Good afternoon, everyone. And thank you for joining New America National League of Cities in Stanford Legal Design Lab for our virtual event improving America eviction data. I'm Lauren Lowry. I'm the Program Director for Housing and Community Development at National League of Cities and National League of Cities represents America's cities, towns and villages. Like you would imagine, the conversation for cities, towns and villages over the last years has been keenly focused on housing affordability and housing instability. And in recent months, that conversation has been amplified due to the pandemic. And the question cities, towns and villages over the last months have been asking is how can we tackle the eviction crisis. And this set my team off on a journey to produce recommendations through a series of blogs to not only talk about the impending eviction clip, but also how to build a strategy to tackle evictions. And one of the blogs that we wrote was using data to understand your local eviction crisis. This blog came about because as you know, there's no roadmap as to how cities, towns and villages can't even begin to address the local eviction crisis. And this was our attempt at beginning the process. And I'm glad today that we can continue the conversation of improving America's eviction data, because it is so critical to the success of getting a handle of evictions, but this crisis that happened long before the pandemic. Could you please present the slides? Next slide. And so to give you a landscape, you know, about the problem with eviction data, there's no coordinated or national collection of eviction data. One third of us counties have no available annual eviction figures and even during the pandemic, we had data for only one fifth of renter households. Next slide. And we know the data sort of exists, you know, counting courts, they collect data as part of the eviction process, but that collection process varies. And even to the point if this data is available digitally. Next slide. So when it exists, it's not accessible. It's poor and inconsistent. It's not standardized. It's not linked to other data. It's not even collected in real time. And there are concerns with equity and privacy. And why does this matter. Next slide. Because we don't know the who what when or where we don't know where evictions are occurring. We don't know who's being evicted most often. We don't know if evictions are rising or falling. We don't know how much back rent tenants have to pay. And we don't even know if the order is working. And this makes it hard to one target aid to those in need to target outreach. To address racial inequities and evictions to spot and fix problems early, and to keep people in their homes and I'm really excited to pass it over to Sabia to talk about how we can go about thinking about this. Thank you so much, Lauren. Hi, everyone. My name is Sabi has anal by and I am a senior policy analyst at New America's future of land and housing team. Before we dive into our next two panels that really get at the, you know, the how and the, the why of eviction data. We can provide a high level of view of the eviction data system recommendations that New America, along with a host of other organizations co developed and released in April. So we can go to the next slide, please. Thank you. So understanding the issues with eviction data that Lauren just alluded to New America facilitated a series of workshops in late last year and early this year with a host of housing data and innovation experts and municipal leaders, all of whom have a slightly different perspective and need when it comes to eviction data. So these workshops really centered on three things. First, documenting all of the pain points and challenges with eviction data. That's not what an ideal eviction data lance landscape could look like and third presenting a framework for achieving it. So the eight eviction data recommendations that we released do just that they present a framework for improving the local and national eviction data landscape with the end goal of creating local eviction databases that feed into a national database. So these recommendations were co developed and co signed by nine organizations including New America, whose logos are listed here. But we can go to the next slide. Great. So, at a high level, the framework that we released has three parts. The first one is creating a federal or state enabling environment, and that really consists of different investments that are needed for local jurisdictions really to be able to take something on in a way that is robust and comprehensive so that this includes a significant amount of funding and robust technical assistance as well as shared data standards. So we're creating a local enabling environment. So in order for local jurisdictions, both at the city, or at the city level county level and state level to be able to meet the data standards and collect and aggregate eviction data they'll need to be able to conduct a comprehensive assessment of eviction data of their eviction data infrastructures that currently stands and additional data needs. But they'll also need to as Lauren talked about develop robust strategies to actually achieve those needs. And lastly, you know the the goal of all of the of of this infrastructure is really to create a network of local eviction databases that feed into a national eviction database. So that, you know, with, with the larger goal being mitigating evictions and the force displacement that results. So, you might notice that this framework does not opine on several significant issues like what level of government should be accountable and what kind of entity is the right one to aggregate and post these databases and in part it's because we don't necessarily have those answers yet. We of course have thoughts on on all of those things. But I think what comes next is engaging with many of the organizations and people listening today to think to really think through how to operationalize this framework into something that works for across local jurisdictions. So, you know, many of the components of this framework are already in place or even underway, for example, the creation of data standards or, you know, robust and comprehensive assessment of eviction data infrastructure at the local