 I'm Megan Dugan Bassett and I am the Chicago Fellow based at the Chicago Community Trust running our Chicago office. I'm so pleased to have all of you with us. We have a great group today. This is the second in a series of events and I'm so pleased to have the guests, the panel who have assembled today. As we've been getting to know them, it's been incredible knowing that there's people like this out here doing work in America and makes me feel really good to be an American. Just to let you know a little bit about our agenda, we're doing a series of small presentations so we can really dig into what each group is doing. You can go to the next slide. Our first presenter, and will be Leah Taylor, will also be joined by David Williams and Josh Goldstein. You can see each of their respective organizations and my colleagues will go into that in more detail. I'm joined today by my colleagues Meredith Sumter of the Justice, Health and Democracy Rapid Response Initiative at New America, which is a partnership with the SAFRA Center and Molly Martin, who I just have the pleasure of working with regularly. She's the director of New America Indianapolis and she coordinates local work at New America. Thanks so much to our panelists for joining. Before we get started, we want to make sure that you have a chance to engage and get your questions answered. So there's a question and answer box. Please feel free to add questions there throughout our event. But right now, if you would like to share who you are and why you're interested in today's session and what you'd like to take away, that'll help us make sure that we tailor our questions and the discussion to what you are interested in hearing more about. If you'd like to, you can do that right now. And just to reiterate, we'll have a short presentation from each of our panelists and time for questions from the audience. And then at the very end, we'll have a panel discussion with my colleagues. Without further ado, I will turn it over to Meredith Sumter. Thanks so much, Megan. We're pleased that all of you have joined us for the second of a two-part series on mapping inequality. So for those of you who joined us in June in our first session, you'll know that we learned of efforts in Chicago to map historic disinvestment and inequity that is spurring new strategies to allocate resources to neighborhoods that have been marginalized. We've also heard of mapping efforts across the Sunbelt in areas with high eviction and foreclosure rates with new learnings and data that is enabling local decision makers to respond in ways that can stave off housing loss following the pandemic. So today we will discuss with our speakers initiatives that are exploring different types of inequality in both rural and urban spacing and finding innovative ways to take them head on. So as Megan had mentioned, this webinar is hosted by New America Local, as well as the Justice, Health and Democracy Impact Initiative. Just a few words about both. New America Local is a distributed team at New America that works within local communities across the country on issues of racial and economic equity. So our team engages and connects with community partners, bringing new attention to the experiences and expertise of people whose voices frequently go unheard. And even more exciting New America Local works to help these ideas and perspectives inform policymaking. I represent on behalf of New America, the Justice, Health and Democracy Impact Initiative, which is a partnership between New America, the Harvard Saffron Center for Ethics, and Brown University School of Public Health. It's a new and integrated policymaking model through which national experts work directly with local leaders and practitioners to design effective policy supports and practical approaches in support of what we're hoping will be a more modern social contract, but one that also is responsive to local needs. So we thank you again for joining today's discussion and without further ado, I'm excited to have us kick off with Leah Taylor from the Center of Rural Innovation. Welcome, Leah. Leah will be sharing some of the center's work and using mapping tools to help investors and others identify areas of opportunity in our rural communities. This is, of course, an addition to the center's work with communities on the digital economy and broadband strategies. So Leah leads the Rural Innovation Initiative at the center on rural innovation. She has considerable experience in advising rural communities on building place-based digital economy ecosystem strategies, as well as on obtaining the resourcing that's necessary to make them happen. Leah has long been involved in community development through a variety of economic, social change, and indigenous entrepreneurial projects in communities across both the United States and Canada. Welcome, Leah. Thank you so much for that warm welcome, Meredith, and for inviting us to be here today. I'm really excited to talk with you all about mapping the future of rural innovation and how we do that through the Center on Rural Innovation and the Rural Innovation Initiative. Next slide. So our mission at the Center on Rural Innovation, which we affectionately call COREY, is to advance inclusive prosperity through digital economy ecosystems that support scalable entrepreneurship and tech job creation for those rural communities that we work with. Next slide. So this is our mission because we are facing a very significant rural opportunity gap in the United States today. After the 2008 recession, as you can see from this chart here, job growth in rural economies as a whole never recovered to their pre-recession levels, whereas Metro counties did recover and continued to grow jobs. But of course, you can see that on both sides, Metro and rural, there was a huge drop off because of the pandemic that impacted everybody across the board. But unfortunately for rural counties, especially, continue to push those places and spaces behind. Next slide. So everyone always likes to ask, and this is a whole other talk, but just very briefly, why did this happen? And there are three key reasons that we look at at the Rural Innovation Initiative, one being automation via manufacturing that turned typical rural jobs like manufacturing jobs, forestry tourism, agriculture jobs into automated opportunities that made those opportunities leave for jobs elsewhere for rural community members. Globalization obviously sped up the loss of these kinds of jobs and ship them elsewhere. And I think it's also important to remember that we're facing an ongoing decline in entrepreneurship as a whole across the country, but particularly in rural places that you need to have that entrepreneurship in place to home grow more of these jobs that need to replace those that have been automated or left us offshore, but only 1% of venture capital currently goes to rural areas, whereas 80% of that capital is currently focused in just five cities. Next slide. So at the same time, there is immense economic growth and opportunity in this country, and a lot of it is in the tech and innovation sector of our economy. From 1997 to 2017, as you can see here, the digital economy grew 4.3 times faster than the overall economy. And in 2017 comprised almost 7% of our GDP, but a whopping 97% of those computer and math related jobs were created in metro areas. Since 2010, I want to say that again, 97% in metro areas. Next slide. And this ongoing trend toward automation really threatens to widen the opportunity gap we're already seeing further. So a significant swath of rural counties are seeing this decline in net jobs as those jobs become automated. The McKinsey Global Institute did an interesting study that's pretty depressing, which is that if we continue on trend and we don't intervene, around 429 rural counties in the country will likely see 25% of their workers displaced by 2030 from automation of their jobs. Next slide. So we know that a significant portion of our economy is going to be digital. That's the future. And we need to find ways to make sure that rural America is also benefiting from this growth and not getting further and further behind. And so you can see here some examples of digital jobs that we're focusing on bringing more of to rural. The median annual wage for computer and IT occupations in 2019 was about $88,000. In contrast, that's far higher than the median annual wage for all occupations, which is a little bit under $40,000. So this is really important to bridge that opportunity gap. Next slide. But only 5% of tech workers live in rural America, even though rural America accounts for 15% of the total workforce. And so at Corey, our job is to close this gap. We want to see 15% of rural jobs as tech jobs. And we see that as a way to reach parity across the nation. And so we're not saying that all jobs in rural should be tech. But in order to partially close this opportunity gap, we'd like to see 15% of them in tech to help make a more robust economy overall for these rural places and spaces. Next slide. And to do this really requires an ecosystem approach where you have cross-sectoral partnerships in these rural places that are coming together that create systems that will bolster the creation of more tech startups that then lead to more growth in the tech industry for jobs and retention of those tech jobs over time. So that includes engaging higher ed institutions that are focused on digital skills training, of course, increasing broadband access, but not just access, also usage. Interesting challenge that we see in a lot of communities. We're looking at how do we foster more tech startups through entrepreneurship programs that may have in the past been really focused on Main Street businesses, which are important, but only one part of the puzzle. And doing things like creating remote worker attraction programs that have certainly been an interesting thing that's taken off in a silver lining of the pandemic. And last but not least, we're looking at how does this ecosystem help to create more opportunities for regular folks in a rural community who may have never thought of themselves as a potential tech worker or that they could run a tech startup as a part of that tech culture and community and that they can be a part of this story and see it as a part of their community's success over time. So the purpose of the Rural Innovation Initiative that I lead is to partner with rural communities who are looking at this as the future, as their future to build these digital economy ecosystems. So we started this work in 2018, we're still fairly young, but we've worked with 20 communities all the way through the process