? And we had good reason to expect that that would probably be the case based on a number of prior studies that I’m going to talk about super quickly because I’ve only got 10 minutes. But I just want to show you the strength of data behind this relationship.

So this first paper looked at what happened when Texas, back at the beginning of the COVID-19 pandemic, banned abortion essentially for a period of two weeks by saying that abortion was a non-essential medical procedure. And we looked at what happened at, to request to Aid Access during that admittedly short time period. But it was a really quick and evident increase. You’re looking here at a graph of cumulative requests, so you’re seeing the actual data before the ban. They’re in black. Then you see the data after in the orange line, and the model fit, um, compared to what was forecast. And we saw this doubling of requests over the two-week time period after abortion services were shut down in Texas.

Staying in Texas, we saw what happened in September of 2021, when Senate Bill 8, that was essentially the six-week ban, uh, went into effect. And again, we saw that compared to a long baseline of what Aid Access had been doing, requests for self-managed abortion really spiked when people knew what was about to happen. But even out several months afterwards, you were seeing a tripling over the baseline numbers.

Again then after Dobbs, we saw states with total abortion bans. And again, we saw, when you compare to this baseline of what access had been seeing from these states, a doubling or sometimes even a tripling of requests in those banned states, which is more than what was happening in states without bans. So over and over again, and this is really, I think, in keeping with what we’re seeing, we see in the global context, what we’ve seen historically in other places with abortion bans, when you make clinical abortion access harder, you see this increase in people looking to self-manage.

So now what I want to talk about is going beyond requests and trying to actually count, because the question that, you know, people often ask is, okay, but we see that relationship, but how many self-managed abortions do we think are happening in the U.S. post-Dobbs? And that’s a really hard question to answer. Looking here though, this is from WeCount, and people maybe hope are familiar with the effort from Society of Family Planning to count and make a census of abortions provided within the formal health care setting after the Dobbs decision.

And this is early on, right? We’re only looking out here to six months post the Dobbs decision. But initially there was a decrease. There was a decrease in the number of abortions being provided within the formal health care setting, which raises the question of did we see a concurrent rise in people self-managing? Do we know how much of that decrease of approximately 32,000 abortions provided within the formal health care setting might get offset by abortion outside of the formal health care setting?

Now, the post-op landscape really changed what self-managed abortion looked like. That’s another issue for us. We had worked with Aid Access for a long time and continued to do that because they were an online clinic mailing pills. But there was such a response to the Dobbs decision from community support networks. So based on accompaniment models, oftentimes in Mexico or Latin America, and we knew that model’s been so prevalent in South America for so long, coming to the U.S. to try to secure access for people through volunteer networks and then also websites selling pills. So not online, um, telemedicine operations, but simply online vendors that were like, yep, we’ve got misoprostol/mifepristone. You can order it from us, and we’ll send it to your house.

So trying to, first of all, map this is a large effort, right? Trying to figure out how many different providers out there, out there, as particularly with online vendors, they tend to change a lot. And different people may run multiple websites. They may pop up and go away. It’s hard to keep track of all this. So part of the work that we’ve been doing is trying to figure out how many pathways are there, how many providers are there, and then what does each provider provide.

And in an attempt to do that, we published the first kind of findings out of that looking out six months post-Dobbs. Um, you can find this paper also online. We saw this increase in self-managed abortions provided in that six-month period post-Dobbs, when you saw the decrease that was found within the formal health care setting and now this increase in self-managed abortion. And this chart attempts to break it down by the different types of provider, the community networks, the telemedicine org, and the online vendors. So you can see the baseline.

There was, of course, provision beforehand before Dobbs. People were, of course, self-managing then, too, partly as a result of abortion restrictions, partly as a result of preference. But it really changed post-Dobbs in mostly in states that enacted bans. And approximately 26,500 abortions is our estimate for the six-month post-Dobbs that took place outside the formal health care setting. Lots more methodological details on that in the paper that I don’t have time to cover right now.

I wanted to highlight that these different types of organization, um, play a critical role, partly because of cost. Um, from our qualitative work, we know that even the $90 that a service like Aid Access was asking for in donation is too much for a lot of people, and many of the accompaniment networks are able to provide at no cost, which is really important for people.

Secondly, these options are out there. They are, they’re, they’re becoming more known about. But that doesn’t mean that people don’t often look to other ways, too, maybe as part of their journey to getting what they need or as the ultimate end of their journey. And for some people, this could even be something that’s unsafe or harmful to them. So I haven’t talked a lot about that today, but I don’t want to overlook it completely. It comes up in our qualitative work quite a lot.

Then finally we’ve got this shifting post-Dobbs landscape. We’re now looking at numbers coming in from WeCount showing abortion numbers increasing. And we also see from the Guttmacher map project also, um, similar counts in the monthly provision data as well. So there seems to be an increase in access overall.

And what Aid Access are now doing we wouldn’t call self-managed abortion anymore because they’re now providing, um, entirely through U.S.­-based clinicians, through shield laws. So getting medication abortion to banned states from providers that are working in states that have shield laws, that allow that to be within their scope of practice. So now we have a different, um, challenge on top of the counting of self-managed abortion, which is this new definition of shield law provision, and trying to count that alongside, um, the self-managed, uh, medication abortions too.

So I like to leave it there because I only have those 10 minutes. Uh, that’s a summary, a very high-level summary of what we’ve been up to and what we’ve been trying to do. Uh, please check out our site to look at our papers. Um, I’m looking forward to your questions in the Q&A as well. Thanks so much for your time.

Beth Jarosz: Thank you so much for setting the stage and for covering a lot of information in a very short time. And I’m going to invite Jane up next.

Jane Seymour, University of Wisconsin–Madison CORE: Wonderful. Thank you all so much. Um, I’m really delighted to be here today to talk about some of the ways that we’re measuring the impact of Dobbs in Wisconsin at the University of Wisconsin Collaborative for Reproductive Equity, or UW CORE. CORE is a research initiative focused on abortion, contraception, and other aspects of reproductive autonomy that’s housed at the University of Wisconsin School of Medicine and Public Health, which is Wisconsin’s largest and only public medical school.

Okay, there we go. So given our focus, one of CORE’s goals both pre- and post-Dobbs is to document the health, well-being, and social consequences to Wisconsinites of barriers to wanted abortion care.

As you may know, post-Dobbs, an 1849 state law here in Wisconsin was interpreted as banning abortion, and as a result, all abortion services in the state were halted, and data from the Society of Family Planning’s WeCount effort, which Abigail referenced, shows here that the, in the year after Dobbs, roughly 7,000 fewer abortions occurred in Wisconsin compared to the prior year.

And while abortion services have resumed in Wisconsin as of last fall, we know that many barriers that predate Dobbs remain in place, and providers are still ramping up services to pre-Dobbs levels. In other words, there are still significant barriers to abortion in Wisconsin.

So naturally, this leads us to ask what happens to Wisconsinites who want abortion services given these bans and restrictions. And we can imagine three scenarios for these folks. First, we can imagine that some likely cross state lines for abortion, as was already the case prior to Dobbs, given Wisconsin’s extreme abortion restrictions. However, data from, excuse me, data from WeCount, um, shows us that the increases in haven states, such as some of the other Midwestern states shown here, don’t make up for the bans in states such as Wisconsin. Um, second, we can imagine that some people self-managed an abortion, obtaining pills from a variety of sources, including places like Aid Access. And finally, we imagine that some Wisconsinites who wanted an abortion did not have one and instead carried their pregnancy to term.

So although we can imagine these scenarios, it’s important to understand the lived experiences and trajectories of abortion seekers in this restrictive environment as well as the impact on their health and well-being.

So to understand these experiences, we must get information from Wisconsinites who considered abortion. As many on this call know, prior to Dobbs our field often recruited for studies from abortion clinics, which may have induced a selection bias, as we failed to include those who face barriers to care such that they never made it to a clinic. Some researchers in our field have made attempts to overcome this limitation by recruiting from prenatal care clinics and/or online via social media or, or Google ads.

Post-Dobbs, especially in states where there were no longer abortion clinics, including Wisconsin for a time, this method, methodological challenge has only been amplified. In other words, we have to search in many different places for research participants to fully answer our questions about barriers to care.

Here at CORE, we’re taking a multi-pronged approach to understanding the impact of Dobbs on abortion seekers, which we call the post-Roe impact research portfolio. In this portfolio, there are three studies shown here, which we refer to as the Turnaway, prenatal, and MAP studies. I’ll briefly note that the Turnaway work is comprised of interviews with those who participate in Dr. Diana Greene Foster’s post-Roe, uh, work.

But today I’m going to focus on our other two studies, which recruit from prenatal care clinics and online, respectively. And both include longitudinal surveys as well as in-depth interviews. Overall, this portfolio builds on Dr. Foster’s original Turnaway Study as well as pre-Dobbs work that sought to recruit those who considered abortion outside of the clinical setting.

Here’s a bit more detail about these two studies. In brief, the prenatal study recruits patients from UW Health prenatal care clinics, after which they complete a baseline survey. Those who report having considered abortion are invited to participate in an in-depth interview two weeks after the baseline survey, as well as for 10- and 18-month follow-up surveys. Additionally, at baseline, we ask all participants to agree to use of their electronic medical record, or EMR. We pull EMR data for all study participants to compare outcomes between those who did and did not consider abortion care.

Oops. Excuse me. Uh, currently, we’re still recruiting, and the first participants have received their 10-month follow-up survey. As you’ve already seen, the MAP Study, or the Midwest Abortion Pathways Study, is a partnership between CORE, Ibis Reproductive Health, and Indiana University and recruits participants via Google and Microsoft internet search engine advertisements. Participants are eligible if they’re pregnant, live in Wisconsin, and report having considered abortion for their current pregnancy. They complete a baseline survey after clicking through the advertisement and then are invited to complete 4-, 10-, and 18-month follow-up surveys, as well as an interview post-4-month survey. Currently, we’re still recruiting in the first. Participants are about to receive the 10-month survey.

Now, typically this is where I would share a few nuggets of our results, but instead I’m going to share some challenges we’ve encountered as those feel particularly relevant to today’s conversation.

First, as is likely no surprise, abortion seekers who were hard to find pre-Dobbs are even harder to find now, likely due in part to concerns about the legality of abortion and related increases in conversations about digital security. Second, the legal and health care delivery context for abortion is extremely dynamic. We’ve had to be very flexible and in some cases act quickly to update our survey instruments to understand the current legal or political context in Wisconsin.

Finally, and perhaps most notably, bad actors and bots abound in this work. We’ve been overwhelmed by the number of fraudulent responses we’ve received and, in turn, the time and effort it takes to parse the good responses from the bad. In the cases of bots that churn out thousands of responses each week, identification is fairly easy, as, for example, their open-ended responses and their email addresses are completely nonsensical. But for those duplicate responses from legitimate participants who are likely trying to obtain additional remuneration and individuals posing as eligible when they’re not, the process is much more art than science.

Through this process we’ve learned a lot about how to proactively prevent fraud and handle it when it slips past our checks. First, the thoughtful, capable data scientists on our team have been an invaluable resource. Their efforts have allowed us to analyze data quickly and again, pretty proactively and quickly, identify appropriate data flags with relative ease and pivot our processes accordingly.

Additionally, having checks in our data collection tools that help identify bad actors and bots has been crucial to our success. I’m happy to talk more about those in detail during the question and answer period, but for now, I’ll highlight to you. Um collecting IP addresses and asking questions for which responses can be compared, both within a single survey and across multiple survey waves has been crucial in helping us catch fraud. With that said, I’ll say that our team remains hopeful in this really is a team effort.

Through the process, we’ve developed even stronger partnerships, and we’ve learned so much. We’re better scientists because of the challenges we’ve encountered. And while our progress may be slower than we hoped in some regards and much more challenging than we expected, our methods are working. We’re finding Wisconsinites who considered abortion and never made it to a clinic and are willing to share their experiences with our team.

So I’ll leave, leave it at that except for two asks. My first is that we continue to fill the gap in finding folks who consider abortion but don’t make it to care. They’re a crucial population within, uh, that should be a focus of our work more often, and I’d ask that we all continue to work collaboratively to build effective anti-fraud strategies that can be applied across contexts. I know there are many folks in the field and in other fields working on this effort, and our collaborative efforts have already been so fruitful, and I welcome more investment.

So with that, thank you very much. And I’ll welcome questions during the question and answer or at this email address at any time.

Beth Jarosz: Thank you so much, Jane. And we will move on to Alison.

Alison Gemmill, Johns Hopkins Bloomberg School of Public Health: Okay. Great. So thank you so much for organizing this. Um, I’m really happy to talk about the, see, it’s working, the data component here. So, um, for those of you who don’t know me, I’m a demographer and a reproductive perinatal epidemiologist, and I am studying the health impacts. And I’m going to talk about some of the challenges of using secondary data sources in this work.

Um, so I wanted to highlight two current projects. Uh, and this is collaborative work with Dr. Suzanne Bell. The first of these is to look at the impact of highly restrictive abortion policies on fertility: so birth rates, uh, severe maternal morbidity and mortality, if possible, and birth outcomes. And then the second project is to look at the impact of these highly restrictive abortion policies on changes in high-risk pregnancy care. And this work is currently funded through the Society of Family Planning.

So what are the data sources that we use? Um, for the first project where we look at birth rates, we obviously use birth certificate data. So we, we rely on vital statistics data a lot. Um, we are also looking at some infant outcomes like infant mortality. So we rely on death certificates as well. The good thing about vital statistics data is that they are virtually complete. So for births, for example, they represent over 99% of all births in the U.S., including home births, and all states participate. So we have good coverage over time and space.

Um, for maternal health outcomes or pregnancy-related outcomes, we can’t really rely on vital statistics for those. And I’ll explain more why shortly. So we’re going to rely on state-level hospitalization data, um, and specifically this is through a database through AHRQ. And what we do is we use ICD 9 or 10 codes for diagnosis and procedure, procedures to identify these types of outcomes.

And then, uh, potential projects in the pipeline might actually be using some of our typical survey data. So, for example, some of you are familiar with the National Survey of Family Growth, or NSFG, and the Pregnancy Risk Assessment Monitoring Survey, or PRAMS, and I’ll talk about those in a bit.

So I wanted to actually highlight some data challenges, uh, because I think it’s really important in this work, and it’s what we’re dealing with. The number one challenge: everybody wants to know what’s happening on the ground right now, but we do not yet know, and that’s because our data are lagged in terms of when they are released. So in the case of vital statistics data here, um, usually final birth and death certificate data are lagged by a year. So we have to play the waiting game. However, uh, I’ll talk about this at the end, uh, there have been changes in that they’re making provisional data more available to researchers. And this has been an amazing change.