level. What's really needed is is systematizing some of those things and bringing all those pieces together in into a common roadmap as Lauren mentioned. So, this event is kind of a kickoff to that process really and we're looking forward to talking through all of these issues, more in our next panel, where we'll hear a little bit more about how we get from here to there, So, Margaret, I will turn it over to you to leave that off. Yes, thanks so much Sabiha and hi everyone so happy that you made it this morning or are watching this later. We're going to do a keynote panel right now where we talk about how we move from recommendations to implementation. So just like was mentioned by Sabiha and by Lauren. We have these great framework laid out of data that we need about current problems roadblocks opportunities. Let's talk about how we get to action, and we have two amazing guests here to spend 20 minutes with us and illuminate some thoughts forward. So first we have DJ Patel who's the former US chief data scientist under the Obama administration, and we have Cecilia Munoz who's the senior advisor at New America right now, and formerly was the director of the domestic policy Council, also in the Obama administration. So I'll kick off with a question and audience please feel free to put your questions in the Q&A feature, and I'll keep an eye on those two. So DJ and Cecilia, I wanted to kick it off to you. What are some good models or corollaries out there for when you have a relatively bad data system at the local level, but a lot of needs and federal interest in having a better data system. Do you have comparable war stories or examples that you can share with us, maybe DJ first then Cecilia after. You know, I feel like that question summarizes a good chunk of Cecilia's time together is, is how do you get these things to work. And, you know, like, part of the thing is, we have this incredible structure of the federal government that is able to leverage data in really effective ways, when it gets the data. But a lot of times that data by design is fragmented or structured in a way that is highly local. We have good examples of where this data is aggregated and collected some of that data is retail data around, you know, buying behavior helps us understand the economy. Other parts of it around traffic fatalities and this is data that really was started to be put in place after at the end of World War Two, and the depression time period where there was just no ability to say what's going on. But there was a lot of structure where this data is aggregated, collected, layered on each other, cleaned and brought back up. And what we've seen also on the other side of this is there's many places of data where it's just fundamentally, we haven't made that investment policing data around excessive use of force or what we think about policing and Cecilia and I got to work on a lot of those projects that we can talk about. But the other side is also gun violence, there's other aspects around mental health issues. And so there's all these things but the one of the threads that if you pull on over all these things are suddenly foundational, mazo hierarchy as data sets food, clothing, water, shelter. So, if we think of it that way, eviction data is foundational for us to understand what other data sets need to come together to help us understand and appreciate the problem. That's just 100% agree. And there are, I think, and DJ's named some of the lots of examples of the kind of messiness that you saw in the, in the presentation about how we there are the courts have some data and the, you know, counties may have some data and cities may have some data. There are lots of examples of sort of important information that would be really useful to be able to help people to understand our problems better to understand how to fix them, but where the data is messy and therefore you can't. So in some ways one message is, there are other contexts with this is true, but we can, we can fix it it's this is not insurmountable. It requires making an issue of priority, I think it helps as somebody who's worked in the federal government I think it helps a lot of the federal government makes it a priority and then makes both resources, and kind of specific information available to the folks who have who carry different pieces of this data, in order to, in order to get to uniformity and get to one place where data is being submitted so that we can begin to, to paint a picture of what's going on and I'll just say from my own experience. So I'm a Latina. I started a million years ago, working at the group that was then called the National Council of La Raza it's now called Unidos us. So we were in Washington 1988, we were still working off of the first census data which actually counted Latinos, which was in 1980, which counted us in any kind of meaningful way. So that meant, we couldn't tell our own story. We couldn't describe what the disparities were in our say our educational status or economic status. It was impossible to create a policy agenda for what is now the largest minority in the United States where we have data. And what we're describing with respect to evictions is the same problem right we know this is an issue, but we can't quantify it we can't talk about who it affects, or how we might address it, unless we're able to pull but you know data in some kind of uniform way so it's a critical foundational issue. So really, I have a follow up, I would love to hear an example of how to kind of unlock that federal interest leadership funding information release. So whether there's an informative example from another field or DJ if you want to add on afterwards about how to kind of leverage federal power to get local activity. And I can both go on all day about something called the police data initiative which we both worked on when we were in the federal government and right that was at a moment when policing questions of the use of force. It were as they still are a vital importance but the federal government is not the owner they're 18,000 different police forces in the United States, and they're local right so. Because it was a priority at the federal level. We kind of created incentives for to help local police agencies start to look at the data that they have. We urge them to make