so far for I'm working with this summer. And we've helped these communities raise more than $10 million in federal and matching dollars through something called the Economic Development Administration's Build to Scale Venture Challenge Grant, which is a great opportunity for these kinds of communities to apply for. And once communities finish working with us at the initiative, they join as members of the Rural Innovation Network where they receive ongoing support to continue to build out their ecosystems, collaborate with each other and learn from one another. Next slide. So the Rural Innovation Initiative has three phases of technical assistance. First, we start with a current state assessment and that's where we really use our data and mapping tools that I'll show you in a moment to better understand the assets and the challenges that that particular community has. And then we do a deep dive based on that assessment to build a place-based strategy that looks at that ecosystem partnership approach. And finally, we support those communities to then apply for federal funding like Build to Scale to make sure there's the resources available to actually have this take off and get wings. Next slide. So the Tech Talent Tracker is, as you can see here on the right, is one example of how we use data and mapping during the assessment phase of our initiative and you can actually test out this tool yourself if you go to RuralInnovation.us, you can find it, it's a fun little tool to explore. The Tech Talent Tracker maps employment in digital jobs in a rural county, computer science graduation rates, patent data, web venture activity rates, broadband connectivity and usage and more. And then you can actually benchmark one county against other peer counties. So you can see how do you stack up against maybe your neighbor county or the nation as a whole to understand where is your biggest competitive advantage and what are the gaps that you're going to need to fulfill through strategic interventions. So now I'd like to share with you about one rural community to work with which is Platteville, Wisconsin and how we work with them to map out their digital future. Next slide. So we actually, even before we start engaging with the community directly to do this work we use data and mapping tools to even find the communities that we think have the best positioning to start to move this work forward. And often they do not realize that they have this potential yet which is always an interesting part of the dialogue. So we found Platteville using Corey's Rural Opportunity Map that we developed which maps all opportunities zones across the country in rural areas, broadband availability, where the post-secondary schools are that are producing computer science graduates as well as foundational things that make a community attractive to live and stay in like museums, libraries, breweries, child care opportunities and proximity to airports, things like that. So you can see here in this map that Platteville has a ton of these assets already. They have a four year institution that has a STEM focus which is the University of Wisconsin Platteville. They've got some really cool breweries. They have some childcare availability. They already had a Platteville incubator and they've got some really cool arts and culture activities happening in the area. So they had a lot of those latent assets that we look for in terms of what you need to start building a digital economy upon and they're facing really significant challenges. They have a poverty rate of about 31.4% versus the whole of Wisconsin which is only 11.9%. And so there's a ton of economic challenges as well as untapped potential to grow. Next slide, thank you. So we also, once we engaged with them and said, hey, we think you're a really great contender for a build to scale opportunity for funding and that there's real potential here. Then we dove even deeper with University of Wisconsin Platteville and their regional partner at the Southwest Wisconsin Regional Planning Commission to understand even further what other assets they have available. And so through our initial assessment phase we found a couple of things that I'll highlight for you today that really stood out for us that gave them some competitive advantage. First of all, their area produces 120 computer science graduates a year. And that comes from a few different institutions within a 30 minute drive time but in particular the University of Wisconsin Platteville. And they're in the 66%ile for all micro counties across the US which is impressive for a rural county. 50% of those students though report that they want to stay in the area after graduation but that unfortunately they can't. They have to go elsewhere for jobs. And there are jobs in a 50 mile radius but there need to be more in that Southwest Wisconsin region to be able to have that demand available for those graduates when they are finished. And what was really cool to discover was that there's a ton of intellectual property disclosures happening in the last five years particularly coming out of UW Platteville because they are a STEM focused institution but they're not being commercialized. And this was a real opportunity that was sort of left on the table and not being utilized yet when we first started talking to them. So based upon this initial assessment of their assets and gaps there was this really interesting paradigm shift that took place in our conversations with our partners in Platteville where a number of the community leaders when we first started talking to them said things like we don't have tech startups here. We're not sure this can happen in Southwest Wisconsin. Are you really like this is you really think that it's possible here that's just not what we do. Our students are just sort of perpetually going to be in this position where they have to go elsewhere to find work if that's what they're interested in. And through this process and being able to map these kinds of incredible opportunities that are available we were able to have that paradigm shift moment where on the second day of our strategy work with them they actually brought in a tech startup entrepreneur that they had found because of this conversation and started to realize that they have amazing assets in the community that with the right amount of water, sunlight and fertilizer can turn into local tech startups and then produce more local tech jobs that those graduates can then stay and be a part of the community and continue to make it even more of a beautiful place to live and be in. So we worked with Plattville then to take all of this data information and translate it into a strategy and an application for build to scale funding. And I'm very happy that they were successful in winning an award. So they won almost or a little over a million dollars in total and in three years they got the grant in 2020 they will produce 15 scalable tech startups through this funding 20 new entrepreneurs overall and 55 new jobs. So that's just one story of many communities. Next slide. So there's just like I said there's one story of many communities like Plattville in our network that are all working towards digital economic growth and entrepreneurship in their own communities. And we're really excited to continue this journey with more as we go on in the work. Thank you all so much for your time and attention today. It was a pleasure to share with you. I look forward to answering questions and please feel free to reach out to me by email if you have any further desire for discussion and dialogue. Thank you. Oh, thanks to Yulia. It's such an engaging, uplifting and energizing presentation of the untapped very much their potential across our rural communities. I was most struck by your discussion around the paradigm shift that happens as Cori is engaging local leaders about the potential that they, their local industries and their local workforce could bring. And to that I can see from our list of questions that some of our audience members likewise have questions about that. So let me go ahead and turn to a few of those. One, it comes to us from Aaron. He asks, how do we get elected officials not familiar with sophisticated mapping approaches to become sufficiently informed in order to be comfortable with this approach so that they can understand how they make use of these tools for funding development. That is such a great question and it's actually a big part of what we do at the assessment phase. Once we've finished the assessment, we produce a deck that utilizes this data and shows the data story and the mapping story that we have come up with their case for change for why they can move into a digital economy of the future. And that is often used to be socialized with political leaders and other influencers in the community to see this as one, this is possible but two, this is how you can use data and mapping to show that story and translate it into an application like a build the scale grant that makes it more compelling. And if I just made a quick follow up and I know that we're short on time but as you've worked with multiple communities, I mean, Platteville is just so inspiring but as you've worked with multiple communities across the country, what are emerging as best practices for how Corey approaches that community, both the local government but also the local workforce? Because you're working, it's not just one audience member that you've got there. You also have to convince the workers that this is an opportunity that you too can utilize on. I will try not to talk for an hour about this Meredith. What I will say briefly is we are learning every day when we work with the communities. So even right now today, I had a workshop with one community on their digital workforce development and we were exploring what we were calling guerrilla tactics to inform service industry folks that they could potentially participate in a coding bootcamp and earn significantly more than they're earning today. And one of our strategies was to make flyers that people add when they give their receipt and sign and give a tip that's just like, did you know you could participate in this bootcamp and make $90,000 a year. So we're constantly looking at that. I think the biggest thing is one of our parts of our model is inclusive tech culture building and it's really about figuring out in each community who are the target participants that we wanna be intentional about reaching and who are the partners in that community that have the best access and understanding for those groups to make sure that what we're designing is going to be accessible and that awareness and outreach