Um, in terms of hospitalization data, these take a lot of time to come out as well. So I can’t tell you yet what’s happening to an outcome like severe maternal morbidity. Um, so these are lagged by about two years. So data on 2023 births will not be available until early 2025, for example. Um, in terms of those two surveys I mentioned, CDC’s PRAMS, they interview people who are postpartum, so these are among people who gave birth, data on 2023 births will not be available until 2025. And then for the National Survey of Family Growth, they did resume data collection in 2022. So there is a potentially an opportunity to use these data, but they won’t be released for some time.

The second challenge is about varying data availability, availability across states or limited geographic identifiers, and to conduct the kinds of studies that we want to conduct that have very strong causal inference embedded in them. We need data for states, each state. So the state inpatient databases that I talked about, the hospitalization data, those are great because we can get those at the state level. However, one of the big states that we’re interested in, Texas, does not participate, at least in the HCUP Central Distributor where we access these data typically. And then for the NSFG, they do not include state identifiers, nor do they include month year of important reproductive events. To access those data, you actually have to go to a restricted data center, which is associated with time and cost burdens.

The third challenge I want to note is that there’s varying data quality across states. And this is very, or this is, um, specific to birth certificates here. Um, so not all items on the birth certificate have high validity. And this validity varies by state. So because I have a captive audience, I wanted to highlight one of the papers that we wrote. Um, so what you see down here is a section of the birth certificate where there is something known as the maternal morbidity checkbox. So on the birth certificate we can capture information about some of these common maternal morbidities like maternal transfusion or ruptured uterus. However, we did a validation study where we compared the data on the birth certificate to the hospitalization data, and the estimates do not match up. And what our conclusion was is that the birth certificate data for these specific maternal mortality, morbidity indicators, the validity is quite low. So I recommend not using them.

Another challenge: the data are cost prohibitive. So I mentioned that we’re going to be using these state inpatient databases. These are really expensive. So one year of data for one state can cost anywhere from $200 in the case of Florida to about $1,600 in the case of Mississippi. So for our project where we need data for several states and several years, this is going to be quite costly. Thankfully, we have funding to support this work. Um, but again, this is a big barrier, right? Um, I mentioned the NSFG. You have to go to that restricted data center, and that costs a lot of time and a lot of money.

And then finally, I think a really great data source are Medicaid claims data. However, I will not be using them because they are very expensive to use. And you kind of need an existing data infrastructure. So you need, so you need to be linked to universities that are already kind of using Medicaid data because it’s a big, um, what’s the word, it’s a big barrier to overcome to get started with the Medicaid data, is what my understanding.

And then finally, this is my last data challenge, and it’s more of a statistical challenge. It’s about how do we estimate impacts among subgroups. And we know this is a very important question. However, the numbers can be quite small and this comes with lower statistical power. So, for example, how do we measure fertility rates among smaller or, yes, subgroups in smaller geographies? Or how do we measure events of very rare maternal outcomes that really matter, but they might just be so rare they’re hard to study.

So we need to expand our causal inference toolkit to detect these effects. We don’t want them, we don’t want them to go unnoticed, right? We want to detect some signal. So how do we do that? And that’s where I think a lot of the work needs to be done in terms of population health outcomes.

And then finally I’ll close with some data opportunities. Um, the one that I briefly touched on is that the CD, or the National Center of Health Statistics has made this release of provisional data in terms of birth certificate data and death certificate data. Um, and it’s been a game changer. I think what happened is COVID prompted the release of this data because we needed to know in real time, especially with mortality, what was going on. Um, and as of 2023, provisional birth and death certificate data are now available on CDC Wonder. So if you don’t know about CDC Wonder, this is a great interactive, um, platform that you could use online to download data. It’s an amazing resource.

So one of the first things that we did, um, while we’re still waiting for, uh, to study impacts of Dobbs, is we could study the impact of Texas SB8 policy using that provisional data from NCHS. And so this is a paper that my colleagues and I wrote, um, looking at what happened to fertility after SB8. And we did find a 3% increase in live births.

And I believe this is the last thing I want to say. So I just wanted to know other potential data sources for those of you in the audience that are thinking about doing this work. Uh, one colleague at Hopkins, he’s a current student, has actually used the behavioral risk factor surveillance system, which does have data by state. And he looked at outcomes related to self-reported anxiety and depression and found that those were elevated in respondents in banned states following the Dobbs decision.

I know other people might be looking at changes in the workforce. So there’s potential data, um, from some organizations that might be possible. I know people have looked at Reddit forums. Um, so there’s some rich qualitative there, data there potentially. And then I think we’re just going to be, have to be innovative in terms of other types of digital data that might be used.

So, um, I think that was it. And I look forward to any questions you might have. Thank you so much.

Beth Jarosz: Thank you so much, Alison. And last but certainly not least, I will invite Laura to present.

Laura Lindberg, Rutgers School of Public Health: Okay. Thank you all for having me here today. And, um, Alison really set this up because I want to focus on a subpopulation, which is adolescence. And I want to move my slides. There we go.

So adolescents are experiencing disproportionate legal, financial, logistical, and social barriers to abortion. This policy environment impacts not just adolescents seeking abortion, but all adolescents. And the experience of adolescence itself may have fundamentally changed. Adolescents are thinking differently about many aspects of their lives: their relationships, health, where to go to college, where to live, and what their future might look like.

Adolescents are impacted by new abortion laws aimed at all pregnancy capable people, as well as those such as abortion trafficking laws that specifically target minors’ access to abortion. And abortion access remains difficult for minors, even in states where access is protected, whether it’s because of parental involvement requirements, financial logistical challenges, or forms of abortion stigma.

It’s against this backdrop that I’m going to draw on a new report, Adolescence Post-Dobbs: A Policy-Driven Research Agenda for Minor Adolescence and Abortion. And I’d like to take this opportunity to acknowledge and thank my incredible co-authors, Julie Maslowsky and Emily Mann. While we focus on minors because of their unique standing in the law, our recommended action steps would benefit adolescents of all ages, their families, and their communities. And today, I’m going to focus on the data agenda that we developed in this report.

This report was produced under the auspices of Youth Reproductive Equity, a national multidisciplinary research collaborative composed of both researchers and clinician scientists. We formed in 2021 in anticipation of the Dobbs decision and its disproportionate impact on young people, and we continue to expand our work.

So, we found that minors are systematically underrepresented in research about abortion. Far too often, studies start at age 18, excluding the experiences of younger adolescents. Failing to produce needed research on minor adolescents and abortion is an equity issue, and the large knowledge gap has become a liability as the data gap allows for non-evidence-based policies.

A key call to action of our research agenda is to ensure that research designs and analyses include the experiences of minors. We make a distinction between studying the direct impacts of changing abortion policies on pregnant minors and the indirect impacts of abortion policies on the total population of minors.

So currently we lack the data needed to study the direct impacts of the new restricted abortion policies on minors. For example, it’s well established that federal and state abortion surveillance is incomplete. For example, California doesn’t participate in these systems, and states don’t always collect data by age. Studies of abortion patients, usually based out of clinics, even when they do include minors, are often limited by small numbers, and the new real-time data collection of abortion counts, such as that from Guttmacher or the Society of Family Planning, doesn’t even collect patient age, leaving critical gaps in the surveillance of minors’ receipt of abortion care.

Thus, we recommend expanding data collection to increase and improve the inclusion of minors in clinical studies, as well as state and national surveillance, and this may include a need targeted oversampling of minors.

Further, where there is data, we need to expand again our approach so that we present age-specific data in ways that we can identify minors’ unique experiences and not group them with all adolescents up to age 19 or, worse, with the general population.

In addition to expanding our research, we call for approaches that use tailoring, which is to tailor direct collection to provide an in-depth examination of those experiences that are unique to minors. This allows for focused attention to policies, focus on this age group’s abortion access, experience, access and experiences separate from those of adults. And a key recommendation around tailoring is to field a new longitudinal study of pregnant minors across different policy environments to better understand their pregnancy, abortion, and parenting experiences.

Now, I want to turn to the data needed to examine the indirect effect of abortion policies on minors. And here we propose the need for what we call contextualizing, calling for population representative as well as targeted studies of minors that aren’t so focused on abortion but capture the context of adolescents’ lives as abortion access is changing.

So as we think about contextualizing, we can see many gaps in existing federal, state, and national data collection efforts that limit our, our ability to do needed research. So let me just talk about a few. There’s obviously other data sources out there, but I think these are some major ones that are worthy of discussion.

So the Youth Risk Behavior Survey, or YRBS: these are state surveys of high school students. And they should allow us to compare between different abortion policy environments. But an increasing number of states are choosing not to participate in the YRBS, and this is likely to only get worse over time. Still, there are opportunities here to abortion policies by knowing the state that the student resides in to outcomes such as their mental health, their experience of intimate partner violence, and contraceptive use patterns.

Alison mentioned the National Survey of Family Growth. This is a household survey that starts at age 15 and goes through age 49. However, the sample size of adolescence is relatively small, and especially if you want to do analyses limited to sexually experienced teens. Um, Alison noted that the geographic identifiers in the study are not made publicly available, which I’ll talk about more in a minute. She also mentioned BRFSS, and this is a good resource because it does provide state representative health data that could be of interest, but it only samples adults. And this is an example of the exclusion of minors from research that an expansion of the survey could address and improve.

And finally, we lack a current longitudinal study of adolescent lives. Add Health has been probably the most influential source, source of longitudinal data on teens, but it was started in the 1990s, and those adolescents are now adults. Indeed, it’s the National Institute of Aging that now funds this project, so it doesn’t help us to study today’s teens in today’s post-Dobbs world.

The National Longitudinal Survey of Youth, or NLSY, faces similar aging as the 1997 cohort, which was the most recent cohort, is now in middle age. The Bureau of Labor Statistics is currently designed designing a new NLSY, and this is really an opportunity, I hope, for collaboration to ensure that relevant health and psychosocial and other effects are, and measures are included in addition to the conventional labor force and work and education measures that this survey has usually focused on.

These gaps lead to key recommendations to improve and expand current data collection and start new efforts in the field. So we’re calling for both new cross-sectional and longitudinal survey of the general population of adolescents. These surveys should include not only sexual and reproductive health behavior, but adolescents’ knowledge, attitudes, and behaviors related to changing abortion access. And they should allow for the longitudinal study of the impact of the Dobbs environment of living in this, at this time on their behaviors, their education, their economic and their health, health outcomes into adulthood. Now is the time to design and implement these studies.

And we recognize that part of the context of minors’ lives are the adults in them. Be it parents, health care providers, caseworkers, teachers, even policymakers whose views on adolescence color their approaches. And studies of these adolescents who are influential in minors’ abortion experiences are also needed to understand the context of these experiences.

Finally, I want to remind everyone that in our country right now, your zip code determines your access to abortion care. And to help researchers study the influence of location, we need to make geographic data more readily accessible. This could include strategically collecting state representative data as well as making existing geocodes on surveys more available. So Alan, Alison pointed out the challenges of the difficult to access NSFG geocodes through the research data centers. I’ve lived through that; I call it often the, um, circles of hell, um, and it is not easy. But one approach to facilitating needed research with these geocodes could be to create publicly available aggregated geocodes that group states according to their state policy environment but don’t run these kinds of risk of disclosure, disclosure that the RDC is trying to protect from.

So in conclusion, all adolescents are impacted by the changing abortion policies, even if they aren’t seeking an abortion. And there’s a need, there’s substantial need for more research and data for this population. The historic exclusion or blind eye to minors’ experiences as compared to adults leaves us with inadequate data systems. Excluding and overlooking minors is both an equity and a rigor issue. We need quality science that includes marginalized populations, including those treated differently because of their age. Expanding, tailoring, and contextualizing data collection for minors and improving how researchers can access key data offers us a needed path forward.

I’ve shared here a QR code so you can access, download our entire report. It has not just these data and research needs, but also a deep dive into the changing legal and policy environment. I also invite you to contact us at Youth Repro. We are available for consultation, collaboration, and thought partnership, and my email is up here as well. Thank you.

Beth Jarosz: Thank you so much. All of these presentations have been fantastic, and I want to take a moment to acknowledge all of the great work that you are all doing, and also to suggest that our audience members seem to think so, too, because we have a ton of questions. Um, I will try to get to as many of these as we can, and that’s the 15 minutes that we have left.

And so I want to start with, um, and this is probably for Abigail, but for any of these, any of you can answer, um, and the question is, Is it legal for women in banned states to receive the pill in the mail? And I think maybe talk a little bit about shield laws, which you mentioned in your talk.

Abigail R.A. Aiken: Yes. Thanks for the question. Um, it’s a complicated one because it depends, um, on who we’re talking about being the subject of the laws. Um, it is the case that, um, most states don’t have laws on the books currently that would explicitly criminalize the person using the medications or receiving the medications for a self-managed abortion, although that doesn’t mean that people won’t be surveilled and won’t be subject to investigation or even times prosecution, um, unlawfully. And so, um. That’s one where I would also, if you’re interested in that question, check out the resources of If/When/How: Lawyering for Reproductive Justice because they’re extremely knowledgeable on this issue. So that’s one, um, where it’s, you know, not explicitly criminalized, but doesn’t mean that people couldn’t face, um, legal jeopardy.

For those who are delivering the pills, and I see the question about, um, is it, uh, legal for the person sending them. Now, technically, that would be against the laws of most states who had to have abortion bans or have restrictions on, uh, telemedicine provision of abortion. But the idea of the shield laws is to protect providers in states where they reside and where they practice. So there’s a great article in The New England Journal, uh, written by David Cohen, that lays out shield laws. It’s a really interesting and informative read, and it tells you about some of the protections, uh, that providers residing in states with shield laws would have in terms of protecting their license and protecting them from states that want to enforce their own state laws outside of their state boundaries.

Beth Jarosz: You know, and that kind of leads into, I love someone posted a question that I already had on our list, and I think it dovetails nicely with this. And it’s speaking to privacy and confidentiality. I think that’s one of, it’s sort of the, the elephant in the room when we’re thinking about this, that we need really good, high-quality data for a topic that is sort of legally challenging. Um, and, uh, so can you speak, I know we talked a little bit about that with geography, but I think each of you probably have a perspective on this. Who wants to go first, Abigail, do you want to take us off?