commitments just to identify three data sets to release to make public and began to provide technical assistance to help them assess how to use their data to make improvements. An example of the federal government deciding that something is important, and rather than waiting for Congress to pass a law and allocate the funds, just creating incentives and mechanisms to help the local owners of the data. Make it visible and begin to use it in a way that addresses a policy problem. And one of the things I want to add to this is coming is, it's very easy I think a lot of times for us to look and say hey let's just get this done with dollars or push money down. And what we found through this time period is there's lots of people who really want this to happen, but they don't either have the expertise or the experience to make it happen so you had plenty of police departments who were willing to open up the data but they don't know what that means and sometimes they're locked into procurement contracts that where the data isn't actually the cities anymore it's owned by some vendor. And so one of the things I think which we have to ask ourselves is also how do we capacity build at the hyper local level to now allow this to happen, because you know, these things are oftentimes at the local level or unfunded mandates for for teams and they need help. So here's a little bit on what can go wrong. Do you have any warnings to those of us working on eviction data housing data about things we should avoid traps other ways that we could spend our energy on productively. And so as a policy person who who on the issues that I work on, brings like a lot of knowledge to the equation, it is sometimes an obstacle when you can see the whole and like everything that you would need in order to address the whole, because it's a comprehensive approach for resource reasons or other kinds of reasons. So it helps to pick a lane where you can have some impact to show some wins to help convince municipalities or other owners of the data why it's actually in their interest to make it visible, or to do something different with it, and then expand outward from there I think sometimes we trip ourselves up when we try to fix everything. And we end up fixing that. Yeah, I would echo that you know we have a saying that we use during these projects which is prototype for one X build for 10 X engineer for 100 X. People often think of that as a technology frame. That's a policy frame to you know like one city may have figured out how to do it at one side is another may have another size and you got to kind of figure out what are the common things that you can use to scale that. The other part is, I think what I really emphasize to people is, don't try to solve like that. Don't Rome wasn't built in the day. And so, you know you can get into all sorts of how is the data perfect. And what really matters is your iterations speed on the data, we try to say the data is finalized as one data set. What we find is a more beneficial way to look at it is making it iterative and getting the cycle where somebody's using the data. If you collect the data but no one's using it. What good is that. And what happens is when you get this feedback cycle of other people using the data that helps you inform what data needs to be collected how can it get better and so it's an arc of progress that gets us to where we need to be. So these are some examples or stories about the, the actual relationships or communities that are involved, like how local jurisdictions might influence or work with each other or that kind of federal to local relationship, and how we can think about building that in the best way for eviction data. I'll throw a couple out there one, you know we're seeing examples of this right now around COVID in an incredible detail why because there's data that's just critical to manage this and there's so many different versions of this where this is going well and where it's breaking. Part of what I think I would highlight in terms of getting eviction data what we've seen is organizations like many of the people here are critical to acting as a catalyst for making it happen so so what's the number one thing. The way we got police data initiative going is honestly taking a whole bunch of people and slamming them together in a room and saying you can't leave until you come up with something. And then what we realized is people are actually far more aligned than they people thought that would be that includes police chiefs, civic activists, technologists, and you think well this is going to be, you know, really contentious it turned out, people were much more aligned because it was. These are sort of basic questions. Another thing I think which which I would say is to point to is specific analogies that we've seen is we have to ask ourselves, like there's there's versions of this where there's other data sets that may give us a proxy. You know the one that people often highlighted is Roger Chetty's work, and, and that his team on using IRS data in those cohorts, but there's a lot of other proxy data that can give us a signal. And then the final part I think I would I would just emphasize it's very easy for us to get focused on the data and the data sets. And, and one of the most important things to me is like, these are data points these are people, these are real, these people have stories, and we have to remember not to just categorize them in buckets, but to remember to tell their stories to remember who they are, and also deeply understand the pain or experiences they may have. And one quick example to DJ is very good points and that is for a time, our public interest technology project at New America had a project that was focused on opioids and we had a colleague who organized 12 counties, just because they were interested and we were all grappling with the problem of opioid use disorder in different ways, and help them share information about how each of them was approaching it and one county in one part of the country had figured out a way away to use data to pinpoint specifically when overdoses were happening they were able to pinpoint literally that that like overdoses were most likely to happen in particular neighborhoods in a particular population among males in a particular age group. And then so