will happen from the outset. So it's not just the usual suspects that show up. No, absolutely. And you're unlocking through that collaboration. You're unlocking new opportunity where there wasn't before. Leah, Taylor, thank you so much for your time with us. We will have more time to ask questions on the back end of the presentations, but I'd like to now shift quickly to David Williams who serves as the Director of Policy Outreach and Opportunity Insights to share with us the latest research on tracking and mapping poverty and inequality in our communities. Opportunity Insights is a research and public policy lab. It's based at Harvard University and it uses big data to strengthen upward mobility in our communities. So David supports Opportunity Insights research and evidence-based policy changes by creating and leading partnerships with communities across the country. So before joining Opportunity Insights, David served as his Senior Advisor to the Mayor of Detroit and was a member of the Mayor's Economic Development Team, brings a wealth of insight and knowledge. Welcome to you, David. Meredith, thank you so much. Very pleased to be here with you. And I think it's a really interesting conversation because all these different tools and policies that we're talking about, I think are very different, but I think there's some really interesting overlap. So to get to kind of present together and answer questions together, I think provides a really great opportunity. So I'll talk a bit about our research overall of Opportunity Insights. And then I'll talk specifically about one of our tools called the Opportunity Atlas. That basically tries to distill that research and really help explore with communities and stakeholders doing the work on the ground to understand how we can really translate research to impact across communities, across the United States. So if we go to the next slide, we'll talk a bit about some of our research focused on opportunity and economic mobility, a real core of what we work on at Opportunity Insights. And a lot of our most recent research has focused on geography and how geography differs dramatically based on where you grow up across the country. And what this map is showing is, one metric we use to track economic mobility and upward prosperity. And how we do this is that we leverage IRS and Census Bureau data of 20 million kids who grew up across the United States in the 1990s. And specifically, we focus on kids who grew up in low-income families. We're able, we know how much their parents made when they were growing up. We know where they grew up and we're able to track their outcomes through this data five, 10, 15 years later when these kids are in their 20s and through their mid 30s. So we really get a sense of, right, how low-income kids are doing in terms of adult earnings and car restoration rates, college access. And specifically, this map is looking at those earnings in early adulthood. And what you can see is that this metric of upward mobility of Opportunity varies dramatically based on where you grow up. You see these areas of deep blue in the Great Plains and on the coast are areas of great upward mobility where low-income kids on average who are growing up in families that earned around $27,000, they're earning upwards of 35, 40, sometimes over $45,000 on average. And these are really economic mobility rates higher than any country that we have data for. But you also see these areas of deep red in the Southeast, in the Rust Belt, place like Detroit, Cleveland, Atlanta and Charlotte where kids who grew up in low-income families on average remain low-income adults and very low rates of upward mobility in some places actual downward mobility. And so a lot of what we do is using data to track these trends, but also really thinking critically around what's the cause of these different rates of opportunity upward mobility and what are policies that we can do to change some of these trends where we see opportunity lacking. If we go to the next slide, one of those factors that we look at actually kind of interesting compared to kind of the work that Leah's doing is we look at metrics like job growth as well. But interestingly, something we see is that job growth rates oftentimes aren't associated with this metric of opportunity that we're focused on. And if you look at places like Charlotte and Atlanta, communities that have had tremendous job growth over the past 10, 20, 30 years, these are also places that have very low rates of upward mobility. And I think something that we see when we're working with communities like Charlotte is that, yes, there's lots of development. There's lots of new jobs, but oftentimes it's people moving to Charlotte who are taking advantage of those opportunities. And that kids, especially low income and middle income kids who are growing just down the road from uptown Charlotte where you have places like Wells Fargo and Bank of America, right? They really don't have access that exists right in their own backyards. So something that we focus specifically on with our research is how we really can think about human capital development in childhood and really building ladders to opportunity within these same communities where there really does seem to be prosperity potentially available. If we go to the next slide, another factor we look at are issues of race and ethnicity. And so these maps are the same as that original map that really charts upward mobility across the country. But specifically we're looking at outcomes for black men compared to white men. And one thing to note is that these two maps are in the exact same color scheme. So what that means is that the best places in terms of upward mobility for black men are still worse than the worst places for white men. We see very different outcomes for black and white men in all the regions across the country in every community. And I think even in 99% of neighborhoods across the country, we see higher outcomes for white men than their black counterparts. And it's important to note that these are black and white men who are growing up in similarly low income families. So even when we control for your childhood circumstances, we're still seeing very different outcomes for black and white men. And I think this makes us think critically around what are those structures, what are those policies, what are those forces in places in our communities that are really impacting black men specifically, be it bias in terms of discipline in schools, the criminal justice system, employment discrimination, what are those factors specifically impacting different subgroups? And we're able to look at these trends using that census data tied to those long-term IRS records. But it's also important to note that even within these racial subgroups, if you look at the map for white men, we still see a range of blue to red. So of course, although race and ethnicity are playing a real role in terms of upward mobility, we still see that geography has a lot to say on this front as well. You can go to the next slide. And so when we look at these factors, I think some of the questions talking about, how do we actually help local leaders, local stakeholders, folks doing work related to economic opportunity and mobility leverage this data? What we did is we created a tool called the Opportunity Atlas, publicly available at OpportunityAtlas.org that takes all this data and allows you to explore your local community to better understand what are the trends for different subgroups based on race, gender, household income when kids are growing up to better understand what those local factors might be driving these outcomes we see in the data. And if we go to the next slide, when we zoom in to local communities, that same range of blue to red that we see across regions in the country, we also see within almost every community in the country. This map specifically is looking at New York City. And you see parts of Queens and Brooklyn and Staten Island have very high rates of upward mobility, but places like East Harlem and the Bronx and these very red colors, very low rates of upward mobility. I think in many ways, this is more helpful than those national maps where I think it might be difficult to say, hey, I'm to the mayor of Charlotte, you should be more like rural Iowa, right? That's probably not gonna be relevant with their policy conversations, but when we see these same disparate outcomes within communities, I think that starts to give us more clues about how we can really start to reverse these trends. If we go to the next slide, so something that we've done, and I think something that hopefully the Opportunity Atlas continues to facilitate, is looking locally to see what are those factors that can really drive better outcomes for low-income children. So some of these factors are those that we see nationally, better school quality, schools that really support low-income students, neighborhoods that are more socioeconomically integrated, where we have more interaction between lower and higher income families. These are all places where we see higher rates of upward mobility. Interestingly, a factor that we see highly correlated with rates of upward mobility are the proportion of two-parent households present in that neighborhood. I think something that I was really struck by when I first started working on this research was, neighborhoods that have a higher presence of black fathers specifically, all those young black men in that community who are growing up, regardless of their own family circumstances, have higher rates of upward mobility. I think that's one data point that really speaks to the community where you grow up, having role models, people that you can relate to, who model pathways to college and to stable careers can really have impact. And I think that's probably intuitive, but to be able to actually track those outcomes through data five, 10, 15 years later, I think is really powerful. And so with the Opportunity Atlas, we work with communities and help them leverage our data to identify those places where we might see surprising outcome to again help pinpoint what policies, what characteristics might be able to drive better outcomes locally and also provide lessons across the country. And if we go to the next slide to compliment that, we also work to better understand what programs, policies and resources can really drive better long-term outcomes. So programs like Universal Pre-K, mentorship programs for teens and adolescents, programs like Year Up and other workforce development programs that have been proven to really drive better outcomes. How do we build the evidence base about