Abigail R.A. Aiken: Yeah. I can kick off there. Yeah. From the self-managed abortion and also the shield law perspective, um, it’s extremely difficult, right. And, you know, we know that, as I said, just because people don’t live in states with state laws that explicitly criminalize them doesn’t mean they won’t be, uh, surveilled and harassed and sometimes even unjustly prosecuted.

And so we really limit our data collection, and we are really limited in terms of what we can collect. So we never collect anything identifying. And even then, we don’t collect a lot of the things that, you know, I appreciated Laura’s call for this more detailed data, and I think we absolutely need that. It’s really hard with self-managed abortion. Um, and so far we have really stuck to the idea of firstly, anyway, counting right, getting information on volumes on prevalence.

Um, before Dobbs, we did quite a lot of qualitative work looking at people’s experiences and their motivations. And I’m not saying we won’t go there again. Um, but it is an even more difficult environment in which to, uh, do this work than it was before. And so, um, right now we’re really very much, when we get data directly from providers, we ask for as little as possible.

Beth Jarosz: Thank you. And I think Alison and Laurie, you both mentioned, um, sort of geographic specificity, which we know is really important in this context. And, Jane, I have a follow-up related to privacy for you, too, but I want to talk a little bit about the challenge of balancing geographic access with confidentiality in these cases. If either of you want to speak to that.

Alison Gemmill: Well, I was actually thinking about some of the rarer outcomes that we’re going to be studying, which you could inadvertently disclose somebody’s identity in a given state, you know, in a given age range. And they have a very rare pregnancy-related outcome. And so one of the challenges we’re going to have is that data are made available to us, and we have a data use agreement where we will make sure that we protect the data at all, at all costs.

But, um, it’s, it might be challenging for us in how we disseminate the information. So we have to make sure that we’re not going to, you know, report only five cases of something. So there’s certain rules. So that’s how I’m thinking about it with the secondary data that I use.

Laura Lindberg: Yeah. And I just want to mention, I mean, there certainly are real risks here. And our role as researchers, we have to take those seriously. But we also need to be educating our IRBs about the reality of the extent of those risks. And what we’re hearing from a lot of research these days is that IRB, IRB members don’t know much about abortion. They’re getting their news from wherever they’re getting it. Um, and they may be concerned in ways that doesn’t reflect the true risk, and their solutions may not be true solutions.

So being the person in your university or in your setting who can work with the IRB to educate them, um, can be helpful. And the Society of Family Planning is in the process of preparing and will be disseminating a series of, um, guidance documents that people can use with their IRBs, both for general sexual and reproductive health research and focused on doing research with minors. So that should be useful to the field.

Beth Jarosz: Wonderful. Thank you. And that’s actually a really nice lead into the question that came in for Jane. And it was thinking of privacy, actually, from the flip side is that, um, you’re finding ways to remove cases that are fraudulent using IP addresses, but does that cause any IRB or confidentiality concerns?

Jane Seymour: Thanks so much for this question. This is something I think about pretty much constantly, it feels like. Um, I think it’s a really, really important conversation, and the tension is really real. So I don’t, I don’t pretend to have any of the answers.

Um, with that said, I really appreciate Laura’s call to, for high-quality data. And we as researchers have a responsibility to ensure that the data that we put out into the world, the results that we put into the world are as real as possible. And in the case where we’re dealing with hundreds and thousands of cases of people who in some cases, like, I think they’re, they’re kind of the two groups I spoke about, there’s like the bots and things that are really, really easy to weed out. You know, when it’s like Abcdefg and a string of 14 letters at mymail.com. That’s pretty easy.

There are some people who have, like, really done their homework and have really convincing stories. And in some cases, we’ve gotten as far as getting them on the phone for an in-depth interview, and it’s become clear that there’s no way that this is a real story that they’re telling. They’re talking about getting pills over the counter in Wisconsin in a time period when, like, pills are not available over the counter, abortion wasn’t available in Wisconsin, you know, just and, and when we probe that, it’s clear that that’s not the case. We’re not talking about issues of stigma where somebody might be changing their story due to abortion stigma.

At any rate, I think it’s incumbent upon us to balance participant safety and security with the rigor and validity of our data. And we feel pretty strongly that IP address is one of those data points we can collect that helps us significantly. We’re really lucky at our institution to work with an IRB that’s very supportive of our work.

One thing I’ll flag here that I didn’t have time to talk about in my presentation was the challenges that we’re working with, um, as it relates to certificates of confidentiality from the National Institutes of Health. There have been changes to that program, and many third-party platforms, including Qualtrics, which I imagine many of us use for data collection, are no longer acceptable, uh, third-party platforms to use under a certificate of confidentiality. So we’re really again struggling with how much does the rigor, how do we balance the rigor with the data protection. And again, I haven’t figured this out, but I think it is a real tension that we’re going to have to continue to work with as a field.

Beth Jarosz: So, um, so, so many more questions. We have time for one, maybe two more. So let’s see if I can package these together. Um, I have sort of a very broad question. I think all of you have touched on this, and that is, What’s a research question you really wish you could answer but don’t have the data now? And one specific question from an audience member is, Do you have statistics on covert delivery? Um, sort of these, uh, abortions that are happening in the states that, that perhaps that have banned abortion, um, in the wake of Dobbs.

Alison Gemmill: Um, I guess I’ll start. And mine is a pretty easy ask. I think I talked about state inpatient data, so that’s people who are hospitalized. I think the next step would be thinking about emergency room departments as a source of care. Um, and those data do exist, but again, not for every state. So that’s a big challenge. And then I think, like what Laura said about longitudinal data, I would love to have longitudinal data to link people over time, whether that’s within administrative claims data or a survey using secondary data. So I, I would love to see data like that eventually to answer some of the questions that we have.

Beth Jarosz: Laura, I know you had a call for data on adolescents. Do you want to renew or repeat them?

Laura Lindberg: Yeah. I mean, I think for, for adolescents, from a research perspective, from an IRB perspective, from a policy perspective, we need to be thinking more about what the harms are for adolescents who wanted an abortion and couldn’t get it, who want and were not telling their stories in our research, that the harm that when we think we’re protecting them by not including them in our research. In fact, so many harms happen when we can’t tell the stories and they’re not included.

And this happens not just for abortion research, by the way, but sexual reproductive health research more generally. So do we, if we don’t include minors in our contraceptive studies, we can’t show that contraception is safe for them because they weren’t in the study to begin with. They need to be included more to in fact increase their safety, not harm it.

Beth Jarosz: And I think I have one more question for Alison. And it’s, you know, you talked about the maternal morbidity data and the research that you’ve done around the challenges with that on the birth certificate record. Um, if you could make recommendations for how to improve, and you probably have that in your paper, but if you could make recommendations about how to improve that data collection system, what would you say?

Alison Gemmill: Yeah. I think, thank you. That’s great. And it was a research letter so I couldn’t say much, but I would, I mean, my understanding is that the National Center for Health Statistics has not had the resources to really check the validity of items. Um, and so first of all, I would want an evaluation of the validity of items on the birth certificate. That would be number one. But then second, it’s really a state’s issue, right? And the data are collected within states at their health departments. And it seems like there is varying data quality. So if there’s a way to train people that fill out the birth certificate to improve the way that they do that, I think that would go really far, because there’s some pretty potential rich data on maternal health there that we could be using.

Beth Jarosz: I think we have time for one more question, and I think this one is for Jane. And it’s, How does a researcher assure that a source for qualitative data like Reddit is reliable and meaningful?

Jane Seymour: That’s a fabulous question. Um, I think that in qualitative data, you know, the aim is not to be generalizable. The aim is to understand the experiences of those people for whom data exists. Um, you know, unfortunately, this is, I have not worked, some of my colleagues at CORE have worked with Reddit. Um, I have not worked directly, worked with Reddit data, but know that there’s quite a literature, which Alison you’ve referenced here. And Alison, forgive me, I’m not sure if you’ve worked with Reddit data, so please feel free to chime in if you have, or anyone else on the panel.

But I think that that Reddit data is a source of data that we can use to understand the experiences of some people who are searching for abortion, have had abortion, or have been denied abortion. And it’s never going to give us the full picture of the experience of everyone, but I want to be really clear that a lot of our quantitative research also doesn’t do that. So these are all important pieces to a larger puzzle that we can put together when we work effectively together to, to gather high-quality, rigorous data.

Beth Jarosz: Thank you. So I want to thank you again for sharing your expertise and your time with us today.

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Transcript

Diana Elliott, moderator: Hi everyone. Thank you for joining. Welcome to today’s today’s webinar on writing about population research for non-scientists. I’m Diana Elliott, Vice President of U.S. Programs. Though this webinar was organized by the Population Reference Bureau and the Association of Population Centers, with funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

I’m pleased to introduce four speakers to today’s event. Shannon Monette is the Lerner Chair in Public Health Promotion and Population Health at Syracuse University, and we’ll cover some of the benefits of writing research briefs and examples of impact at the Lerner Center. Following Shannon, we’ll have Beth Jarosz, Senior Program Director; Paul Scommegna, Senior Writer; and Mark Mather, Associate Vice President, all in the U.S. Programs department at PRB. And we’ll be providing some additional guidance for writing briefs and bridging the research and policy gap.

We’re going to save the Q&A till the end, and we encourage people to use the raise-hand feature in Zoom and to unmute yourself to ask questions. So for those of you who aren’t familiar with where this is in zoom, if you go to reactions at the bottom of the screen, you’ll see that there’s a raise hand feature under that reactions tab. The webinar is also being recorded and will send you a link to the recording and the slides in a few days. Closed captions are also available. Participants can turn on captions by selecting the Show Captions option from the Zoom control bar. Now I’ll turn it over to Shannon.

Shannon Monette: Thank you, Diana. Welcome, everybody. I’m looking forward to the conversation that we’re going to have today about writing population research for non-scientists, in addition to being Lerner Chair at Syracuse University. As Diana mentioned, I’m also the director of the Center for Policy Research here and a professor in the sociology department. And we have two brief series, one through the Learner Center and one through the Center for Policy Research. And they’ve both been quite successful. So what I’m going to do is, um, provide a motivation for writing briefs. Presumably you all think that it’s important and that’s why you’re here. But I’m going to give you a few reasons why I think that, um, writing policy and research briefs can be really exciting. Uh, I’ll talk a little bit about the purposes of and audiences for these briefs. I’m going to provide a couple of overarching tips about structure. In a couple of examples. Uh, Paola will cover more detail later about some tips for writing effective briefs. And then I’ll finish up by sharing some examples of how some of our briefs have resulted in broader attention, uh, or impact that that’s been really exciting.

Uh, so first, why might we want to disseminate our research to nonacademic audiences or non-scientists? Well, one reason is that it’s just super fun. Um, I think it’s way more fun than writing academic papers or presenting academic talks, because you can be more free in your language and your style. You can be provocative. Um, it provides the opportunity to meet different kinds of people that you might not otherwise meet and interact with. Another good reason is to help break down barriers between academics, between scientists, and between the public, and show people outside of academia that what we do can be relevant and is relevant to their lives. Um, it’s also an opportunity to show the public that we’re people to into to help build trust, which is particularly important during an era where there’s declining trust in academics and experts. Another reason is that your dean, your department chair, your research center director, your parent, your partners can use it to show off your work. Um, provost and deans love this kind of stuff because it’s really easy for them to share with donors. Um, and rather than an academic article which can be 40 pages or even longer if you consider the supplementary materials, these short 2 to 3 page briefs or something that you know the dean can share with alumni or with their advisory board members, your parents might read these things too, like mom probably isn’t going to share your academic article with their friends, but she might post your brief on Facebook. Another reason is that it’s a way to get really timely findings out more quickly than an academic journal, you know? We all know it can take forever for academic articles to come out. Sometimes we’re working on time pressing issues, and we want people to know what’s happening right now, so it’s a really good outlet for that.

Um, briefs can also get you research into the hands of unexpected audiences. It can launch unexpected opportunities. I’ll talk about some of our successes and those unexpected opportunities at the end of my presentation here. Um, and of course, these things can generate a lot of impact. They may… They may actually be your best shot at someone paying attention to and using the hard work that you’ve done. Um, academic articles are behind a paywall. They’re long, they’re dense, they’re difficult to get through. But briefs and things like op eds even get to main points quickly so they can have a lot of impact.

Uh, and so in terms of like, what are the purposes of research briefs or policy briefs and who are the audiences? Well, the purpose of briefs are to translate your findings and disseminate your findings in publicly accessible and easily digestible formats, toward some purpose, towards some action. So that purpose or that action might be to enhance knowledge or raise awareness. It could be that you want to change hearts and minds about some topic. It could be you actually want to change behaviors or practices. Um, or it could be that you want to influence policy debates. Um, the audience for these are varied. I think it’s, it’s somewhat important going into the writing that you have a target audience in mind. So your target audience may be policymakers at the national level, the state level, the local level. Um, your audience may be practitioners. If you’re writing about health care, for example, um, your audience may be reporters. A lot of faculty actually use these briefs for their undergraduate classes. So the audience may be students and the audience might also just be the general public.

Um, what I like to tell our authors when they’re writing briefs is, would your uncle Bob understand what you’re writing here, what you’re saying here? Um, so in terms of writing style, these audiences are important to keep in mind. Just a few words about brief structure. Paola is going to discuss a suggested approach for writing briefs for PRB and a checklist of things that they consider at PRB, but I thought I’d quickly provide some suggestions for how you might think about structuring a brief. And here I’ve just provided an example of our brief template that we use at the Syracuse University Center for Policy Research. Generally, policy briefs or research briefs, um, summarize 1 or 2 main findings or big picture takeaways. They’re not bogged down with a lot of detail or nuance. Is this 1 or 2 big things that you want your audience to know? They’re usually 2 to 4 pages. Sometimes they’re one page. They’re definitely not 20 pages. Briefs are, as they’re called, very brief. Um, they should provide a short intro of the problem and why your reader should care about this problem. Our briefs, we have the authors provide 1 or 2 main research findings, include visualizations if possible. Pictures are worth a lot. And also our briefs include implications for policy. And I know that that PR, er, PRB’s briefs do as well. Now, what you don’t see here is theory, a lit review, or a lengthy data or methods section for our briefs. We do include a very short data and methods section at the very end. Um, they’re very short, and we just sort of just describe what the data set is, the, the years that are represented, the sample size, and maybe a couple of sentences about variables. But then we direct the reader to a published journal article, if there’s one that exists from which the brief is, is summarizing findings.