they use that information to then gear their response and organize their response. And just by sharing that one innovation that they had come up with, with other counties who were in the circle that approach began to move around right they were essentially a community of practice that was sharing information, so that each place wasn't inventing their approach by themselves. I think there's a lot of analogous power in that. So I have a question from one of the audience members about potential downsides or harms when opening up data. So as let's say more housing data is released or that people have been through an eviction and potentially that this might be part of the data that would be released, how that could be used against them how that could be used to do risk assessments screen. Otherwise harm future opportunities. Do you have other lessons about safeguarding and getting that right balance between open data and then protecting the folks whose data, or who the data relates to.  There's a couple things for those are interested Hillary Mason Mike with he's and I wrote a book about data and ethics and how to design some of these systems is free on on Amazon, the number of places, the key things that I would say is one is, you have to, you have to start putting things together. You can't see all the blind spots. So you have to do a few things one is get a team together of people who can read team this and that team needs to have a lot of good characteristics diversity life experiences, understanding how data could be abused, but also understanding what it means to be responsible in using that data. And then is as you're putting this together, you create concentric circles of working with this data so you try to do it with a small beta test if you will with people who are trusted, and try to see where things might go wrong, and then you expand it out. And then, as you're doing this you can't just release a data set and say, we're done. You got to own it, because something may go wrong downstream that you have to course correct or find issues with. But the best thing that you can do is just engage with a great community of people who are, you know, really thinking deeply about these issues around all the parts of it. Let's talk a little bit about funding and capacity building. Have you seen different models where it's completely bootstrapping and borrowing professionals who already have their salary paid elsewhere or other ways to unlock funding that can be meaningful, especially in the, these first phases of getting action going either at the federal or the local levels. There are different approaches. One is to identify places that already have, you know, somebody who's good at some aspect of this to help just identify what it is that they're doing to again, spread that information around others who might be interested in doing the same. I learned that it was not even always occupants of the same position in policing, for example, it was not always the same person in the same job from place to place to place to place to place who was the big innovator. And so one key is to find whoever a local innovator is in a jurisdiction that seems to be doing something right. Figure out what it is that they're doing and finding a way to spread that around that's like the lowest maintenance way. Obviously there's coming out of the crisis that we are all living through. You know, it is to be hoped that there are philanthropic resources that are interested, again, in, in helping build systematic approaches and helping build capacity to do this work well to create the models that can then be taken to scale. And then this is a really good moment to be having this conversation at the federal level. Right, we have leadership that we know is very interested in evictions and have been trying to extend the eviction moratorium, for example. And that is, that has some focus on this issue so both at the Department of Housing and Urban Development but also in the White House I think that and certainly in the Congress. There are allies to be, you know, made an advocacy to be built and models to follow either through policing. There is an interagency council on homelessness which touches on these issues which, at least in the Obama years I found to be very, very effective. It's always to be very effective in the Biden administration. So I think that there are structures at the federal level that can be worked with to create the kind of capacity that you're looking for. Yeah, the only thing that I might add, and apologies, there's some noise in the background because during a panel there has to be someone has to have construction going on. The thing I would say that is not working well is, you know, when you want something you say hey we have a problem and you say you get a whole bunch of volunteer people to come in and fight. Well, who owns a problem afterwards. And there's a capacity building that we talked about which is, you need, you need that institution together. And that is a perfect example of this. You've had incredible volunteers come in to help work on COVID issues, but we haven't invested in public health for a decade. So, so this is, this is a systematic set of failures over a period of investing. And that conversation I think is the ad is, what does it mean to capacity build at the local level so you get the right kind of people in there, you know, as a technical technologist, and just, you know, there's a great book that Cecilia's colleagues, Sarah McGinnis and Anna have written on public interest technology which I think is essential reading, frankly, on this topic of how to do this properly at the local levels. Last question before we go to the fireside chat portion of the webinar. If you were in charge and you were made kind of the federal lead on improving America's eviction data scape. What would be one of the first actions that you would take or one of the first priorities to aim at Cecilia first, sorry, and then DJ. So, I would that the convening power that you have at the federal level of the White House DJ and I learned is is in some ways can be frequently the most important thing. So I would, again, work with people like some of the folks who have organized this very webinar like folks who have made themselves experts in the field who have come up with