these types of programs and resources? And how do we learn from and work with organizations like the Harlem Children's Zone? Strive together. Other organizations who are focused on bring all these different resources, policies and programs together in place to really drive revitalization and support in neighborhoods to help create opportunity in place in communities who have been disinvested in for years, if not decades. If we go to the next slide to compliment this work using a tool like the Opportunity Atlas, we can also overlay other data on this metric of upward mobility. And on this map, what we're showing are locations of housing choice about your usage, federal subsidies to support low-income families in renting apartments, overlaying that data with opportunity in Seattle, Washington. And something we see in Seattle, and we also see across the country is that these very affordable, that these very important affordable housing resources are oftentimes concentrated in high poverty neighborhoods where we see lower outcomes for children growing up in these places. And so thinking around, not just how do we increase opportunity in place, but how do we rectify years of housing discrimination and redlining that have caused segregation that probably drives much of the unequal outcomes that we see in our communities today? If we go to the next slide, we ended up partnering with the Seattle and King County Housing Authorities to test out one potential intervention to help families who use section A vouchers and increasing the access to opportunities across the region, especially those places that have better outcomes for low-income children, oftentimes neighborhood that have not been accessible to lower-income families and families of color. And by providing customized search assistance, engaging with landlords and some short-term financial assistance, we support these families. And if we go to the next slide, we see that we've actually been able to have a very significant impact. Typically families in Seattle who are using housing choice vouchers, less than 15% ended up living in what we have done as these higher opportunity places. Go to the next slide, families who received these services during this evaluation were almost four times more likely to end up moving to these higher opportunity places. Neighborhoods that, based on our data, oftentimes children who grew up in these places will earn upwards of $200,000 more over their lifetimes. So a very dramatic way to potentially help really break the intergenerational cycle of poverty. I think this is just one example of how we can kind of leverage this data to increase opportunity for kids across the country. If we go to the next slide, basically to wrap up again, I think it's really interesting to look at all these different types of tools that we can use to better understand our communities in a variety of ways. And we focus specifically on upward mobility and economic opportunity, thinking about increasing opportunity in place, increasing geographic access for families in places that historically have had better outcomes, but also to really highlight these different issues and the inequality that exists within all of our communities to help galvanize, inform, and hopefully push our leaders to really invest the time and resources we need in our communities. So thank you very much. Looking forward to any questions and opportunity to have some dialogue with other panelists. Thank you so much, David. As Megan said, my name is Molly Martin and I'm the director of the New America Indianapolis office. And I did quite a bit of local work. And you know, David, I am coming to you from a very sad story in the Opportunity Atlas. In Indianapolis, if you were born in a low income household, you are even more likely to lack upward mobility than in most parts of the country. This is a big problem for us and we use your work well that way. One of the questions that we're asking ourselves in Indiana, rural and urban areas in Indiana, is with the growth of the Latino population. This really important cultural benefit to our society. We're lucky to have all of our new Hoosier neighbors. And there are huge deficits and opportunity for our Spanish speaking Hoosier neighbors. So tell us a little bit more about where the Latinx population shows up in your data. We had a really good question from the audience because they're seeing a lot more dialogue about opportunity for black men. Tell us a little bit about the experience of Latino men and women. Absolutely. One thing that I think is powerful about the sense of data that we're able to leverage is that we can break all this data down by race. So we can look at outcomes for black children, white children, Latinx children, Asian children, native children. And I think when you actually break down that data and look at the different subgroup outcomes, that can be really enlightening. Because I think one thing that is really sometimes heartening, sometimes not, is that even within the same community, we see very different outcomes for groups based on race and gender. And I think something that actually is heartening is that overall, we are actually seeing fairly high rates of upward mobility for the Hispanic and Latinx communities. I think oftentimes, these communities are lower income. So in general, we might see lower outcomes in general, but for those families who are specifically low income, when they're compared to other low income families who are white or black, their outcomes are actually relatively decent. And I think a lot of our research focuses that if we actually see the same rates of upward mobility for the Latinx community, they will actually start to be on par with the white community in a few generations. But again, these maps really emphasize that that differs based on where you grow up. And I think especially with the Latinx community, given all the different subgroups as well, we're seeing very different outcomes for Mexican Americans versus Dominican Americans and geographic kind of breakouts as well. So I think being able to look, I think both across the country at these different demographic subgroups, but also look and see where folks are doing extremely well, can it really provide potentially concrete lessons and think about what specific communities might need and those supports we can target in a very kind of more nuanced way. Thank you so much. On that same note, you said where you live makes a difference. I wanna take one last audience question before we move to Josh. I think one of the most important takeaways from the Opportunity Insights work is demography and destiny and the touch in between that. And we had an interesting question in the chat about how far you can zoom down because the difference from block to block is really sometimes very stark, especially as places continue to gentrify and change. How far do you zero in? Do you look at census track, zip code? How far do you go down so you can get a sense of kind of the block by block multi-generational wealth opportunity we have? It's a great question. So on the Opportunity Atlas, we're able to dive down to the census track level. So that's getting pretty granular in terms of what you're able to see in these outcomes. If you use the Atlas for yourself, something you might see is that, we're not able to look at every subgroup for every census track because there's not enough people of every particular group in all those tracks, but basically across the country on the Atlas, we're diving into every census track in the country and breaking out by those subgroups where there were enough kids who grew up in those places where we're able to create a statistically reliable estimate. I think we basically need at least 20 kids from every subgroup in that sense of track to be able to create the estimate for both statistical reasons, but also to make sure that we're maintaining people's privacy as well. I think if you were a middle class, if you were the only middle class black to get to grow up in your entire census track, we probably wouldn't be wanting to show that individual's actual outcome. So we have to aggregate that to that track when we have enough people to create those estimates. Thank you so much, David. Don't go anywhere. We'll be back to you. But for now, we wanna move on to our third panelist because I think conversations about data and demography and location took on a different meaning during COVID and the concept of resilience became increasingly important. And so we're pleased today to have Joshua Goldstein, Josh is the Director of Business Development and Partnership at Urban Footprint, a data insights platform that helps governments and companies support community resilience. His background includes a stint as the CEO of the Department of Better Technology, of the Chief Product Officer at Citibase. He also has experience at Google, the World Bank and USAID. So Josh, I'll turn it over to you. Thank you. Awesome, thank you so much. It's really fun to be here with David and Leah because as we've developed our data platform, both Opportunity Insights and Quarry were projects we looked at. So it's super fun to be here on stage with them and learn about the latest of their work. So one of the ways I think about Urban Footprint is that we're trying to really bring resilience, like kind of resilience DNA into the strategic planning and operations of organizations, really help them understand where communities are today, whether their interventions are reaching those communities and how they can get better at providing resources in a way that build long-term sustainability. Next slide please. So one of the most striking things about our political moment is really the mismatch between the resources that are available and those that get into the hands of the communities that need them most. We see this in everything from eviction risk and rental assistance here. The Emergency Rental Assistance Program is allocating billions of dollars across the country through states, counties and other municipalities. And many of these have not, been distributed or gotten into the communities that need them most so that these organizations can be confident they're preventing long-term destabilization of communities. Next slide please. We see this also in food security, something we often take for granted. The food insecurity rate in the US grew almost 50% since the start of the pandemic. And even though the Biden administration through the American Rescue Plan and other initiatives have extended higher levels of benefits, there are still nearly 20 million households of the lowest income households that have not received any