So just show you a couple of examples from brief series here at SU. So, this first one is a brief that was led by my colleague here, Jennifer Karras Montes. You can see it’s just three pages. It provides a nice snappy title: Democratic erosion predicts rising deaths from drug poisoning and infectious disease. So, it gives the main takeaway right there in the title. It includes a couple of key findings so that if someone only read those key findings, they would know right away, uh, everything they need to know about that. The takeaways of this brief, you’ll see there’s a short introduction about the problem. Um, there are a couple of really easily understandable figures in here. And then at the very end, there is a section about what should be done about this problem. What are the policy implications? And in this section, we ask our authors to be concrete to identify the actors. Um, they’re not the place where you advocate for future research. They’re the place where you advocate for changes, for policy or practice. And I think you can be provocative here. Um, it’s okay that you didn’t study a specific policy. You’re the expert. You can speak to what you think the implications are of what you found.

Here’s just another quick example. This one is from our Center for Policy Research brief series. Again, similar sort of format. We have a snappy title, key findings, um, an easily understandable figure, a couple of sections with a little bit of information about the findings and then, um, what the policy implications are here. And so again, just notice the title and notice the headings. They provide statements about the key takeaways and the conclusions. I wanted to just quickly give you a couple of examples, um, of the difference between academic writing and public language. Okay. So, the way that we’re trained to write for journal articles is academics is not the way that we want to write for public audiences. In fact, I would actually say that I would prefer the writing for public audiences, even for academic journal articles. But, um, people might fight me on that. So, the academic text here is on the left, the public brief text is on the right. And this is from an article that, uh, coauthored with some colleagues here at SU. And you can see this lengthy academic text, um, we’re using technical language in it, things like controlling for confounders, estimated models, um, county and state level data, just all kinds of technical information that a public audience may not understand or care about. Compare that to the short end text from the brief, and we’ve condensed all of that academic language into a very short sentence that says what this brief does in very clear and simple language. It’s much shorter, it’s much simpler, and it still delivers the intent of the research. We also present visually results differently in academic publications versus briefs. So this is just an example of how we converted a complicated technical table of our findings into a simpler figure that tells the exact same story. The table, you’ll notice, uses terms like counterfactual and IMR, which is the infant mortality rate. The figure just shows different minimum wage levels and number of infant lives saved at each different level of minimum wage, so it provides the same information but in a simpler format.

This is a similar example from a paper in a brief written by Andrew London. Another one of my colleagues here at SU. And this table shows a lot of numbers with various symbols. This is from his academic paper. There are odds ratios in here. There are confidence intervals and p values. Um, which is great. This is what we want for academic papers and this is what reviewers demand. But for the brief, the bar chart shows simple probabilities of the outcome. Much easier for a policymaker or reporter or for your Uncle Bob to understand and digest.

So I’ll finish up just by talking about some successes that we’ve experienced from our from our brief series. We’ve had lots of media attention from places like NPR and CBS News and New York Times and in many other outlets. Um, we’ve gotten attention from the public. So random readers will write in to our authors to thank them for writing the brief. We get a lot more of those than we get, like, the nasty emails. Those happen once in a while, too, depending on the topic and how controversial it is. But we get a lot more just random, you know, my daughter experiences this thing. Or thank you so much for writing about this. Or like, what do you think about what’s going on with this thing? And in my city, um, we’ve also had attention from policymakers. So one of our, our graduate students here in the Lerner Center, for example, wrote a brief a couple of summers ago that that ended up being shared with a staffer for a New York state senator here. Uh, and from that, our student was invited to testify at a New York State Senate subcommittee hearing on aging, which was really exciting for her. Of course, um, one of our Center affiliates has been asked to participate in congressional briefings and give Senate testimony as a result of her briefs on veteran food insecurity. And you never know when, when this kind of thing might happen. It doesn’t happen with all briefs, but I think it’s more likely to happen with briefs than with, with academic articles, because they’re so accessible and easily digestible and people can read them in a couple of minutes there.

Um, there are also unexpected invitations and benefits that come from, from writing briefs. And I’ll just give you an example from my own experience, one of the very first briefs I ever wrote was for the Carsey School of Public Policy at University of New Hampshire, and it was on rural urban differences and adolescent opioid misuse. Now, that brief was based on a peer reviewed, published journal article. So I had the article published, and then one of my colleagues, Ken Johnson at Carsey School, said, you know, why don’t you turn this into a brief? He, he had done a lot of these and had a lot of success. So I wrote this brief. They published it through the Carsey School. And then that led to an invitation to attend a conference at the United Nations Office on Drugs and Crime in Vienna, Austria. Like, these people paid for me to fly to Vienna to give a presentation on this, this topic that I was doing research on, not because they found my academic journal article even though it existed, but because they found my brief. Um, so it was, you know, a really exciting opportunity this, you know, working class kid from rural upstate New York gets to go to Vienna, Austria, which was super cool. And I’ve had similar experiences from other briefs. So I wrote a brief while it was at Penn State on, uh, deaths of despair and support for Trump in the 2016 presidential election. And that led to a lot of media attention. But it also led to, um, this research director from this organization called the Institute for New Economic Thinking calling me up and saying, we want to give you some grant money to study this topic more. It’s, like, unheard of. It doesn’t happen. People don’t just call you and say, we want to give you money. But, but he did. And in addition to, you know, that that grant that I got to conduct more research on that topic, that organization also paid for me to, um, to go to Trento, Italy, and to Edinburgh, Scotland, to give presentations on this topic.

So again, you never know when these things are going to happen. Um, it depends a lot on the topic. It depends on who sees your brief. But I think that these types of opportunities on anticipated benefits are more likely to happen when you’re writing in a style that’s accessible for people outside of academia. So I’ll just leave you here with a couple of examples of other media coverage from some of our Lerner Center briefs, and I’ll go ahead and turn this over to Beth. Thank you.

Beth Jarosz: Thank you. Take me a minute to switch sharing screen. And we did this into our run. So, if you can’t see my slides, please let me know. I’ll assume silence means it’s okay. Um, and Shannon described there being a barrier between research and sort of the wider public, whether it’s policymakers or the public or journalists, and I’m going to describe it as a gap. But, essentially, we’re talking about the same problem. And I think I wanted to start with, um, you know, a focus on public policy specifically because most of my career has been in informing elected officials and policymakers about data so that they can make good decisions.

So I’m going to focus a little bit on that policy piece. And when I say public policy, I mean a set of actions, plans, laws, behaviors that are adopted by a government and that can be enacted through things like agency guidance or court decisions, executive orders, funding priorities, policy documents, laws, legislation, rules, regulations and so on. So that’s the angle I’m going to take. In talking about that, the really good news is that evidence can matter. Um, and as Sutcliffe said in 2005, the bad news is that often it does not. Um, and so let’s talk about some of the reasons why that gap exists.

Um, there is a deep communication gap. And I think a piece of it is different languages and different skill sets. And I’ll talk about that. But part is also that stereotypes are part of the problem. Um, so before I go on to the next slide, I want to ask each of you to take a moment and picture a policymaker. Think about the words or the phrases or the sort of emotions that come to mind when you think of someone who’s in elected office. And, and when we have asked this in the past, um, we get things like that they have very limited perspective, that they distrust research. Or if people are feeling less generous, that policymakers don’t understand research and that they are the ones who are responsible for digging up evidence and data to inform their policymaking, that their actions aren’t evidence based, and all of these have the sort of undercurrent of that policymakers are partisan. Um, which may be true in some cases, but in my career, I’ve worked with a lot of elected officials. And even when we don’t necessarily agree on policy or policy ways of achieving things, um, I think that there is a lot more, uh, appetite for having evidence informed public policy than I think sometimes they get credit for. And of course, policymakers may have stereotypes about researchers. Things like excessive use of technical jargon, um, researchers and journal articles, in particular, being very general and theoretical rather than the sort of real world or real problems that policymakers are dealing with day to day. I use if you can’t see, I use real problems, in sort of air quotes, but that that is seen as a gap between the two worlds and that researchers tend to avoid policy. I know those of us who are in the research world, um, we don’t want to assume causality when we’re when we’re looking at data where there’s a correlation. Um, and so therefore there can be an interest in shying away from policy implications when what reason, what policymakers need are those policy implications or implementations. And sort of the summary in one word of that, of that series of stereotypes is sort of the tower piece.

And all of that said, it is possible to bridge the gap between researchers and policymakers. And I’ve got a couple of practical examples of how to do that. Um, longer term and sort of fodder, perhaps, for a different workshop is thinking about that research uptake and engaging policymakers up front. Um, but what we’re going to do today, just in the interest of time, is focus on that third piece about communicating strategically. And if you take nothing else away from what I say today, I would say: assume competence, but not expertise. So assume that the person who’s going to be reading it is smart, but that they’re not using the same terminology. They don’t have the same depth of knowledge about the theory. And what their goal is, is to be educated in order to make good policy decisions.

So how do we do that? A couple of a couple of tips are to use clear and concise language and avoid jargon. Um, and what I’m going to, uh, offer to all of you is an activity. I know we’re going to take Q&A at the end, but if in the chat you could type some jargony terms that you use. Maybe there’s a term that’s very specific to your research. And those of us who are here can start to give you alternatives, but we can be your sort of live thesaurus. So if you have a term like etiology, um, maybe we would respond with the cause of disease and use that phrase instead. Um, if you regularly use a phrase like externalizing behavior, um, it could be aggressive, impulsive, or antisocial behavior. Replace it with, um, so thinking sort of about the jargon that we use can be challenging, um, but one of the tips here is write what you would write academically and then go back and, try and go back and use a thesaurus and sort of work those words back out again so that your work is more accessible to a policy audience, like, so, um, Go ahead and type those. If there’s a key, a term, a jargony term that you use that’s really important to your work, type that into the chat. And Mark, Paula, Diana, and maybe Shannon can live give you examples of what you could replace that with. A couple of, a couple of suggestions coming into the chat. So, I will let people keep working on that and move on to the next sort of two, uh, tips for work for bridging that research to policy gap. And it speaks directly to issues that policymakers care about and provide information that allows them to feel confident taking action. I’ve grouped these two together, um, because, you know, we, we as researchers might think there’s a really compelling arc about sort of the, the life-saving implications of an investment or the, the sort of social, emotional well-being of a particular marginalized group is the most important thing. But you need to know your audience. And so if, if you’re talking to a set of policymakers who, what they’re going to care about most is the budget implications of something or the fiscal impact or whether or not it brings jobs to their community, it is okay to make that the primary selling point when you’re making your policy case. It’s not pandering. It’s not disingenuous. It’s meeting a person where they are with the issue they care about.

You can and think, think about one of the more polarized issues, you know, uh, diversity, equity and inclusion. I think most of the people on this call probably care very deeply about that. But if you start out with that in a talk with someone who has been sort of socialized to resist, that they might not hear anything else that you’re going to say. So maybe start talking about, more generally, human interest, maybe talk about fiscal impact, and then you can sort of lead into those other issues, um, that might have been more sensitive before you built on that report. Just, and in terms of providing information that helps them feel confident taking action, give them data that they know the sample size is big enough. You know you’re not going to put a whole literature review in there, but you can signal things like a wide body of research also finds that this policy matters, um, you know, or study after study shows that if you do X, Y will happen. Um, you don’t have to do a full lit review to signal that they can feel confident that if they take this policy action, there’s going to be an outcome at the end that they expect.

And then, last but not least, um, propose with that solution is, and Shannon alluded to this when she did her overview. What is that concrete action step that they can take? Is it expanding a program? Is it making a budgetary change? Is it funding, um, additional health care services? Make it clear what the ask is in your writing and what the outcome is going. And so with that, I am going to turn it over to Paola to give you some specifics about how to write a brief working in those cases that I’ve talked about in terms of adding some more.

Paola Scommegna: Thanks, Beth. What I’m going to do is share some very specific techniques, um, that we use at PRB so you can recognize them and really understand the reading, the reasons behind them. And the first thing I want to share is it’s crucial to understand the, the differences between academic and journalistic writing. Academic writing, um, builds to a conclusion, starts with background, findings, and the conclusion is at the end. Next slide. But journalistic writing turns that format on its head. It’s called the inverted pyramid, and the most important information is shared first. Generally, that’s the conclusion. And then additional evidence and background comes later. And this format is used in newspapers, but also in writing for the web and policy memos. And this is what people are very used to reading. So as you begin writing for non-scientists and are aiming to communicate in a non-technical way, I would almost I would encourage you to go sit in a different desk or have a picture of your audience there so that you can think of this totally different way of communicating. And next slide. Oops.

Beth Jarosz: But I apologize. I have no idea what just happened to my computer.

Paola Scommegna: All right, well, the next one is, is on, um, writing headlines, and, um, let’s see if we can get to it. There. There we go. Okay, so these are some tips on writing headlines. It’s the first thing that you’ll do, and what we suggest is you state the main finding clearly like a newspaper headline. You may describe the action needed. You may aim for about 20 words, and it must have a verb. So, next slide, will give you some examples. And, and these examples are from recent population research. And what I’ve done is I’ve highlighted some of the verbs in red.

So you can see that these have verbs, and there’s action here. The first one: U.S. Teenage Births Hit Record Lows and Could Drop Further if Contraceptives Were More Accessible. It outlines the findings of the research, and it also implies the implications of the research. The next one was on, um, describes a natural experiment: When High Schools Moved Start Times to After 8:30 a.m., Attendance and Test Scores Rose. Um. I, very. The main message is right there. The third one is, um, looks at some pilot studies or small-scale research on, um, and the finding is: Taxes and Health Warning Labels on Sugary Beverages May Help Limit Consumption and Improve Health.

Um, next slide. And so the next thing we suggest is you begin writing with a summary of the main message. Now, Shannon shared how you can break that into three bullet points. Um, and, and, and that works quite well. And what we suggest is try to get it in the first paragraph. Um, clearly state the main problem or issue. Summarize your main research findings. Name the implications for policymakers and these three things together. Answer what we call with each other the “so what?” question. Why should people care about your research? Why should they be interested in what you found?

Um, next slide. So, this is some research out of Penn State that does that in the first two sentences. Um, the main finding of the research is the first section. The first sentence, Children in households that receive federal rental assistance are healthier and miss less school due to illness than those whose households are waiting for help. The research is summarized there. The second sentence, however: Up to 75% of renters who need federal housing assistance, including public housing or rental vouchers, don’t receive it. So the problem, the issue, the why people should care, is right there in the second sentence.