specific recommendations. I would like to figure out what's actionable without legislation because legislation takes time. Start with what's actionable without legislation while working with Congress to develop legislation. But in particular identify some places where you can make progress where you can as President Obama used to say like move the ball down the field. You don't start with perfection you start with where you can where you can make progress. So identify what those places are to begin to develop a sense of success and possibility, and to further develop the kind of infrastructure among the organizations that and the jurisdictions that want to make progress right you build layer upon layer, and at the federal level you can help identify what those base layers are. Yeah, the only thing I would add to that is, you know, get commitments. There's an amazing there are so many people who want to help on this problem. We just don't ask or they don't know what problem they need help with. And if you kind of say hey we'd like you to work on this or help on this we've seen this like with Airbnb and refugees and so many other great organizations. There's a lot to bring people together. And then the other one I would just emphasize is, we have a unique opportunity right now, given everything that's happening and so much interest in public policy to really think about what the training is that's required and the case studies are required for the next generation of public policy leaders. This has made me very optimistic that there are things to be done without major budgets and major legislative changes and it's just terrific to hear your examples and stories thank you so much for bringing your expertise to today's keynote I'll just give a round of applause. Thank you DJ and Cecilia. So we're going to turn it over now to the fireside chat portion with my colleague Lauren Lowry from NLC facilitating, and we're going to dive in to some of these local areas where good things are happening so Lauren, I'll hand it over to you. And thank you for that conversation you, DJ and Celia did a nice job of setting us up for these fireside chats with, which will ask the question what happens with good eviction data. So these are short conversations with creators and users around eviction data products and we'll be hearing from cities and states around the country as they grapple with this question. First up is Houston, Texas, and I'll pass the mic to Jeff. All right, thank you so much Lauren. We're super excited to share what's going on in Houston and Harris County with this national group here. We've been working with eviction data quite a bit, and I'm joined by my colleague Jen Rice from Houston Public Media. Jen, do you want to introduce yourself and talk a little bit about what you do. I would say I'm a reporter at Houston Public Media that's the Houston affiliate of NPR. And I did not really think I'd be spending the last year, like really drilling down on evictions but I'm glad that I got to work so much with Jeff. Thanks so much. Yeah, I'm glad that we were able to work together. Maybe the tables have turned a little bit because usually Jen's doing the interviewing. And so I'm not quite as skilled as she is at these questions but hopefully I'll do my best here. Maybe I can start by just setting the stage a little bit about Houston. Most people who don't live in Houston don't think about Houston but it's the fourth largest city. It exists in the third largest county in the country Harris County, it exists in Texas, which is very, the laws are very property owner friendly not very renter friendly, very libertarian focused state, but the city itself is very progressive and has millions of people who are looking to draw attention to this pervasive problem that existed even before the pandemic. Jen how did you get involved in in covering evictions you didn't start on this beat. So I cover city hall. So it was from that vantage point that I noticed two things happening that kind of put Houston in a remarkable position I noticed we had exceptionally weak rental protections during the pandemic specifically, and we had exceptionally good data, thanks to the general advisors dashboard which this is not a commercial for but it's truly incredible and I really can't imagine my year without it. Thanks so much. I'm Jeff I'm with January advisors so that's a, it's a commercial for our website I'll put the link in the in the chat but I think it's extremely interesting because we're so fortunate enough to live in a city that makes this data available both at the city or at the county level. So I think we extract a lot of really good insights from it and make it available to people like you, who are an expert and kind of understanding what this is telling us from a narrative side. What do you think, what are some of the ways in which you use eviction data in your reporting to kind of tell this story. So I've been covering this in depth all year. And so I think for people who regularly listened to Houston public media, my hope is that they know three things by now, they know that the CDC order is not stopping most evictions here. They know that individual judges are playing a big role in who gets the CDC protection and who doesn't. And they also know that Houston area elected officials made a policy choice several policy choices to allow pandemic evictions and none of those things that I believe that our listeners know would be possible really without the data. One example would be, I'd say in the fall when the, when the CDC order first started, I was like driving around to all these different courtrooms across the county. And I remember the first week, attending 100 hearings and only one of them was abated by the moratorium. And obviously that's changed. When you came out with data in like December saying that, you know, 10%, basically around 10% of cases were being abated. It was like a, like a light bulb moment for me because I had been like driving around and seeing it, but seeing your numbers I was like, Oh, this is this is really a game changer for me. And then another example I'd have on how I've been using it is we just saw in Houston. The mayor finally decided to pass a grace period ordinance, which we've seen in other parts of the state. But it was interesting because, you