benefits, set benefits since the start of the pandemic. So how do we kind of close that gap? Next slide please. So I like this quote, giving away money is quite hard. All the money in the world isn't going to matter if it doesn't get to the people who need it. I think this sort of summarizes the challenge that folks in a lot of these spaces are facing. And getting money into the hands of the people who need it is a multifaceted, it's not a simple problem. There's a lot of pieces related to making sure the application system works to making sure the program is known by the people who need those resources the most. Next slide. And coming from a data science and technology background, we thought about three key components that we think of as building blocks to data-driven resilience. The first is really a comparable and granular understanding of the composite elements, social, economic, environmental and climate risk, facing a community. Next is visibility into weather program dollars and efforts are reaching the most vulnerable communities. And the third is the ability to rank and compare and prioritize interventions that will close the gap and lead to long-term resilience. Next slide. And we're doing this in a number of settings. The first two examples I ran through here, food security and rental relief are really where we've put a lot of our efforts as a company working with state agencies across the country to help target and deploy those resources. We're also working with other federal and state organizations on equity screens for infrastructure and climate spending, and also folks like FEMA and Cal OES for disaster response and prevention. Next slide, please. And we're also working with energy utilities. So looking at how to deploy grid asset hardening. This is kind of an example of a complex large organization that has a mandate to invest in their infrastructure upgrades, but may not have a deep understanding of the community dynamics and how those dynamics interact with natural and climate hazards. Next slide. And then the final of the three pillars we look at is public finance. So ensuring that investments, whether it's municipal bonds or other public finance and equity and debt issuances can really take into account holistic climate hazard and community risk factors. Next slide. And the thing that connects all of these problems is that measuring resilience requires really deep context. And we think about this from a platform perspective in three levels really. One is the community resilience side, understanding people in a community and their behaviors. The second is the built environment. We have our roots in urban planning. So we have a very detailed understanding of place. And third is the climate and hazard risk. Next slide. And just to give one example of understanding granularity, which came up a little bit earlier, we put a lot of our effort from a data science and product side into taking data that is publicly available or that we purchase and clean and combine with other things and really disaggregating it across the landscape. So here's an example from how we look at food insecurity across the landscape. So we're integrating data from the Census Pulse Survey, which is wonderful, I'm sure most of you know. And really building synthetic populations and disaggregating that across the landscape so we can get down to the block group level and estimate the number of households that are food insecure. We think this is a compelling approach because it's not modeling based on past behavior. If the Census Pulse Survey, for example, in this case, if the results show that the population that is food insecure is getting older or has other aspects changing demographics or otherwise, that will be reflected in our model, which is updated every two weeks. And that really informs decision-making for state agencies and their partners as they seek to make sure that the households that are most in need can get access to things like SNAP benefits next slide. And then we spend a lot of time visualizing and displaying that across the map so that we have the ability to kind of tell those stories visually and important in addition to the data. Next slide. And to give a really concrete example, we're working with the Department of Children and Family Services in Louisiana. They're using Urban Footprint to increase SNAP enrollment, reduce costs on outreach and really sort of change the nature of the conversation, both internally and externally at the organization. Historically, a lot of these organizations will measure outputs. So the dollars spent on an ad campaign or even the rental assistance applications in that use case, but we wanna help them provide the denominator in a sense of really understand as they're getting resources out into the community, how are they essentially solving the long-term problem that they set out to solve? Are they actually closing that gap? Next slide. And this is not done in a vacuum. We're also working with amazing community partners, including Second Harvest Food Bank in Southern Louisiana. And they're using our platform to map the partners that they're working with across these communities and identify places where they can build new partnerships and develop a more comprehensive view of resilience. Next slide. And also feeding Louisiana, which works at the policy level, advocate for more resources and to help policymakers understand the dynamics on the ground. So that's really a three-pronged approach. We're working with the state agency itself to target distribution, working with partners on the ground who are distributing direct assistance and working with advocacy groups that are doing policy to address the underlying issues. Next slide. And then one other example is our work with the state of California. We're helping to target the distribution of rental assistance across the state and it's a similar challenge where we are helping a pretty broad ecosystem of partners map and measure the need in a dynamic way, compare given limited resources where they should do outreach and track the effectiveness of those interventions and how effective they're closing the gap. Next slide. And we removed some of the numbers here, but our work there both looks at the state level and also down into the community level. So here's an example of where there is a gap between where these applications are coming from at the state level and where our predicted need shows that the need is greatest. So really trying to build that visibility into this ecosystem. And next slide, I will stop there and look forward to your questions and chatting more. Thanks. Thank you so much, Josh. And actually we will be right back to you, Josh. I have a good audience question, but I will say before we lose Leah Taylor who has to leave a little early today, if you don't mind, Josh, I'm gonna throw a question her way first. So Leah, before we cut you loose, I grew up in West Virginia, live in Indiana. Meredith is from Alaska. Megan is from Iowa. We know rural. And what we do know is that you do have a yeoman's effort in front of you to change the way that some rural communities think of themselves. And one thing that I have found is we tend to tell rural folks, hey, you can do this job from anywhere. It's remote, it's tech, it's digital. What kind of community do you think a person needs to feel around them in order to not just be a worker, but stay in a place and enjoy remote work from rural America? What are folks telling you? That is such a great question. Just quick shout out to David and Josh, we learned a lot from both of your presentations already looking at ways to apply some of the things I learned for our own mapping. Great question on community building. Again, that is one of our core five drivers is inclusive tech culture building. And that's things like, a lot of the time we'll find out that there's a lot of remote workers and they're literally living in the woods and they have no connection to any other remote workers or there's tons of tech workers that we find in through our LinkedIn data that we can look at, but they're also not connected. So how do you bring those folks out through meetups? What are the topics that are gonna get them excited? Often it's not like tech for tech's sake, it's figuring out what is interesting in that community and culture that's gonna get folks out. So in Randolph Vermont, for example, we talked about the technology of beekeeping and finding those kinds of intersections between the local culture and the techies to get them excited about coming out of the woods, literally, and meeting each other and maybe producing new ideas, synergies, things like that. So it's bridging both the tech interest and then the local cultural traditions, contexts, things that will get everybody out to an event. Thank you, Leah. One last thing before I pivot to Josh. One, thank you for being here. I know you'll have to slip away, but another is I need someone smarter and more important than I am to tell the audience, are rural communities solely white? No. No, they are not solely white. Yes, Megan, thank you as an example of that. Sure, I think that there's unfortunately a stereotype that that is the case, but when you look at the Southeast, for example, many of those communities some we're looking at right now are maybe 70% African-American or 50% or 60% Hispanic or Latinx. It is not at all the case that the majority are white predominately communities. And that's a big picture. That's why I think, David, you're mapping, I'm already thinking about how to use it. I started looking at Towson, New Mexico and the differences in opportunity across different races and genders. And it was a pretty staggering difference. Highly recommend you check that out. Absolutely. Just jump in before we move over to David and Joshua before we have you. Leah, just a few more minutes, we're gonna squeeze what we can with you. I was really struck by Molly's thoughtful question and your response about individual tech workers responding to community in rural communities. The question I have for you is when you are working with local communities with the local government and local industry, what's the process by which they come to understand their own potential and developing a local tech industry? How do they go about doing that? And how do you work with them to support that process? Great question. It often starts with the mapping and data and saying, have you thought with the fact that you have this many computer science graduates? And in the case of Randolph Vermont as another recent example I worked with, they're all going to other places in Vermont to work. There's nothing happening on