Next slide. So, here are some style tips to keep in mind. We talked about jargon with Beth, that, be conversational, and one way to do that is once you’ve written something, is to read it out loud and make sure it sounds like how you speak. The second thing is to define acronyms and technical terms. For example, if you write on the EitC, you need to say “earned income tax credit,” and then in, include a few words to explain what that is: lower, middle and lower income workers tax bills. Um, and that’s certainly how you would talk with someone who isn’t familiar with the acronyms that you use often.

Third, um, write in first person. I. I did this. We investigated this. And that will help you use active voice rather than passive voice. So, you would say, “we surveyed a representative sample,” rather than “a representative sample was surveyed.” And the reason we’re so fussy about passive voice is that it’s not conversational. It takes all the action out and the actor is unclear. And so it’s something we strive to avoid in the, the things we publish.

Finally, insert citations as numbered end notes. You saw that in the pieces Shannon shared with you, and you’ll see it in the pieces on the PRB website as well.

Next slide. Um, subheads. What are they, and why use them? Um, they’re descriptive phrases with a verb, and they’re really important. They break up the text. Highlight the main points for a reader who’s skimming, and research shows that many of us are skimming, particularly when we’re reading online. It. They reinforce the main message and they provide signposting. They signal to the reader what to expect in the text in the following section.

So, next slide. So what I did here was I pulled some subheads out of a brief so you could see them separate from the text that follows them, and can see how they summarize the main messages. Um, and this piece was on parental incarceration and its impacts. Parental Incarceration Is Widespread and Taking a Severe Toll on Children’s Lives. When a Parent Is Incarcerated, Children Are More Likely to Develop Behavior Problems, Face Homelessness, and Experience Harsh Parenting. Those are the research findings, in brief. The third subhead, um, points toward the action. The policy implications: Screen Students for Parental Incarceration, Rethink Sentencing Policies. So, it’s a succinct way to communicate your, your findings and, and the main message of a piece and keep the reader going through your piece, even if they have a tendency to skim. Um.

Next slide. And now, um, finally, I have some advice on data and graphics from PB. We find that bar charts and maps are much better than tables. We aim for no more than 8 to 10 data points. The title should be non-technical and have a verb like a headline. Xs and Y axes is clearly labeled. Use whole numbers if possible. And next is a sample of a PRB figure in PRB style. And the first thing I want you to see is that the, the main title is in more conversational, less technical style. Female, White, and Highly Educated Older Adults Were Most Likely to Feel Lonelier During the Pandemic. But below it, we include a much more technically accurate description for people who might want to know more specific things. So that is there, too. Um, the, um, numbers are whole numbers. The axes are labeled. And look what we’ve done here with the colors. They are designed to help you, uh, help a reader look at what we want them to focus on. So the first two bars are age, the second two in another color or gender. The third are, um, race/ethnicity, and the fourth are related to education. So, the colors work to focus the communication as well. So, I’ll stop here and pass it over to Mark.

Mark Mather: Right. Thank you, Paola. I wanted to end just by talking a little bit about how PRB can help, what we’re, what we’re trying to do to, um, help you write your own research briefs. And so the last thing I wanted to mention in this, uh, in today’s presentation is that we have a, a new research brief series with the Association of Population Centers where we’re helping researchers. Uh, well, there’s two different options. Uh, one is that you draft a research brief, and we can assist at PRB with editing and production of that brief. Or if you prefer, we can draft a brief, a research brief on your behalf. The, um, we’re aiming for, for about a thousand words for these briefs, which is pretty typical. Uh, we try to include some simple interactive charts, and we’ll publish these, uh, materials on previous websites and share them through social media. And Lillian, you can see, just put in a link in the chat here. So this is where you can find a sample template that’s available. It shows you, uh, the basic structure for one of these briefs and as well as provide an example. And then there’s also a short online form that you can fill out if you would like to have assistance. Lillian, just put that in the chat as well. If you don’t want to fill out the form, you don’t have to. You can just send us an email and we’ll be sure to respond to you. Um, there’s no cost to you for this work. The only requirement is that the topic really needs to be related to demography and/or reproductive health and population health topics.

So, in the next slide, I just wanted to provide a list of some of the new and forthcoming research briefs that we have at PRB. The first three are currently available on our website, whereas the other, I guess five of them, are currently in production. So those have been drafted and they’re in the process of being copyedited. And just so you know, it does take a little bit of time to produce these. There’s a, you know, we want to make sure we get the data right. So there’s a fair amount of back and forth with the researcher. And then it goes to our communications team for copyediting. So, the whole process can take, um, sometimes 5 or 6 weeks, sometimes a little bit longer than that depending on people’s schedules. And you can see that these briefs are on a wide range of topics. Um, we’ve got briefs on, recent briefs on marriage, child care, coastal hazards, and gender norms.

And then I thought I’d end the next slide. Just, um. I think there’s one slide before this one. Beth. There is not. So yeah, you can just go to the next slide. But I don’t know what happened to this, the intervening slide. But, um, I thought I’d end with this because, um, this is an example where PRB wrote a research brief and, um, it ended up being picked up for a maternal mortality awareness campaign last year. And it’s, it’s, so it started with a research brief that Paola had written, and we’re really proud of this one, because it took a lot of work to, um, to work with the advocates who were organizing this campaign. There was a lot of back and forth to make sure that they were representing the NICHD-funded research. So we wanted to make sure that everything was, was accurate. Um, and, you know, not everything that we publish gets a lot of attention. But if you keep working at this, you’ll find that, um, you can have an impact. And again, um, Lillian has just shared the link to this, uh, this brief and the related materials on our website, and I think I will stop there, and we can open it up for questions.

Diana Elliott, moderator: Right. Um, so. Just to remember, as part of the Q&A, um, we’re going to ask people to use the raise hand feature and then to jump in and ask their questions when they have them. Um, raise hand feature is at the bottom as part of the reactions, um, tab at the bottom of Zoom. Um, but we have a couple of, of questions that have come in. Oh, great. Alex, Kaylee, I see your questions. I’m going to ask the ones in the chat, and then we’ll turn to Alex and then Kaylee for their questions. So, we had one question come in through the chat, which is, what is the optimal timing for composing and publishing a research brief to mitigate potential copyright issues with journal article publication. Anyone want to jump in and, and speak to that one?

Shannon Monnat: I can, um. I suppose because we publish these briefs all the time, we don’t have any problems with, with copyright, um, concerns. And this is because you’re not actually reproducing the journal article. You’re summarizing the findings from that paper, if you have one. Um, and you are not copying and pasting the figures, for example, from the article, you know, we’re reproducing the figures to be more inclined for a public audience anyway, it’s your work. So there’s no, there are no copyright infringement concerns in terms of the best timing. If these are briefs that you want to pair up with an academic journal article, and for example, you want to link the journal article into the brief which, which I would recommend, um, I would suggest drafting the brief after you’ve gotten a revise and resubmit on your paper, or it’s pretty clear that it’s going to be accepted. Maybe you’ve gotten a conditional acceptance to have it ready to go so that once the, you know, you’re sending the proofs back to the journal, um, you have this brief done, and all you’re really waiting for at that point is the link from the journal article that you can embed into the brief. But if for some reason you don’t do that, that’s not to say that you can’t publish a brief after the article is already out. Um, this happens a lot with our authors, where they have an article that’s come out, they decide they want to write a brief. It’s targeted to a different audience. So it’s not like you’re missing out on anything if you don’t have the brief done right away. That’s, that’s my $0.02 on that.

Diana Elliott, moderator: Thanks, Shannon. Um, I’ll jump to the next question, um, which is, what platforms have you been most successful with reaching different audiences?

Beth Jarosz: I can, I can probably take a first crack at that. And I think we all probably have different perspectives. Um. I have found two things to be particularly helpful. One is social media, I’m assuming this is social media platforms, um, X before it became a terrible place to be. It was very effective for communicating with journalists and sharing information out. Um, I also am in the, the sort of unique position of I regularly present work to elected officials because of some work I do here in California. So I’ve got, like, a very direct line here that I don’t think counts. Um, but LinkedIn, weirdly, can be a good place because you’ve got an audience that is, uh, sort of issue focused, can be a really good platform to share. Um, and outside of that, one-on-one communications, you know that nothing—I know we’re talking about writing for these audiences, but, but nothing really beats building a relationship with whether it’s a policymaker. And again, I kind of mentioned this in the beginning to think about how to engage policymakers early on. If what you really want to do is policy change, start building those relationships, personal relationships, early on. Same thing goes with journalists that nothing beats knowing the person on the other end of the email.

Diana Elliott, moderator: Anyone else want to chime in on that one?

Shannon Monnat: Our briefs are indexed in Google, and I presume yours are as well. And actually, most of our hits come from that, from people doing Google searches. So we, we, we post the briefs and all the outlets that Beth mentioned. And, you know, we’ll get hits on those once in a while. Um, but when you look at the, the download statistics, most of it is from people doing Google searches because those terms kind of pop up at the top. Um, so, you know, just making sure you’re publishing with a brief series that does index on Google is a good strategy.

Mark Mather: I’ll just add, it’s, it’s good to have some, it’s okay to publish these in PDF format. But um, if you do that, it’s also good to have the short blurb so that people can find it easily, so they don’t have to take that extra step of opening up a PDF. I mean, that’s what social media is all about to you want to get people to see it first, and then if they if you get their interest, then they might click to see the whole thing in a PDF format. But as a general rule, we do now publish all of our briefs in HTML format so that they’re easier to search and easier to find.

Diana Elliott, moderator: Right. I think I’ll switch to, uh, folks with their raised hands. Alex, do you want to chime in and ask your question?

Alex: Sure. Hi everyone, thanks for holding this webinar. It’s been great so far. My question is related to, I think the question was just answered, but I wanted to know basically like, you write a brief, how does it get into the hands of a journalist or, or one of these people? And I understand there’s these research series, but do you contact journalists as well? Obviously, like you use your social media presence, but are there any other tricks to kind of get it in front of people? Um, and, and yeah.

Diana Elliott, moderator: Paola, I wonder if you have some thoughts on this.

Paola Scommegna: Um, it really helps that they’re, um, indexed in Google so that when a journalist is writing on your topic and they do a search, they find you. But I also follow who’s writing about the things I’m writing about in, um, in the national media. And I will send them something, um, through the, the addresses they provide, say, the aging reporter at the New York Times. I, I do send them things. Yeah. Usually, I’ll compliment them on something they’ve written and then saying, you might be interested in this.

Beth Jarosz: So excellent strategy. The only thing I would add to that is that if there’s a particular writer who you really hope will take up the article, if you can send them an early draft before it’s live and they feel like they have an exclusive, they’re more likely to respond favorably.

Diana Elliott, moderator: Not always a guarantee that they will write, though, and sometimes that’s very disappointing. Um, but they’re also, they’ve got other competing demands or editors who have opinions as well. So, um. Anyone else want to chime in to that or should I switch to Kaylee? All right. Let me switch to Kaylee’s question. Kaylee, do you want to chime in? And I’m sorry if I’m not pronouncing your name correctly.

Kaylee: Nope. That was spot on. Um, thank you all for your presentations today. It’s been incredibly helpful. I’ve just been taking notes frantically. So, my question is, um, pretty demography specific, but one of the things that I would love to hear about your experiences with or best practices is in terms of, um, when you’re trying to express uncertainty with your results. So, I’m thinking about, in the case of, for example, like demographic forecasting, um, or modeling in that way where, you know, you might have a point estimate, but what you really want to convey is like, here’s the possible range of outcomes. Um, how do you ,how do you manage the, the balance between like being honest to what your results are actually telling you versus wanting to tell this compelling story?

Beth Jarosz: This is, I, this is what I do all the time. So a, a big piece of my work is, is doing forecasting work for regional governments in California and um. I would say, where I started my career, point estimates were the only thing that people wanted to talk about. And now, particularly in the post-COVID context, there’s an appetite and an interest for having uncertainty ranges. Um, and I have had no problem just being really clear about that. Like, here’s the point estimate we’re going to use. And then here’s how widely it might diverge at the end. And um, really appreciated and no challenges with, um, sort of understanding among that policy audience.

Diana Elliott, moderator: Shannon, do you have anything to add based on your experience?

Shannon Monnat: Um, there, there’s a sociologist who wrote a journal article a few years ago with the title that said “eff nuance.” And the point was like, you’re going to get your point across much more clearly if you provide, you know, like not all kinds of little ifs, ands, or buts about what you’re trying to present, but you just say it straight. Um, having said that, I agree with Beth that it’s perfectly reasonable to just provide a range to say, you know, like our estimates suggest this is going to be the number. But because this type of projection can be uncertain, the range might be between x and x. And just say it like that. But what I would avoid is, um, all kinds of details that are things like, well, under this conditions, this thing happens, but only for this group and only on like Mondays. Right. So, um, then you have way too much detail and nobody really knows what to do about it.

Beth Jarosz: Yes to all of that.

Diana Elliott, moderator: Do we have any other questions from the audience? I don’t see any other raised hands. Um, and there was another question that was asked, but I believe it was already answered through the course. Yeah. Winnie, would you like to go ahead and ask your question?

Winnie: Yes. Thank you. So I wanted to know, can I, can a policy brief be publicly based on someone else’s research and not necessarily my own?

Mark Mather: Wait, you’re talking about, um, summarizing someone else’s research in a brief.

Winnie: That’s right. So, uh, without necessarily being the first author or whatever, like, you just find an interesting research and then you want to turn it into a book.

Mark Mather: Yeah, absolutely. I think it’s, it’s good to, um, you know, the first thing you would do is probably just reach out to that person to let them know that you’re starting this process and because they will be important, uh, an important reviewer, we always send out our we we’re always writing briefs based on other people’s research. And, um, we send it out to them to make sure that we’re getting it right. And they like they also like to have, uh, they like to know when it, when it’s being published to so that, uh, in case somebody does come across that they’re not kind of taken by surprise when they get a call, um, that they, you know, a journalist just found this, this brief, and they want to talk to somebody about it.

Winnie: Great. Thank you.

Diana Elliott, moderator: Jan [German pronunciation]. It’s good to see you.

Jan: Good to see you, too. Thanks for the great presentations. Um, I was wondering if any of you had any, any experience with using a, AI to get a policy brief started, and if that is helpful.

Shannon Monnat: No, but that’s a great idea. I think I am. Part of me wonders. You know what I would spit back if you put in, you know, the abstract of a journal article and said, please simplify this using non-technical language. It might spit back something that could get you started. Um, and then once you’re started, it’s easier to, to proceed because it would probably identify what the most important parts of that abstract were for you. It’s worth giving it a shot.