know, advocates have been asking for it all year, and when he finally did announce that he was doing it, you know, I read the ordinance and I was like, That's funny because this actually is pretty much just the CDC order, like they just kind of copied the CDC order. And then the mayor said to all the council members he was like this ordinance puts evictions on hold for six weeks. That's what he told people he said this ordinance puts evictions on hold for six weeks. And I was just like, I don't know what's going to happen. But I'll see you in six weeks. And I'm going to call Jeff, and we're going to find out how many hearings there were, and how many filings there were, and how many of them were abated, and there will be a story in six weeks, and we'll see if that claim was true. So that that's the kind of stuff that I cannot do without, without the data. And so I think it's a really interesting point and it harkens back to what DJ was saying in the previous panel, which is that there's a person, and there's a family behind every single one of these eviction cases. And what I really like about your reporting is that you kind of marry together the human element, telling these stories of, of just tragedy and trauma with the data element, oftentimes when I'm alone in a conversation, talking about eviction and trying to communicate scale, saying we've had 40,000 evictions since January of 2020. You know, there's a can be weaponized data can be weaponized against the data person and saying well, these are people let's not lose sight of that. How do you find that balance of communicating scale and communicating the actual the elements that make up that scale the trauma. I would say one of the people I spoke with over the past year that had a huge impact on me was this young woman who was in eviction court she she was being evicted and the judge asked her, she said that the CDC moratorium applied to her that she was eligible for protection and the judge was like asking her, Well, couldn't you just go live with your parents, and she was like, I don't have a relationship with my parents I can't do that. That that whole line of questioning was really uncomfortable for her. That was the only reason he found for why the order didn't apply to her. And he just didn't listen to what she was saying and you know rule that she could be evicted and so getting to talk with her afterwards about how that felt for her. And that's like transformative for that story because you know we have the numbers on the fact that you know if she had just gotten the other judge in the same precinct. She wouldn't have been evicted, because he's not actually hearing eviction cases so you know it's just, it's one of those moments where I was amazed by like her strength that you know she was willing to kind of say like this is like powerful judge did and this is how it impacted me. Yeah, so that's something I'm not going to forget about this year. So I'll just close I know we're coming up on time and want to thank New America and everybody who's speaking here for giving us the opportunity to expound on Houston and put it in a national spotlight. This is a bit of a loaded question but I'm just curious about your, your response, based on all the information that we have all the good reporting that you and others have done over the last year. The attention that all of our policymakers are paying towards eviction and the boiling of the ocean of stopping evictions in Texas. How optimistic are you that when we continue to use data that that will actually move the needle a little bit on policy issues. So, that's a great question that is the question. On the one hand, I would say, first of all as a journalist like I don't, I don't ever say what should happen. My job is just what is happening to really capture for people what is happening and showing them through a mirror to like where you live this is what's happening that's my job. So I'll just say that first of all, but, but it I believe everybody wants eviction data to get better so we can do better reporting and one thing I think would make it much, much more compelling and more effective data would be if we had a better sense of actually how many evictions are taking place because you know the data we have from courts is just like a small fraction, it's just the courts, it's just the cases that are filed like we have no idea how many notices to vacate are actually posted. And that's something that I think probably could be fixed pretty straightforward, you know if you had like a state level form that was like track that was like this is how many notices to vacate have been posted in Texas like, I can't even imagine the stories we could tell. We don't have data on how many notices to vacate are posted because like we have no idea how many evictions are taking place and I hope that one day we'll be able to tell stories like that. Well thank you so much for joining us today Jen I really appreciate it. And thank you everybody for listening I'm going to kick it back to Lauren now. Thank you Jeff. Thank you Jeff and Jen that was a very powerful as to why we need eviction data to tell stories and tell compelling stories and answer those questions I mentioned earlier, who what went in there. I'm excited to kick the conversation to Orlando, Florida to hear about what is happening in the community. So I'll pass it to Caitlin. Thank you so much Lauren and thank you to the first, first fireside chat here I think it's a it's a great transition to hear about the individual personal stories and then I'm excited to talk with you, Frank, a little bit about your role in Orlando and and how you're telling these personal stories but you're also coordinating the entire central Florida response to housing so I wonder if I could hand it over to you to sort of lay the landscape of what's happening in central Florida for us. Sure, fantastic so thanks so much Caitlin and thank you to our friends at New America and the League of Cities, and all the other great hosts for this is a wonderful event it's been a fantastic conversation so far. My organization Bright Community Trust works on housing access and housing affordability issues and related community development work in several regions of the state of Florida house that you see here in my background is our central Florida