the entrepreneurship side. How do we solve for that? So showing them what's available in their community that is an asset and then what is the other side of the balance of that system that is missing is often where the inspiration starts to happen. I think then it's just really, that's that paradigm shift moment that happens almost every single time with these examples, which is then showing them and pointing to other communities that are similar that we've worked with and saying this is how Cape Gerardo, Missouri did it or this is how Traverse City, Michigan explored this. So this is what Red Wing, Minnesota has done where they've come from to show similar opportunities faces where they started and where they are today to get them motivated to move in that direction. It's why there's that aha moment and we get it as well when we're working with local leaders in communities across the country when they're thinking, well, there's opportunities in more urban spaces. So I'm going to focus my efforts on trying to connect with partners in larger urban spaces other than realizing, actually, if you look right around you or even in communities of like-minded size or characteristics, you can find some very interesting opportunities to build that digital tech ecosystem. You don't have to go to the urban center to thrive in that digital economic environment. Yeah, I'll just add one more thing. That's the cool aspect of the network is it's actually 1.2 million people-ish now. So we think of as our own rural distributed city and there's a lot of collaboration happening across those communities where you can leverage the activities that are happening in one to start happening in another. And that's more exciting because there is that mutual understanding of what it means to do this in rural versus trying to replicate something in Tulsa, Oklahoma. I realize some people might see as rural. It is not compared to what we're talking about. I just want to say briefly, thank you all so much. I'm sorry I have to go. It's been a pleasure to learn from our other panelists and to talk with you all today. Thank you so much, Liam. Have you. Kind of doing a pivot back to Josh because we do have some specific questions for you before we get into a group convo. So I'm going to take great care to read this one, Josh, because it's a word problem, but it's a really important one. So Erin, thanks to the point. Let's say a mayor has $5 million approved for $500 checks to give to 10,000 people in a city of 300,000. How do you determine who needs those funds, who comes first, how to distribute it most equitably to solve future problems? Great question, Erin, Josh. How would you leverage your science to do that? Yeah, so we try and flip these resource allocation questions a little bit in the sense that most of these programs, like the one that was described in the question, perhaps are application-based programs. And that's a challenge, right? Because if you have first come, first serve, or you just have a income threshold, it's very difficult to know how effective you are going to be at fixing really the long-term problem that you set out to solve. And it is imperative to have that measure because these challenges, food security, especially rental assistance, these can destabilize communities for generations if there's mass evictions, for example. And so really having a visibility into where that need is, is critical. And that's where we've tried to help out a little bit, which is essentially having that dynamic measure at the spatial level. So for the most part, and there are a few exceptions, we don't do individual sort of human or person-level analysis. We're analyzing the contextual factors about a person's community, right? In the same way that like you or I are put into kind of little boxes by Facebook and Google in terms of our marketing interests and whether we are tricycle riding, coffee drinkers, there is an analysis that one can infer certain characteristics at the community level in terms of need, right? We should be able to put these tools to work to infer where need is just as much as we can put them to work to sell us something online. So having that full granular understanding of community dynamics and how it's changing can essentially inform the outreach and allow for dynamically updating that strategy so that if you have partners, PR firms, if you have outreach partners, you can help them fill the gap and make sure they're getting to the places and the folks who need those checks the most. Josh, I wanted to jump in here with another question from the audience. So one of the people in the audience was asking about how you gather information from people in the spaces that you're working in. So beyond the kind of publicly available data and the data that you purchase, how do you learn from the communities that you're going into or from the expertise and knowledge in the communities that you're exploring and analyzing? Yeah, that's a good question. I think the main thing that has improved our models and data has been interactions with experts in the particular issue areas. So most of those, in fact, I would say, particularly around food security and rental assistance are community organizations that are active on the ground. Like we would never have been able to build a sort of data tool for food security or eviction risk without developing that in partnership with Feeding Louisiana, Second Harvest Food Bank and these others. So that practitioner engagement and by default kind of taking in their local understanding has been absolutely mission critical to us and it's a huge part of how we do product development. And since the start of the pandemic, we've released now two iterations, two versions of the food security insights data product and we're kind of continually to update and hopefully make it better with input from the organizations that are using it on the ground. So coming back in to that same point, I think just to press a little harder than that, but coming to you, David, how do you help people in communities or how would you recommend we help people in communities understand what's being collected about them, how it's being used, where they might go if they have a problem or a question or an idea for better data points or more human-centered data collection? That's a great question. Also, hopefully everyone can hear me. I have to change my speaker. But I think the biggest thing is that, right? I mean, I'm actually not a data person by training. I'm a lawyer by train, right? I'm not the one who's going to the U.S. Census Bureau website and taking their data messing around, right? I work with a great team of economists who know how to really manipulate this data and we really leverage some really great data visualization people who are going to create some of these online tools. So I think our first step, one was acknowledging that academic papers are not going to get the message across. Like really technical resources are fantastic, but that's not going to help people who are really smart doing great work but might not have a data background as their primary responsibility. So I think a tool like the Opportunity Alice where we basically try and create something that's as user-friendly as possible that takes this data and really creates something that anyone can use, I think is the first step. I think also something that we've done is we partnered with Bloomberg Philanthropies and their What Works Cities program to actually basically teach a course on that. I think we wanted to make it as user-friendly as possible so people can use it on their own. But then actually working with local government policymakers to say, hey, here's how we think you might be able to use this tool and this data, but also we would actually love to work with you. So let's actually have this iterative process understand what your challenges are, the questions you're asking, and see how this tool can be more effective for you and also how we can learn from these experiences to create new tools and resources that might be able to ask and answer other questions as well. So I think one, it's listening, being aware that we're not all data scientists, creating tools that are hopefully easy to use, but then I think really having that iterative conversation to say, hey, here's our assumption about how we can use this data, but we really love to hear from you about the questions you're asking. And then we can start thinking about how we can leverage our experience and skill set to build additional tools and resources for these types of questions. Yeah, if I just might jump in here as well, I'd love to your presentation, David. As always, when you're working with mayors or county officials or even state and other local level officials, part of it is understanding the experiences of your people, depending upon where they are and what their experiences are. And when we're working with local leaders, that's first and foremost. You've got to open up that black box. What I'm really interested in is what happens when that black box is opened. And when you were presenting, you talked very eloquently about your tracking outcomes through data to help pinpoint what policies and circumstances can improve mobility in the four buckets. Just very quickly here, social capital, school quality, low neighborhood, poverty rates, and more stable family structures. And a subsequent slide you talked about, well, look, when receiving support, a large percentage of families moved to an area where they could have greater upward mobility. The challenge for local leaders, though, is what to do with those areas that are struggling. And rather than have them be left behind, it's harder work. It's a harder road to hope. But I would love your thoughts on, and coming from rural America, I can say harder road to hope. So there we go. But I love your thoughts on examples of communities and leaders who have taken your data and have done things with that data, what sort of technical policies that they've put in place to begin to create those opportunities in place that you spoke of. Can you provide just a few examples of how you see this at work? That's a great question. That's really at the heart of a lot of our ongoing research. But also I think sometimes the tension between these policy areas. And to be candid, I think we don't have the perfect answer on exactly how we invest in community to really increase opportunity in place. But I think we're working with certain organizations we focus on particular policy areas. So looking at organizations like Europe, whose model has really been effective in helping disengage you to re-enter the drought market and