Mark Mather: I agree. And there is one of our colleagues at PRB is using, I think it’s called a PDF or something, where you can upload a paper and ask it to pull out the key points. You can query AI for whatever you want to know about that paper. And I do think in some years’ time, you know, this business of writing my technical research briefs, we might be out of business when AI becomes much better at this. For the time being, I don’t think there, the, you know, I think that people can still tell the difference between one of Paola’s briefs and something that ChatGPT created, but who knows in ten years.

Diana Elliott, moderator: I still think there’s going to be a place for people, technical people, to review things. Well, I hold on to that, that hope for the future. Um, so, uh, I wonder if we have any other questions. Um. If not, I’d like to just sort of turn it back to the panel, and we’ve heard a few, I’d like to leave this on an uplifting note, right. We’ve heard a few, sort of tales, of success stories. I’m wondering if, if people want to chime in with some other success stories, to kind of inspire folks to write their first policy brief.

Beth Jarosz: You want that from the panelists? Or do you want anyone who’s participating to also share if they’re interested? Right, I think.

Diana Elliott, moderator: Yeah, I was thinking of the panelists, but yeah, we can absolutely open it up if if other people have success stories.

Beth Jarosz: Um, I would say in this sort of relates to the forecast question that was asked earlier. Uh, there, I wrote a brief about population decline, um, in the United States, that population growth has slowed dramatically in the wake of the pandemic, um, had been slowing leading up to that. And, you know, new Census Bureau projections show that we’re going to reach an inflection point at some point, certainly in the next several decades, if not in the next couple. So, I wrote a blog summarizing that, and a, a journalist from The Economist reached out and said, hey, I saw this blog you wrote. Would you be willing to talk about population change? So, it’s that, um, not every article you write, not every blog, not every policy brief, not every research brief is going to get picked up, but it’s having that sort of base of articles that are out there that gets you into the universe of the journalists that might be interested or the policymakers going to be interested. And then that builds. Now that journalist knows that, you know, I’m a resource for issues about population change and, and may come back to that again, you know, a year from.

Diana Elliott, moderator: And you developed a budding relationship with that journalist too, which is also really helpful. So, when Beth has something new out, she’ll send it to that journalist. And, and it helps. Um, Shannon, you had some great success stories. Not many people get to travel to such fabulous places because of their research. Um, I’m wondering if you have anything else to share on that front.

Shannon Monnat: This is the reason I keep writing briefs. I’m like, who’s going to send me on a trip next? Oh, it’s, uh, it’s so random, you know, like, I, I, um, I probably shouldn’t say it’s the reason I keep writing briefs. Because you shouldn’t write the briefs to get this kind of attention, because most often it doesn’t happen that way. So this idea that you’re building up this portfolio, that you become the go to person on this topic, that’s more likely to happen if your research is out there in the public, easily findable, not behind a paywall. When a reporter is looking for someone who’s an expert on X, you know, population projections for Beth or, you know, rural mortality. And in my case, they’re going to be more likely to find me through a brief than through a, through a journal article. And then these kinds of things happen, which can be exciting. And then you have to start saying no to things.

Mark Mather: I was just going to quickly use Paola again as an example because she, she drafted an article, I think it was 2019, Paola, the one on measuring longevity. So it’s pre-COVID, and it’s just an example of uh, if you, if you just keep producing these things, some of them will become very, uh, widely used. So when COVID, uh, happened the following year, that article started to get a ton of attention and ended up with several hundred thousand views in the first six months of 2020. So, um, so sometimes you might not get attention when you write the brief, but when certain current event, uh, policy, you know, issue comes around, it will start to get attention.

Paola Scommegna: And Mark, I was thinking of something you worked on a related to the burden renters feel or experience, and you gave data for every state, I think. And the governor of New York kept mentioning it, it just keeps turning up. Um, so there’s something you did a while back that’s driving policy.

Diana Elliott, moderator: Right. Um, hopefully that gives a little bit of inspiration for everyone on the call to ,to write, um, a policy brief, whether using AI or not. We support this completely. Um, and we can’t wait to read your briefs or to help you out with that, as Mark referenced before. So, just a reminder that this webinar has been recorded and there are slides and that link for the recording will be sent out afterwards. And I want to just thank everyone who participated who chimed in. Special thanks to Mark, Shannon, Beth, and Paola, um, for their terrific presentations and we look forward to being in touch.

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Transcript

Jennifer Gerson, The 19th News, moderator: I just want to welcome everyone. I am Jennifer Gerson. I’m a reporter at the 19th, an independent nonprofit newsroom reporting at the intersection of gender, politics, and policy. And I just want to thank you all for joining us today. I’m really excited about this webinar, which is being recorded, where you’ll learn more about the Population Reference Bureau’s new report, Losing More Ground Revisiting Young Women’s Well-Being Across Generations.

First, Diana Elliott, who’s vice president of US programs at PRB, and Martha Sanchez, the director of health care policy and advocacy at Young Invincibles, will introduce their organizations and why they came together to present this webinar today. Next, we’ll review the report’s key findings. And then lastly, I’ll introduce our very impressive panel of experts and begin the Q&A.

If you experience any technical issues, please comment in the chat and we will try to help you resolve that as quickly as possible. And now I’d like to toss things over to Diana and Martha.

Diana Elliott, PRB: Thank you, Jennifer. And thank you also to everyone who’s joining us today. PRB is a nonpartisan, not-for-profit research organization focused on improving people’s health and well-being through evidence-based policies and practices.

When we started the research for our new report, Losing More Ground, we knew from our previous 2017 report that young women’s well-being had stalled, but we didn’t expect the declines we see in the findings. Through original data analysis, we compare women ages 25 to 34, or the Millennial generation to same aged women of the Gen X, Baby Boom, and Silent generations. We find that generational progress has declined even further for millennial women in the intervening years. While Gen Z is not yet of age to include in our overall index, our analysis finds that teen girls ages 15 to 19 show early signs of both progress and decline relative to prior generations.

Much has changed since our original report. Since 2017, the US has had two new presidents, two impeachment proceedings for Supreme Court justices, widespread social and political movements, reckoning with racial disparities and health, safety and opportunities, the overturning of federal reproductive health protections, and the COVID-19 pandemic, to name only a few changes. Our findings show that women’s generational progress has been impacted by how the world has changed.

The findings in Losing More Ground have serious implications for the young women of today and tomorrow. And when we thought of how we could best draw attention to them, it was important to us to partner with an organization dedicated to young people’s well-being. We are pleased to co-host this event with Young Invincibles, and for Martha Sanchez to say a few words about this organization.

Martha Sanchez, Young Invincibles: Thank you. Diana. I’m Martha Sanchez, the director of health policy and advocacy at Young Invincibles. We are a national nonprofit organization dedicated to the economic well-being and empowerment of young adults ages 18 to 34 when it comes to their access to higher education, health care, workforce and finance opportunities, and civic engagement, all of which are issues that are touched by this report.

Um, so we are very excited and thankful to be here and grateful for everyone who is joining, especially the young adults who are highlighted in this report. I’m sure you all have plenty to say as well and contribute to this discussion, and we look forward to hearing your ideas on how we can move things in the right direction. Thank you.

Jennifer Gerson, The 19th News, moderator: And now I believe, uh, Sarah Shrigley, who’s the research analyst at PRB, is going to share some of the key findings from the report.

Sara Srygley, PRB: Thank you, Diana. Thank you, Martha. Thank you, Jennifer, and thank you all for being here today. It’s something of a tradition, debates between the generations about who has had it worse. And this conversation comes around so reliably with each new generation that we may not always take it very seriously. But when young women today say that life is harder than it used to be, we now have the data to prove it.

The promise of generational progress has been broken for millennial women, and in many ways, Gen Z girls are already seeing similar trends as they near young adulthood. You can see in this figure that while Baby Boom women saw a sharp rise in overall well-being relative to the silent generation, their progress was more slight. For Gen X, it plateaued briefly for Millennials in 2017 and is now notably in decline.

So what’s happening to millennial women?

Despite all their efforts, today’s young women are faring worse as serious threats to their health and safety are driving this overall decline in their well-being. But let’s start with where things are going. Well. Millennial women graduate high school and attain bachelor’s degrees at rates far outpacing previous generations, making them more educated than at any point since at least the Silent Generation.

And Millennial women aren’t just more educated than ever. They’re also working hard to make gains in their professional lives. They’re more represented in high-earning and often competitive STEM fields and among business owners today than in previous generations.

And the gender wage gap has narrowed from one generation to the next, although it does still persist, as you can see here. It’s even more pronounced between women of color and white men.

When it comes to political representation, the share of women holding office in state and congressional legislation has increased with every generation. As Gen Z comes of age, we’re beginning to see a whole new generation taking a seat at the table of political leadership and civic engagement.

And young women today are also avoiding key risk factors to their health, like cigarette smoking, teen pregnancy at a higher rate than peers in previous generations.

So all of these data tell the story of a generation working hard to obtain their personal and professional goals. And despite all this progress and more, which is detailed in our report, why are Millennial young women still faring worse overall when compared with their mothers’ and grandmothers’ generations?

A key part of this answer is difficult to accept: A young woman in the U.S. today, between the ages of 25 and 34, is more likely to die than at any point since at least the 1960s.

Maternal mortality rates have dramatically increased between Gen X and Millennial young women. In just a few years’ time, this rate climbed abruptly by nearly 60%. And women of color, particularly black women, are disproportionately impacted by these sharp increases.

And suicide rates have also risen, driven by increases for women of color. In fact, during the 2018 to 2021 time period, the suicide rate actually declined for white young women by about 6%. But disparities for women of color drove this overall pattern of worsening suicide rates.

Homicide rates, too, have taken an alarming turn for the worse, and there are racial disparities here as well. The increase has been particularly stark for Black young women, who are five times more likely to die by homicide than their white peers.

We’ve seen that young women today are doing many of the things they’ve been promised would lead to a better life, and these are things that worked in the past. Yet the evidence from our analysis shows that despite their best efforts, they still face very real challenges compared with previous generations in some of the most fundamental areas of life.

How we address these threats to millennial women’s well-being will set the stage for how Gen Z fairs as they reach their young adulthood, and whether they see a restoration of the promise of generational progress. Now I’ll turn things over to Jennifer to begin the Q&A.

Jennifer Gerson, The 19th News, moderator: Thank you so much, Sarah and Diana and Martha. I’m really excited to engage with the other members of our panel right now.

We are also joined today by Kara Brumfield, who is the Director of Income and Work supports at the Center for Law and Social Policy. And Doctor Jamelia Harris, Senior Director of Research at the Justice and Joy National Collaborative.

So I’m really excited to speak with you all and, um, about all the things that Sarah just shared with us. You know, when it comes to education, Sarah just talked about some real wins for Millennial women with high school dropout rates declining and bachelor’s degree attainment rising. But at the same time, we’re seeing overall well-being decline for this generation, both over the last few years and especially relative to other generations.

You know, Martha, I was wondering if you could start off for us. What do you make of knowing that more Millennial women are accessing more education, but still facing worse outcomes, especially when it comes to their health and mortality?

Martha Sanchez, Young Invincibles: Yeah. Thank you for this question. I think the report, um, highlighted, um, that it is still so important to attain higher education in this country. The average salary, uh, for a college diploma is around $61,000, compared to 21,000 for the high school diploma. Um, and so when I think about, though, the experiences of young Latinas like myself, um, and first generation, um, Latinas, um, I have to also consider the fact that many of these higher education institutions, really all of them were not built for us. And so the challenges that we face throughout these academic years, um, definitely influence, um, the health outcomes that we have throughout our higher education experience as well as afterwards when we graduate.

And we see that when it comes to our mental health as well as the financial outcomes, um, financially, even with a college degree, women earn less, um, than men. But women of color continue to earn much less than white woman or, um, white men. And so when you have these disparities, it’s going to affect our ability to build wealth, because we realize that we have to work ten times harder. Um, and even then do not really receive equality or equity when it comes to our earning potential and income.

But that also takes a toll on our mental health, because there were so many sacrifices made along the way from our parents and our family and ourselves to accomplish these goals, these milestones of college graduation, for example, that when we see the reality and when you face all of these challenges, um, it is very it definitely takes a toll on us. And I think an example of what we see on, on college campuses, uh, when it comes to mental health, you know, half of young adults 18 to 25 deal with, um, depression, depression or anxiety.

And in the report, it’s all young women. Um, for almost 40% of them deal with anxiety and loneliness. Um, but on college campuses, we don’t really have the resources. We don’t really have the counselors available. Um, the mental health resources. Why? I we are pushing for a federal designation of campuses that meet, um, a healthy mind standard of of providing resources to students, um, both when it comes to in-person or telehealth, uh, or peer to peer. Um, all of these resources would make a difference in their ability to actually cope with the challenges that before them, especially first generation Latinas and African American students, um, who need these, need these resources in order to actually thrive when it comes to higher education.

Jennifer Gerson, The 19th News, moderator: Thank you so much for that. You know, to kind of continue this, take this to the next step, just like you were talking about. Martha, when we look at indicators where Millennial women are doing worse, we saw some pretty stark contrast between outcomes for white women and outcomes for women of color. You know, especially oftentimes when it came for black women and native and indigenous women.

Doctor Harris, I was hoping you could tell us about what this data tells us about how we understand equity in this conversation when it comes to understanding outcomes, and what kind of policies do you think could really help address this gap we’re seeing?

Dr. Jamelia Harris, Justice and Joy National Collaborative: Absolutely. And first and foremost, I want to thank the report authors for intentionally centering, uh, disaggregate lens that, uh, presents the data across race, age, and gender. And, and as a researcher, I don’t take that for granted, as oftentimes we see that, uh, there is an incomplete story when we don’t have this disaggregate this, this aggregate lens that, uh, really helps us to understand the particular challenges faced by girls and women of color in society.

And, uh, I want to just start out with foregrounding that a lot of the patterns of inequity that we see reflected in the report, uh, are really connected to deep seated histories of racial and gender inequality that girls and women of color have been facing for centuries. Discriminatory policies. Institutional practices have created deep-seated inequities across sectors, including education, health, the criminal legal system. And so, uh, some of the data points that we see, uh, that really are highlighting and illuminating the inequities that women of color, uh, face can really be contextualized by understanding this history.