affiliate so we kept a careful eye on what was happening with evictions as well as on federal supports right the cares act dollars that came down the federal unemployment supplement and so forth. But when it became obvious by say mid summer last summer that we weren't going to have any additional action from Congress to continue to support particularly people who are unemployed. We saw those dollars run out at the end of July. And at the same time we're watching at that level we all had state level moratoriums and then some cases city or county level moratoriums. We were seeing this month by month extension, and we would get down to the 30th of June, and see the moratorium extended 30 more days and kind of all hold our breath till the last second to see what's going to happen. We were talking to colleagues in August and said, we need to have some kind of response it were here because these eviction, sorry these unemployment benefits are going to dry up. People are going to have no resources to deal with the potential for eviction and the rental assistance programs are trying to get up and running now but we don't have much of a safety net here. So in September last year we convened a really broad swath of the community that's responding to this eviction crisis so that's of course our city and county partners, particularly in the three counties around the Orlando metro area. That's our county court system. That's also our legal aid and community legal services folks, but it's also on the other side of the table the apartment association and the landlords. And then a whole bunch of nonprofits that work in this sector, pretty broadly around the table including like our continuum of care, our public housing agencies. Our United Way and a bunch of other providers, so that we can have a 360 degree conversation around how do we prevent as many people getting evicted as possible and so glad that we did it we've seen all kinds of changes coming our way but it's let us really share best practices back and forth respond to the data kind of on the fly. We had a meeting this morning and we're seeing, you know, news coming down from Washington guidance on this state and local fiscal support program the $350 billion that could provide additional housing support. Things are changing so quickly we've got to be able to respond rapidly. And this lets us do that. That I think that you know you pulling on that thread of you know having the 360 response and really intentionally building in so many different voices to this conversation. Can you expand on that you know where where has has the conversation about data been most useful is it getting people to the table is it directing people where to put the, you know their their interventions most you know sort of effectively how how has data kind of played into this this overall response. So we were fortunate that on our, our very first call kind of as a benefit of relationships. And with our judiciary we were able to get the county court judge who oversees our evictions docket in Orange County to come and bring us live here's how many evictions are getting filed at that point it was a managing but not non existent and to have the conversation about what's actually happening in the process because there's an addiction filing but that's different from a judgment and a rid of possession right and and as we came to understand more about this data. We were also getting data from our friends at the apartment association who were able to bring to the table. You know, their constituents are the larger landlords in the community so they're able to tell us how many evictions do they have underway, but also look deeper into the data because they have information on how many tenants are on payment plans that are not being evicted but are in some danger of being evicted. And as we went further down this process we realized that there were more granular bits of data that we could discern that are helpful in in focusing our response so the apartment association for instance started to track last fall information on how many leases were being abandoned. Right, I know there's just no way I'm ever going to be able to catch up with this. There's no prospect of my job coming back. Here's the keys. I'm out the door. In a lot of cases that's a negotiated settlement kind of process that's preferable to having an eviction file and having that on your record so you know we were able to start tracking some things like that as well as start getting a little bit of data on how often the CDC moratorium, or a CDC declaration is being made on the behalf of a tenant helps to have our friends from legal aid and community legal services on the conversations for that. We still feel like though there are a lot of gaps there that the reporting that we're getting is kind of some headline numbers but we don't know how many evictions were filed. And then somebody reached out and got emergency rental assistance dollars and made up that deficit. It hasn't been released how many of those are still out there versus how many are pending and going to move forward with a final judgment we're even starting to hear of cases where things have gone as far as a final judgment, but an actual eviction physical eviction can't take place with the CDC moratorium in place.  Now they're in a new tendency. But in a couple of cases at least our friends at legal aid are telling us landlords are trying to go back and use the previous judgment under the previous tendency. And the judge says no wait a minute you can't do that. This is a new instance of the lease but how often does that happen. We don't have data we have anecdotes right and what's that old adage that the the portal of anecdotes is not data. I think, yes, I would say the perhaps the natural language processing researcher in me would suggest that that could be data. I'm a data scientist and and obviously that that's the first tool I reached to when I think about how we might solve a problem. But I know in conversations that we've had something that's been illuminating is not not only what is represented in the data and Orange County does have one of the better data systems but also starting to understand what is missed. So I wonder if any of you speak about people who are applying for rental assistance need rental assistance