really seeing increased earnings for these kids and thinking through how we can leverage not just a mapping tool, but also our research looking at longitudinal outcomes to better understand what are the long term impacts of those different types of programs. We've also done research on universal pre-K or pre-K programs, high quality teachers, and also showing the long term impacts of those programs. But there's organizations like Strife Together that focuses on collective impact models in communities. You have, I mentioned the Harlem Children's Zone. You have the Dudley Street Neighborhood Initiative in Boston, which is a community land bank and local community organization that have really focused on bringing all the evidence to bear in helping create opportunity in place. I think oftentimes a lot of our work with these groups has been to help galvanize those resources to really show both where there are places where opportunities are lacking and being able to visualize that in a very dramatic way to help bring additional insight and additional eyes on these issues to help them when they're testing out their different solutions. And also I think we're still working hard on exactly what our data can point to in terms of what those solutions are. But again, I think it's about that iterative process. Data sometimes only takes you so far. It's about combining that data with local perspective and expertise to figure out where those synergies might exist. No, I think that's exactly right. And if I can just repeat that same kind of approach to Joshua as well, I think I was struck when you talked about local policymakers' use of urban footprint data, both to better target their outreach to ensure that the resources are better reaching those that are in need of it, but also to identify local partners and those hard to reach areas. And I think that speaks to the element of trust or lack of trust in some of the marginalized areas in our communities where they don't feel as if they have already connection to the governments that is looking to serve them. So I wonder if you can speak just a little bit more about how youth scene local governments use that approach of identifying partners in those hard to reach areas to build that trust and to reach their fellow citizens. Yeah, I think that we're kind of repeatedly struck in these contacts by the challenge of working with the state often from the communities perspective and organizations that sort of provide umbrella resources, whether it's direct food aid or whether it's helping people fill out SNAP benefits, they're often trying to look at a broader measure of resilience beyond just the distribution of a particular benefit. And that's one of the kind of like meta projects I think we collectively have is, and I think David's your group does a really good job of doing this of like providing a better context of what true resilience kind of would look like. And we do that by essentially trying to understand the processes that these state organizations are using to distribute resources and build a little bit of that perspective into those processes. Like one example is for energy companies, they're spending billions of dollars on energy infrastructure upgrades. They've historically done that with a bunch of engineering criteria that they know really well, but they want to say, hey, instead of upgrading the latest, the oldest piece of transformer infrastructure, I wanna optimize for making sure that blackouts don't indiscriminately hit underserved communities, right? And sort of building that in the context of their day-to-day decision-making without having to have them like, really have to rip and replace and like understand something totally new, I think is one of the big challenges and opportunities here. I think that's a great point, Josh. And that actually brings up a question that had come up while you were presenting earlier. I was just thinking exactly about that point about how climate change is really exposing and will probably continue to exacerbate the existing inequities that we have. And so I'm curious, what are the different types of data that you guys use to help advise? And that was exactly the specific example I was interested in to advise a power company on how to change the way that they're investing or figure out where to invest infrastructure first to make sure that they're being really equitable in the way they do that. Yeah, we spend a lot of our R&D sort of time and bandwidth thinking about that because it is really about, as I mentioned, kind of the intersection of these. It's about where climate and hazard risk, heat wave or fire here in California, flooding also here in California, but also in other places and how those interact with underlying community characteristics and even behavior. So things like vehicle miles traveled, percent of people who own vehicle, energy, electricity usage. We're big believers that simple single sort of statistics are not gonna sort of tell this story or inform these interventions, which is obviously a big theme of everything we're talking about here today. And then I mentioned climate and hazard community and then the third sort of pillar being the kind of built environment. So understanding density, understanding zoning. We've gone really, really deep. This is one of the biggest sort of data projects that we've ever done, which is kind of identifying and codifying and standardizing the wide array of kind of zoning and built environment components that are across both the state of California and nationally. And so that allows us to really have what you can think of as like sort of a data cloud because the particular datasets that you need to answer any given question will vary. And that's like one of the big technical and interesting sort of product questions that we have is how we sufficiently provide the menu and then sort of configure or target that menu for the particular needs because that large energy company is gonna have a slightly different riff on what they need than a large municipal bond investor. But the general idea that sort of building resilience into the way these organizations do business on a day-to-day basis is kind of the problem we're solving here for. Along those same lines in terms of kind of solving a problem that people might just consider an urban problem or a rural problem. I'd love to hear each of you highlight kind of what you think rural and urban communities and even kind of ex-urban communities have in common in terms of their struggles and the ways they can use data to combat those and what they are just apples and oranges on. So David, would you go first? Yeah, so hopefully this gets at the question, but I think something that we see in the data is that there are actual differences between rural communities, right? I think oftentimes there's this broad brush or there's this debate or kind of framing of urban versus rural. I think something we see that I found especially interesting in the data was the actual difference within rural communities. So if you look at the Great Plains, Minnesota Iowa was actually born in Iowa, North Dakota, South Dakota. We see very high rates of upward mobility in these rural areas. But if you go to the Southeast, North Carolina, Georgia, the rural areas actually have some of the lowest rates of upward mobility. So I think looking beyond just those assumptions we're making about different types of geographies and actually looking at the data is very important. And I think I'm thinking about Leah's work as well. I think it's really important to think about what the ultimate goals are, right? Because there are probably many rural communities that she's working in that probably have the ability for the kids to grow up there. But because of maybe a lack of economic opportunity, they're all moving to Chicago or to the closest big city. So even though they might be doing well on one end of the spectrum, to actually retain the vibrancy of that community, they need to focus on economic development, job attraction, incubating new new companies potentially in the startup ecosystem versus again a place like Atlanta or Charlotte where all the jobs are going to a lot of these communities but they're low income kids aren't able to actually tap into all that prosperity there. So I might have kind of cheated a bit on this question but I think what I think of as the universal is that there's really interesting heterogeneity in place that oftentimes we assume are very similar. And I think at least this metric of upward mobility I think is one of those ways to kind of think about a core component of what's happening in these different communities. And I think just on one point too, I think what we try and use the Atlas for is looking at these places that might look similar to a neighboring community in terms of demographics, meaning income, some of these things that we think about in terms of affluence and opportunity but have very different outcomes. And then thinking about what is it that's happening? How can we dive a bit deeper either through data or maybe through kind of qualitative research and conversations to say, hey, these places look very similar but what's going on here that's really driving better outcomes and what lessons can we learn from these places? So sorry if I cheated a bit, but hopefully that gets to some of those issues. Honestly, David, I'm living the dream. You elevated my question with your excellent answer. So thank you for that. And Joshua, I'll swing to you with the same question. Yeah, so we've thought a little bit about this in partnership with Second Harvest Food Bank. We're just one of our partners on developing the food security insights. And obviously in addition to just the different scale, like basic facts like a census block, being a different size often based on population. So you're covering a broader area, but the composite of some of the interventions that lead to a more holistic view of resilience, I think they and we were finding are slightly different. That could be anything from where you locate a sign-up program for SNAP or how you route a mobile pantry to maybe leveraging a broader set of resources or potential partners. So they were looking at aligning with nursing homes, hospitals, emergency medical stations, public housing, religious sites. I think there was a broader set of how the interventions and longer-term resilience was viewed in some of these rural parishes. And we're continuing to work with them to sort of build that comprehensive view. We have this concept of a sort of a parish briefing book to try and build that composite and get beyond some of the more standard measures that the