And so I did want to flag a few data points that for me as a Black woman, uh, were particularly stood out, stood out as concerns of equity for women and girls of color. Uh, one of them being that black women saw a 16% increase in suicide rates during this time period. We also saw that even while educational attainment and incarceration rates improved among young women, overall gaps persisted based on race and ethnicity. And I think that these gaps that we’re still seeing, uh, for women of color, particularly for Black women and Indigenous women, really point to how the compounding of oppression due to race, age, gender create unique barriers and challenges for women of color and these data points also really underscore the necessity of what Black feminist scholars have long been calling, uh, as a need for us to prioritize intersectional lenses into the ways that we are addressing our policy solutions.

And so what that means is that our analysis, our policy solutions, should put the people who are the most vulnerable to being harmed by systems and structures due to their location at the forefront, um, of the initiative. And just as we can’t see these inequities without a disaggregate lens, we also cannot address, uh, the specific challenges that women of color are facing without a lens that addresses their race, their age, their gender, and the compounding effect that that has on their experiences in society. And so I would say that while we have a long way, um, while we have, I have to acknowledge many of the strides that this report presents.

We still have a long way to go until this vision of racial and gender justice are actualized. But that work must come from, uh, intersectional and intergenerational policy solutions that are for fronting the people who are most harmed by these systems and structures.

Jennifer Gerson, The 19th News, moderator: Thank you so much, Doctor Harris. It’s really important context to keep really top of mind in this conversation today. You know, to move this even, you know, forward even more. We just, like you were saying, talking about health and mortality components that we just heard about in the data, especially in terms of this really jarring increase in maternal mortality rates, in the suicide rates for women of color.

You know, to the whole panel, I was hoping to hear from, you know, anyone who wants to jump in, what relationship you see between the increase and the maternal mortality rate, the increase in suicide rates and the increase in homicide rates among millennial women, and whether we need to think about all these things as separate issues or how related these things are, especially when we start to break down the racial divide we see in the data.

Cara Brumfield, The Center for Law and Social Policy: I’m happy to start. Um, I think one through line there is definitely, um, mental health. And we know that millennials face really unique, um, challenges, including economic challenges like coming to age and entering the workforce during a recession. Really oppressive levels of student loan debt, housing costs, job insecurity. Um, all of these things, uh, create a really stressful, um, stressful life. And that weighs on your mental health. Uh, we also know that domestic and intimate partner violence and gun violence both increased during the COVID-19 pandemic, as well as social isolation, which Martha also mentioned. Um, and those things, of course, have mental health implications as well.

Um, and we also know that Millennials are experiencing just, uh, a unique set of social pressures. Um, we have delayed life milestones, like having children. So we’re having children later in our lives, which makes having children, uh, more risky from a health perspective. Um, but we’re also facing the dual pressures of society to make a family and be educated and have a successful career despite the economic environment that makes all of those things really hard to do. Uh, and, uh, you know, we have data that shows that pregnant women, 18 to 44, since about 2014 have shown, uh, 30% increases in major depression, hypertension, type two diabetes.

All these things are risk factors for maternal mortality. Um, but we can’t talk about maternal mortality without talking about the experiences of women of color, um, and women experiencing poverty, but especially black women who face systemic barriers to high quality care. Doctors do not take Black women’s pain seriously. And the data shows that wealth is not a protective factor for Black women when it comes to maternal health and mortality. Um, and we’re not really going in the right direction. So, for example, right now in Mississippi, which is one of the most dangerous places to give birth in the U.S. Um, officials are making changes. Officials are sort of failing to make changes to Medicaid that would allow pregnant people more timely access to prenatal care. And we know that that early access to care is really critical for health outcomes.

Martha Sanchez, Young Invincibles: Um, and I can add to this as well. Um, when we look at where we are today, we see that, um, there are policies at the state and federal level that are actively dismantling our ability to have agency over our own bodies and make decisions over our own health care, whether that is by straight out, um, bans on abortion across the country, the overturning of Roe v. Wade, or by the fact that for many of us, we simply cannot afford our health care services, especially when it comes to mental health. Um, so, you know, there are multiple causes, um, and stressors that are affecting our mental health. Everything from these, uh, the, these policies and the lack of agency that we have over our bodies.

But then even when we take the most courageous steps someone can take, which is to ask for help when it comes to our mental health, we find that: A) we can’t afford it because who can really pay a $90 co-pay per session per week? That’s just not realistic financially. Um, and B) there are not enough, um, culturally competent mental health providers out there. And oftentimes insurance plans and companies get away with ghost directories. Um, which means that, you know, they’ll say that they have in-network providers within a 20-mile radius, and then you find out that actually they no longer take that insurers and no longer afford it.

Um, so we are really failing our women when it comes to protecting them, protecting their health, um, their ability to seek help, whether it’s reproductive care, abortion care or mental health.

Jennifer Gerson, The 19th News, moderator: Thank you so much, Martha and Cara. You know, while we’re kind of talking about these economic factors and the toll they can often play, I was hoping we can give some more context to folks on that.

And, Diana, I was wondering if you could tell us a little about what we’re seeing right now with kind of the state, you know, the state of the union of the economy. We saw poverty rates decrease during the pandemic, and they’ve recently bumped back up again at the same time, young women’s labor force participation is at an all-time high.

So, Diana, if you could just talk to us a little about what’s happened since the pandemic in terms of both women’s labor force participation and the poverty rates and the way you kind of saw that iterate in this data set.

Diana Elliott, PRB: Yeah. I mean, women’s labor force participation right now is at a high. Um, so, you know, I think it’s something on the order of 77.8% or so. Don’t hold me to that. Um, but it’s it’s at an all-time high right now, and or at least in recent memory. And one of the reasons for that is we have a really tight labor market right now. And, um, we have this scenario where employers are willing to be a little bit more flexible.

We don’t always have this situation, though, and certainly one of the things that holds us back in our in this country from women, particularly 25 to 34, from having even higher labor force participation, is our lack of a care structure, that we don’t have adequate supports for childcare in the way that other similar peer countries do is a problem, and we are at this critical juncture right now where funding and supports for child care that were there during the pandemic are about to disappear. And this means that certain subsidies that were in place that allowed, um, child care operations to continue and persist, um, may not be there in the very near future because it’s really expensive and hard to run a child care center without that extra support.

So we could see a situation where this might be the high point in women’s labor force participation. Um, and, you know, as we tie this in with poverty, um, there are certain subsidies that make childcare more possible for, for women who are, you know, on the lower end of the income ladder. And again, without those supports and structures, um, they don’t necessarily, you know, they might qualify, for example, for subsidies, but they might not always have slots in various, um, childcare centers.

So we’re about to experience a potential cliff in terms of what women’s labor force participation looks like and whether that can persist. So, um, at least for women in this 25 to 34 year old age group, um, we’re seeing all time highs. But I fear that those highs will not last without adequate supports.

Jennifer Gerson, The 19th News, moderator: That’s really important to keep in mind. You know, when we think about, um. This economic picture we’re in right now.

To Cara, I was hoping you could tell us a little bit about what helped drive down poverty during the pandemic, and what policies do you think could further bolster the winds. We were seeing for some women, in terms of the gender wage gap and employment to even more women, especially across these racial divides.

Cara Brumfield, The Center for Law and Social Policy: Yeah, absolutely. So, um. Something that made a huge impact on poverty during the pandemic, of course, is the American Rescue Plan. It played a huge role. It represented a huge investment in the well-being of our nation. And it really demonstrated that, uh, these kinds of investments are both possible and really impactful. And it made it even more clear and even more obvious how poverty really is a policy choice that we’re making.

We expanded access to Medicaid. Right now, we’re seeing the devastating of, uh, sort of impacts of unwinding those Medicaid provisions that were established during the pandemic, um, over 6 million, I don’t know the current number. I know it’s over 6 million people have already lost access to Medicaid. Um, we saw, uh, lower health care premiums, which is hugely important. We saw an eviction moratorium. Um, we saw relief payments that made a really big difference for a lot of people. We saw student loan debt relief, um, all of these things that are particularly impactful for people of color, people experiencing poverty, for women and for Millennials.

Uh, the American Rescue Plan Act also enhanced a child tax credit [CTC], which really, it helped slash poverty nearly in half. Um, a particular impact, obviously, on, um, families with young children, but also was really huge for people of color. Um, corporate lobbies helped kill the expanded CTC. Uh, at the same time, they were raking in record profits and often paying little to nothing in federal income taxes. Um. So I think that what we see is that we know what the policies are that help address poverty. It’s getting cash in hand to people who need it through things like tax credits, for example. It’s also bolstering our public benefits programs that help people access their basic needs, like food, health care and housing. Um, and we really need to be making those investments that have been proven to make a huge, significant difference.

Um, when it comes to sort of the, um, the wage, uh, gap, I think it’s important to remember that even as women are increasingly educated and increasingly entering the workforce, um, that when you think about it, um, sort of when you start to disaggregate it by race, you see that women of color are still disproportionately in those jobs that are the lowest paid, the jobs that have the most sort of hectic and unpredictable work schedules, uh, which makes it really challenging to have your health care or your child care needs met. Um, uh, so that has an impact on your ability to stay employed and to advance in your career. Um, and we know that given all of the student loan debt and how oppressive that has been, particularly for, for people of color, that those educational gains and those employment gains just aren’t paying off for folks the same way, um, that they might have expected them to.

Jennifer Gerson, The 19th News, moderator: Fantastic. Thank you so much, Cara. Uh, Sara, I have a question for you as well. I was hoping you could talk to us a little bit about what we’re seeing and what you’ve seen from your data about Gen Z and their political power right now. You know, you said Gen Z is really coming of age, taking a seat at the political table. What will this mean in terms of not just representation, but change, not just for that generation or kind of youngest voters, but for the millennial women ahead of them to.

Sara Srygley, PRB: That’s a great question. We know that millions of new Gen Z members will be eligible to vote before the 2024 election, so in pure numbers, the potential voting bloc for Gen Z and Millennials combined is actually poised to outnumber baby boom voters. What we don’t know is if they’ll vote. So that’s the potential voting bloc. But that doesn’t guarantee that they’ll vote. We also don’t know how they’ll vote. They certainly have the numbers to see what’s important to them represented and in policy and in election outcomes at all levels.

But what we really need to be focusing on is empowering that generation, empowering Gen Z, and empowering Millennial members of our society to feel like they can make a difference and to understand how to do that, how to become engaged in their communities, how to become politically and civically engaged so that they can use those numbers that they have and represent their interests on those larger stages.

Jennifer Gerson, The 19th News, moderator: Fantastic. And I’d like to do one more question to the panel as a whole before I ask for questions from our audience today, but I would love to just hear from you each right now. You know, one thing that really comes through in this data is the fact that there seems to be this bigger story about millennial women, and they are dying for a whole slew of different reasons. So I was wondering from where you all sit, how you’re thinking about what we can do to change this. What policy solutions are most needed right now to address how fatal it just is to be a young woman in America today? So if someone wants to jump in or I’ll pick on someone to start. Martha, you want to hop in?

Martha Sanchez, Young Invincibles: Yeah, I think, I mean, first we have to, um, work and fight for policies that protect women’s ability to make decisions over their own health care and their own bodies. Um, and I think, too, um, given what we’re seeing in terms of the increase in suicide rates, especially for women of color, we do need to reform, um, mental health.

Um, and the way that it is delivered in this country, mental health should not be treated as a specialty service 100% of the time. It should be a preventive care service. It should be as easy and as important as scheduling your annual physical to obtain mental health services from your provider. Um, and so that and that includes making at least the first three visits free. Um, under all private insurance plans. Um, and ensuring that we are changing the narrative of what it means to be healthy. Um, the same way that we look at social determinants of health, we have to look at the social determinants and economic determinants of mental health. So I think that’s where we have to focus on.

Jennifer Gerson, The 19th News, moderator: Doctor Harris or Cara, either. Oh, you both jumped in. Okay, here, I’ll pick. Dr. Harris, okay.

Dr. Jamelia Harris, Justice and Joy National Collaborative: Yes, we just unmute at the same time! So, yes, I spoke a little bit about just concerns around the data that is showing that Black women particularly are experiencing higher rates of suicide and something that, uh, our recent research we have been engaging has been looking at the impact of police violence on girls and gender expansive young, uh, folks of color. We found that particularly, uh, police violence has, uh, detrimental impact on the mental health of Black girls and gender expansive young people. And we are now, uh, recently releasing a report that’s looking at the impact of vicarious trauma.

So thinking about experiences of engaging with police violence through social media, um, and especially thinking about this unprecedented moment, uh, of the COVID-19 pandemic, in which many young people were socially isolated from their peers and their loved ones. And in order to stay connected to them, uh, they were engaging on social media and an all-time high that we are seeing that many young people have vocalize at one, uh, they are severely experiencing mental health issues as a result of the COVID-19 pandemic, and that two, police violence is a serious, uh, social health, uh, indicator of some of the challenges that they are experiencing with regard to mental health. And so I would say that, uh, one, I think that we really need to be talking about police violence as a global health, uh, related issue. And two, I think that we really need to be more intentional in thinking about the ways that we are engaging young folks in seeking solutions.

We recently, uh, had some conversations with young people and thinking about what their visions were for futures free from police violence, and they had incredible ideas and insights about ways that we can go about addressing police brutality. And to, to quote earlier, it was mentioned that, uh, young folks are now reaching the age in which they have political power and deserve a seat at the table. And I would say that we know that young folks have always, uh, really pushed for social, political justice in their communities, that they have always, even if they weren’t extended seats at the table.

To paraphrase the words of Shirley Chisholm, they brought their folding chairs, and they really can be the beacon of incredible change in their communities if we allow them, uh, to be a part of, of these spaces and allow them to be a part of seeking solutions to some of the challenges that we’re facing.

Cara Brumfield, The Center for Law and Social Policy: Yeah, I’ll, I’ll underline everything that was already shared. And I’ll just talk a little bit about poverty. Um, we need to address poverty. It is, um, extremely painful, stressful, traumatic. And I think we forget that it’s deadly. Poverty kills us. And as I mentioned earlier, it’s within our power and, uh, to, to address poverty with policy. And we need to do things that work that are demonstrated to have worked like the child tax credit.

We also need to invest, um, in our benefits system that helps meet basic needs. And we need to go beyond meeting just basic needs and try to build a system of benefits that is designed for people to thrive and experience abundance. Um, we also need to address, uh, corporate power, the corporate power that is undermining our shared prosperity in this country and especially oppressive for people of color and people experiencing poverty. And we need to do things that, uh, protect workers like, um, improve wages and provide other protections and supports like access to paid leave, for example, so that we can care for each other.

Diana Elliott, PRB: I’ll chime in and well, I’ll just say thank you to our panelists for those fantastic recommendations. Um, and at least from our perspective at PRB. I mean, we see a lot of power and data. I think these data really show how important it is to disaggregate data for different groups. Um, and that there is real power in being able to tell these stories, because on some of these measures, these deadly measures, we’re seeing different directions. Um, so you might see that white women, for example, have done better on some of these measures over time. While it’s not the case for women of color. So, um, power and data and showing as much disaggregated data as we possibly can.

Jennifer Gerson, The 19th News, moderator: Thank you so much for that, Diana. I’m gonna, um. Very well. Some questions we’ve got from our audience right now. And I just want to remind everyone that anyone who’s here and in the audience, you are welcome to ask the question. And you can do so by just typing it into the Q&A box. And I will read it out loud, just like you’re about to see. And a panelist will answer. And when you’re asking a question, please be sure to also identify yourself and your organizational affiliation.

So I just want to start with, um, some of these that we have here. Um, we have a first question that says that, you know, we’ve got data showing that going to college, um, that, you know, women that go to college do make more annually than those that don’t. But what can we say from the report? What did you find in terms of that comparisons? And is it worth it for women to get into more debt at this point in time and more generally, what does this mean in terms of debt that Millennial women are carrying as a result of accessing this level of education compared to previous generations?

Sara Srygley, PRB: We did look in the report at other research. We did a lot of background research and looked into student loan debt and the racial and ethnic components as well as the gender component. And we did find that women hold more student loan debt than male peers, and that women of color hold more student loan debt than white women. So there, again, is a real disparity there that not only presents those barriers to higher education, but also increased stress for those who do obtain higher education.

So we’re seeing these higher rates of education, but with those higher rates of college degree attainment, we’re seeing that student loan debt coming alongside. And there are some real consequences to student loan debt beyond just the monetary consequences. There’s been research to support that. Mental and physical health is negatively impacted by student loan debt. And so whether or not the trade off is worth it, I think I’ll defer to some of Diana’s expertise on the benefits in terms of the finances of debt and degree attainment. But for sure, we see massive disparities, and we also see some real serious impacts to people’s health when they carry that student loan debt.

Diana Elliott, PRB: Yeah. And I’ll just chime in to say that one of the hardest statistics for me to see personally is that, um, non-completers who are more often first generation students, they’re more often students of color. Um, often go down the path of going to school trying to sort of gain that degree to improve their future prospects and have trouble completing for some of the reasons that Martha articulated earlier, that it, it can be a really sort of unwelcoming place.

And for various reasons, there are other family needs or other needs that arise along the way. They tend to be the people with sort of low amounts of debt that are the ones that go into delinquency the most. Um, and some previous research and work that I did looked at how, um, those who would benefit the most from student debt relief are actually black women. Um, Black women would stand to, to gain the most by student debt relief. So when we think about these policies being proposed by the administration in federal, um, sort of discussions, um, it’s really important to think about, um, how this could change a trajectory and create equity, for example.

Jennifer Gerson, The 19th News, moderator: Thank you so much, everyone on that one. Um, you know, uh, Martha and maybe Doctor Harris, too. We have another question from Emma Bittner, who asks, can you speak more about the importance of cultural competency and the impact of the lack of providers of color when we’re talking about mental health care? Of course, anyone can jump in.

Martha Sanchez, Young Invincibles: Yeah. Um, I think in two different spaces. So we were just talking about how college campuses can not be a welcoming place for first generation students or students of color. Um, that’s because, you know, these institutions expect, um, that we come with the $5,000 to afford the meal plan or the dorm. Um, in the books and everything, on top of being an excellent student. Um, I know that one time I asked a professor for an extension and she said, well, in the real world, you don’t get extensions. But the reason why I need it is because I was working 30 hours a week as being a full-time student. So the stressors that students face on these campuses, um, where they don’t when they don’t have parents that are providing them with all of the financial and emotional support, are can be quite defining of their experience and of their ability to succeed. And it’s time that colleges take a realistic look at their needs in terms of the financial supports that need to be in place, that our government and state governments actually make investments in our ability to succeed in higher education.

Um, but in in these resources, something that will make a tremendous difference. Um, are the mental health resources, um, because for many first gen students, depending on, on their cultures, there’s a lot of stigma around mental health. And college campuses are actually the first safe place, oftentimes, where they can get free resources, free counseling, and the ability to connect with a counselor that understands their cultural experience or is at least open and willing to understand is really key and important, and then feeling supported. Um, so I think at the college level, increasing mental health resources is key. But then outside of that, um, we know that there’s a shortage of culturally competent providers. And that has to do with, again, the fact that that career path is not affordable.

We should be creating scholarships and financial assistance for students to go into the mental health fields, especially students of color, not just at the graduate level, because we know the data tells us, right, that students of color are not attaining master’s degrees at the same level as their white peers.

We need to look at the undergraduate level two and make sure that these students feel like that is a field open to them. Um, and that getting a psychology, psychology degree won’t just mean that they end up in debt and can never actually do anything with that. So we need to really take a look at our higher education systems. Are majors the financial requirements for them and be serious about what kind of workforce do we want to have in this country. Because even from an economic perspective, there is a need, there is a demand, and we’re not doing anything to meet that. And it’s, it’s unfortunate that we’re not providing these resources for the people who will be your doctors and teachers and politicians and scientists of tomorrow.

Jennifer Gerson, The 19th News, moderator: If anyone else, uh, wants to help and let me know. But otherwise I’ll move on to our next question, which is from Roger. Mark D’Souza from Pack Two asks, women from marginalized communities faced intersecting forms of discrimination. How could we recognize and address intersectionality in data, policies and programs and better amplify diverse voices and foster inclusivity? Who wants to hop in before I pick on someone?

Dr. Jamelia Harris, Justice and Joy National Collaborative: I can hop in and just start us out. I think that the first point is the acknowledgment, uh, that an intersectional lens is necessary. Um, I think that, as I mentioned, the research that, that the Losing More Ground report is depicting is really a rarity. And, and I want to be clear, as someone who’s coming from the background of education, that oftentimes, uh, the data that we get is just not disaggregated. And that really, uh, prevents us from having a full picture of what is happening for so long.

Uh, there was this, this, uh, broad and dominant narrative that girls were doing fine in schools because we didn’t have the data that was showing that black, Latinx, Indigenous young folks, uh, were experiencing particular challenges. And so now that we have additional insights into some of the challenges that are facing Black girls within our public education system, such as their push out into the criminal justice system, we know that, uh, Black girls are one of the highest, uh, represented among girls who are suspended, expelled, arrested. And this has consequences on their, uh, social, political, economical outcomes later on in life. Now that we have that understanding, we’re able to implement the policies to, uh, address this inequity. We’re able to implement the programing initiatives that are specifically targeting their identities at the intersection of race and gender.

And so I think that it’s one a first step is, is really the acknowledgment, uh, that we need to be prioritizing an intersectional lens. And I believe that a second step of this is that, uh, we really need to be ensuring that the folks who we are, uh, trying to understand their experiences within these various social inequities are at the forefront of seeking solutions. Uh, Justice and Joy National Collaborative are a big part of our work, is really rooted in our belief that nothing about us should be without us.

And so we are constantly, uh, engaging young people who are systems impacted as we are taking on our research initiatives, as we’re taking on our policy advocacy, if we’re taking on our programing initiatives, and we really do this with the intention of prioritizing lived experience as expertise, which is something that I fundamentally believe, uh, needs to be happening across the board.

And so one of the questions that I always ask myself whenever I’m doing this work is, who’s in the room, who’s not in the room, whose voices need to be in this space, whose voices aren’t, uh, reflected in this space. And once we start to be more intentional and paying attention to who those folks are that are consistently not given a seat at the table. To go back to that, uh, analogy, then we can really move towards ensuring that we have the kinds of representation that we need to push the needle forward for all, uh, young women of color.

Sara Srygley, PRB: I’ll add to that. As Doctor Harris said, the availability of data to disaggregate in this way is a real challenge. So speaking from a data perspective, how we can improve this and continue to take that intersectional lens is we need responsible collection and analysis of data on marginalized groups. And there’s a lot of discussion right now. For example, one of the things that we dive into as much as possible in the report, but we’re really limited in, is looking at gender identity and sexual orientation and the impacts of those identities on health and safety and outcomes for young women today.

And there’s not a lot of data out there, and there’s not necessarily comparable data across generations. And so we were really limited. There’s discussion now around the inclusion of questions of gender identity and sexual orientation in some government data sets and things like that. Thinking about the responsible collection of data and the responsible handling of that data for marginalized groups is going to be a really important piece moving forward to how we are able to identify communities that are most at risk and address those risks.

Jennifer Gerson, The 19th News, moderator: Fantastic. Thank you. And we have another question from Mark Mather who says this report is really about young women’s well-being. But he was wondering if anyone could speak to the potential impact of these patterns on children, since many of these women are also mothers.

Sara Srygley, PRB: So it’s absolutely true that many of these women are mothers, and we know that adverse childhood experiences have a long term impact for children. So these factors such as poverty, maternal stress, maternal mental health, uh, they will have those trickle down effects on the children of women today who are facing these problems and may increase adverse childhood experiences which affect the health and well-being of future generations. So when we talk about this data, it’s not just about today’s Millennial young women. It’s really about where we are today and where we’re going in the future. And so that’s why it’s so critical, because it’s not just about this moment in time. It’s about generations to come as well.

Jennifer Gerson, The 19th News, moderator: You to go kind of a little bit more about what we were just talking about with data. I was hoping we could all stack, but we got a question from Jeff Jordan at PRB, who wanted to talk about disaggregated data and threats to the collection of this kind of data, what you’re seeing, what you’re feeling in this field, and then kind of conversely, what potentially new or promising sources in the future might provide even more evidence for policymakers and program planners. So, Sara, I know you just spoke a little bit about that, but we’d love to hear a little more from Diana, Sara, anyone else who wants to hop in?

Diana Elliott, PRB: Yeah, I can hop in. Um, you know, I think one of the biggest threats that we have is changes in administration and changes in policies on data or shall we say, preferences on what data are collected and what are not collected. Um, now, um, there are efforts afoot. OMB is, is in the process of collecting public commentary on, for example, the sexual orientation and gender identity question. There is the process of vetting new race and ethnicity questions, which could improve how some of these data are disaggregated. Um, but there is a real risk to, um, changes in terms of who can control or who can stop collection of data. We certainly saw that happen in 2016, certainly with race and ethnicity data and changes to federal surveys.

So there is a risk. That doesn’t mean that we shouldn’t stop trying, though, because it’s incredibly important for understanding, as Sara was saying, which groups are affected most and which groups could most be helped by targeted and, um, specific policies in different areas. So, um, you know, I think the, the push for better data, data collection goes on. Um, and I don’t know if Cara has anything to add to this, since I know that she thinks about this a lot as well.

Cara Brumfield, The Center for Law and Social Policy: Yeah. Thanks, Diana. Um, I am a bona fide census nerd, which Diana knows well. Um, one of the challenges that I think about a lot is, um, how poorly we do at counting people of color in the decennial census, which is really the foundation of all of our data. Um, in the, in our nation, it sort of, it’s the universe from which we create samples for all other data analyzes. And we have never, in our history accurately counted, um, people of color, Black people. Um, we also have some challenges around disaggregation of census data. Um, I’ll just highlight that the Asian population, for example, a lot of disparities, um, are completely hidden when all of the Asian ethnicities and subgroups are sort of collapsed into this one big category. Uh, something else that I think a lot about is diversity and inclusion in, uh, among the data experts and, uh, the, the folks who make up the data infrastructure.

Um, we need, just as we need more diversity in the folks who provide us with our health care, we need more diversity in the people who collect and analyze and and discuss our data. Um, because they’re making a lot of decisions about which data to collect and how to collect those data and what those data mean, what the stories, those data are telling us. And we need people with lived experience of poverty, and we need people of color in those positions, because that’s going to help us have a more accurate understanding of what, um, what the data really means.

Sara Srygley, PRB: Absolutely. Uh, Cara, you’re so right that the decisions around what data to collect are really linked to the policy. And that goes back to that political and civic engagement. One thing that comes to mind for me, aside from that population data, is things like firearms research. We talk a bit in the report about some of the limitations that we face when looking at things like homicide rates and suicide rates, because there’s been limitations to funding at the federal level for agencies like the CDC to do quality research on the public health impacts of gun violence.

And so those changes in administration, those changes in policy have really limited our ability to compare gun violence and the impacts across generations in this report and continue to limit our understanding of those issues even today. So it extends really to sort of every area of data collection that is really critical to understanding what’s going on in our country and why we’re seeing these worse outcomes.

Jennifer Gerson, The 19th News, moderator: Thank you so much, all of you. I know we are coming up against it. So I have one last question. Diana. I would just love for you to kind of close out our panel with a look ahead and what you see on the horizon for not only young millennial women right now, but for the generations of women coming after them. Despite all the losses in progress, this data set really points to what wins do you see ahead when it comes to women and equity?

Diana Elliott, PRB: Yeah. Thank you. Jennifer. Um, first of all, I just want to say that I am so heartened by, um, just the amazing panelists on this group. I mean, if this is the future of research and policy, we’re in really, really good hands here. Um, and I’ll say it was really a point of pride for us that we had multiple generations represented as authors on this report. We had a Gen Z author who created our Gen Z pop out box and did research to sort of figure out what issues were most important to her and her peers. Um, we have a Millennial lead author. Um, we have Gen X represented, um, trying to, you know, sort of, uh, represent our, our small and mighty, um, generation. So it was really important that we had this, this cross, um, perspective across generations. Um, and I think the future, um, is really bright, right? We, we know that we have really civically engaged younger generations, Millennial and Gen Z women are civically engaged.

Again, we have, we had this discussion earlier about whether they feel that they have a seat at the table or where they’re whether they’re, um, brought into even these discussions. I think that’s something that we all need to be mindful of moving forward, because, um, you need diversity of perspectives. You need diversity across generations to make the best policy. I’d say the other area where I’d like to see some positive traction is more evidence used for policymaking. So inclusion of lots of voices and evidence based policymaking. I think if we have those two put together, we have a really bright future in this country.

Jennifer Gerson, The 19th News, moderator: Thank you so much, Diana, and thank you to all of our really engaging, informed panelists today. Thank you all for attending and joining us today to and to learn more about losing more ground, please visit prb.org or click on the link in the chat. We’ll drop in right now to follow PRB on X @PRBdata or on LinkedIn. And thank you so much again, everyone for joining us today.

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