industry has historically used and are useful, such as meals per person in need, which measures the amount of just pounds of food or meals distributed over an area in the context of the annual or bi-annual survey to having a more dynamic view of that. So that's something that we're excited to keep supporting some of our local partners on there. Thank you so much. Megan, I think I'm coming back to you. Yeah, and actually we still have a little bit more time. So I want to kind of build on your question and ask a little bit more of David specifically. So Molly mentioned that I'm from Iowa. And I have worked in Chicago, though, and worked on Chicago issues for the last 25 years. But so I'm always kind of, so I continue to work on urban issues, but I'm always kind of in the back of my mind interested in kind of how rural areas are doing. I'm just curious in the analysis that you all have done, it seems like some of the bigger maps, you guys are comparing census tracks. So you have analysis of rural spaces, but then some of the other charts, you're looking specifically at metro areas. So I'm just curious, like when you guys have done different research and also think going back to this thing about, you know, where are people of color. And, you know, recognizing that there are also people of color in the southeast and the southwest. I'm curious about what kind of differences you see when you kind of break it down into this, you know, kind of rural census tracks or rural county areas, compared to some of the metro areas that you look at. And what are some of the interesting patterns you've seen? Yeah, so, you know, a few factors we see, I think one that strikes me as really important are patterns of segregation. So I think, you know, communities where you see high levels of socioeconomic and racial segregation, you tend to see much lower rates of upward mobility for low income kids who are growing up in those communities. You know, one factor that we see, and it's a bit nuanced, I'll make sure I'm not confusing it here, but I think in a lot of communities where you see kind of higher minority populations, you see lower rates of upward mobility. But I think the important distinction is, I think, yes, you see lower rates of upward mobility for a certain minority group, especially African Americans, but you actually see in these communities lower rates of upward mobility for all low income kids, including white kids, right? And we do a lot of work with the community in Charlotte. And I think there's actually been a lot written about Charlotte and South East. I think oftentimes in communities that have histories of slavery and kind of more explicit segregation, oftentimes those laws, those social structures, those mores are in general much less supportive of all low income families and individuals, not just individuals who happen to be Black, who happen to be Hispanic. So I think kind of looking at the social safety net, right? You know, how policing looks. And I think, again, those trends, both of segregation and those places that historically, you know, are defined by, you know, less supportive social structures for folks who are on the lower end of the socioeconomic spectrum. I think those are very big drives. I think we see that pretty consistently across the country. Perfect. I just wanted to squeeze every moment that we can with the two of you. We do have another question from the audience. This one comes from Karen and she asks, is there evidence that shows that in areas where local strategies are targeted to specific neighborhood, and this would be like assistance, like investing in crime reduction, improving transit, funding education, parks, streets, et cetera. Instead of impacting targeted residents that are intended to receive those benefits, instead there is an onset of gentrification. Is there, I think she's trying to understand as well our, is there any evidence of that? So maybe just, just, just briefly, it's a, it's a great question. And it's actually on the top of our research agenda. I'm just, I think Meredith to the point you raised earlier about that tension between geographic access to opportunity versus investing in place. I think we're both looking at, right? What are those different policies, housing policies, especially that have been used to help revitalize communities and what's the evidence base of those policies? Are they really changing, you know, life trajectories in the way that we can track in our data? But I think to the point raised by the additional question is, when you actually make those investments, if you start to see higher rates of upward mobility, you know, is it something that in tandem is actually pushing most of the vulnerable people out of that come out of that come, come community. I think my assumption would be it differs based in different places where I think they're, you know, I'm sure there are certain communities where, you know, you see an influx of economic development prices go up. It's largely low income families are largely renters and they get pushed out of community. I think other places where you might have more home ownership, be more proactive policies of portable housing, you know, you might see kind of more folks who are able to stay and hopefully benefit from those changes that they're seeing in their community and being part of that change in their community. And again, I mentioned places like the W neighborhood street initiative, the Dudley street ever initiative in Boston, a community lanterns actually focused on helping revitalize and support the community while building in and planning for success and making sure that current residents are part of that change and able to stay in affordable housing in that community. So I think my assumption is going to be varied across the country just like economic mobility are varied. I think we're working hard to figure out more precise ways of really tracking and understanding when people are being just displaced by this kind of development. I'll just add one other response to that. So I think it's, it's a super interesting question. I think that captures sort of why we think it's exciting to look at this from a resource investment and distribution perspective, because, you know, some, some resources are about, you know, reaching the communities that, that are, you know, just directly getting resources in people's hands, but others are things like affordable housing investment. We work with, you know, some of the larger folks talking with, you know, Freddie Mac, you know, to some, you know, affordable housing private private sector affordable housing investors. And they bring up this issue a lot where it's, they want to understand how they can sort of provide the right services and support more communities where they already have buildings or, you know, affordable housing. And then also to make new investments in where can they invest into, to sort of strengthen long-term resilience. And it also, you know, you could flip the question, right? And, you know, use, use a lot of these types of data to prevent the sort of bad outcome that we're talking about, right? Like, are you making investments that could lead to a, you know, a bad outcome in the community that, that makes forces people to leave. So I think that, that is a really critical part of this story as we, as we kind of drag this over time. I know we're coming to a close, but Estelle Clemens just posted a fascinating and important comment in the chat box. I wanted to draw attention to that. And if you have any closing comments on whether you've seen this done or if you're aware of research that's out there on how social capital is built and shared and hard to serve communities. It makes me think about Leah no longer with us, but building opportunities in rural areas that have been viewed as being disconnected from social capital or upward mobility. She's proving that wrong, but would welcome any sort of thoughts that, that you have either research that's out there or examples that you've seen on the ground of social capital actually being built in the areas that we're looking to reach into better serve. Maybe briefly on that front, I think I mentioned earlier, looking at some of those variables that are associated with high rates upward mobility, social capital being one of them. I think the kind of struggle that we have is that the current levels of social capital that we're looking to measure that are proxies for what I think we think of as authentic relationship building. So looking at Census Bureau, kind of, you know, responsiveness, you know, voting records, how, how many people are voting in a community. And so we're actually doing more research on that front. I think, you know, think more critically around how we define social capital, especially in the context of upward mobility. Right. Is it that communities that have more social organizations are really thinking about, you know, being able to create relationships across lines of difference, right. So places where, you know, low income families have access to or exposed to higher income families and vice versa. So I think really thinking critically around, right, what are those relationships that can really drive opportunity in a very tangible way are extremely important. And I think we can look at it on the program at a front too. I think a lot of workforce development programs, college access programs, you know, are really thinking about training an actual subject matter, but really building relationships, helping people navigate a lot of these systems that, especially the coming from low income families, they may not be familiar with. So I think, you know, we're working hard on some new research on that front as well. But I think really thinking critically around, you know, what the type of relationships are that can really drive whatever outcomes we care about as a community and thinking through how we can, you know, recreate those within our communities, but also integrate them into our different policies and programs as well. Thank you. Thank all of you for joining us. It was a really wonderful conversation and we apologize to anyone's, anyone who posed a question that we did not get to. We were so interested in the conversation. I think we have our own questions as well, but thank you all for joining us. It was such a pleasure. You know, I think as we go out into the world, I would really recommend and encourage everyone to think about ways that you can be working with other types of communities to build, build power and to build, build new policy approaches that can really benefit a variety of different places in our country. So thanks for your time.