but are they representative of the people who need it the most. So I wonder, kind of in our last, our last comments here, you could elaborate on, what would you like to see in in the data and what what are the stories that you're hoping to tell to people who are who are building out these systems. And a lot of times in rental assistance programs with cities and counties and and we're hearing this in our work in other parts of the state as well as from other colleagues is that by and large the people at the front of the line to get rental assistance are more affluent. They lost a job, but they're more likely to have high speed internet at home. They've got a printer they've got a scanner. They have their financial documents in order so that it's fairly easy for them to print out what they need fill out the form, sign it scan it back. They're good to go they get their dollars they're at the front of the line. The communities that are most vulnerable though our communities of color, women headed households, seniors, families with limited English proficiency. These folks, most need these dollars and are least likely to get them right there. Less likely to have a good high speed internet connection at home, very unlikely to have the printer of the scanner and everything else you need to fill out and sign and scan back documents. So it needs a lot more outreach from trusted community partners it isn't sufficient to put up a website. What we need is a church in the community a child care center of food pantry. Some other kind of a neighborhood nonprofit that has these relationships that can go work with people one on one get that paperwork filled out and so we're we're hopeful to see the next iteration of this show, not just what does the data tell us about where are the communities that need to help, but where are the community assets right how do we map who can help us get these who's on the front lines in these neighborhoods that can really help us intervene and get the resources to the people who are most vulnerable and both need them. What are powerful statement to say not only do we need the data to tell us where we need to go but we need to enable individuals to help their communities do that that work as well. I handed back to you, Lauren to pick up on on that with from the fireside chat conversations to give it over for a last, last couple. Thanks Caitlin and thanks Lawrence was great. No problem thank you thank you Caitlin Frank. And I want to say it out loud, what a franking Caitlin was stressing we need to center equity in the design and implementation and data, because we need to not only look at the racial and ethnic groups that may be present and helping those who may not have access but that that counts for people with limited English, who have disabilities. I'm excited to kick the next conversation to to learn about what the state of Connecticut is doing Peter. Hi, thanks. My name is Peter Hepburn, I'm an assistant professor of sociology at Rutgers University New York and a research fellow at the eviction lab at Princeton University. One of the things, one of the several tools that the eviction lab developed in response to the COVID-19 pandemic was the eviction tracking system which was a way a tool for monitoring eviction filings in real time in jurisdictions around the country. And one of the groups to whom we turned for support and for for assistance in finding those data was the Connecticut Fair Housing Center, and in particular Salmone so Salmone can you introduce yourself. Hi, thank you so much Peter and new America for having us. So, I'm, my name is Salmone. I'm a staff attorney at the Connecticut Fair Housing Center. And I am an urge with some programming skills and very interested in data. And you've been collecting eviction data in the state of Connecticut for for how long now. I've been collecting it since roughly 2017. Prior to that, the eviction data in the state had a number of the problems that we've heard about there was no consistency there were jurisdictions without electronic case files. And even where there were electronic case files there wasn't a unified system. So, as of January 1 2017 that's the first time there was really statewide electronic data available. And so we started collecting it at that point. We were basically do downloading one time snapshots of the data to do the type of demographic analysis that that was actually inspired by the work of Matthew Desmond in the lab. So, yeah, so that's what that's what we're doing at the time. And then in in response to the, the pandemic and the sort of shifting landscape of eviction during this crisis. How, what, what have you been able to do using those data. At the start of the pandemic, and I thought it might be useful to as the eviction lab did start tracking real time eviction trends. So I wrote a script that that basically keeps the data, our local version of the database up to fully up to date so it downloads and parses and imports the data and then manipulated so that every morning we have a fully up to date analysis of eviction records that is relatively straightforward to query query and with this we were able to, for example, make data available to the eviction lab so Connecticut could be added to the covert record. And that I would say the first truly effective use of the data during the pandemic came in August to early September when Connecticut courts began processing previously filed cases again. And so the moratoria were preventing most new fight eviction violence with notable and unfortunate exceptions, but previously filed cases were starting to move forward again, and the courts were beginning to or threatening to issue executions or procedures that would allow a Marshall to to put a house out of a family out of their house. So we were able to use our data to generate a list of cases that were essentially teed up for those executions to be issued. So that's those spreadsheets with the major legal services agencies three major legal services agencies in the state that do housing work. And they divided the list by geography and contacted the every, every tenant households that was at risk of them and imminently being put out of their arms. And so we provided information about the CDC moratorium which is brand new and people didn't necessarily know about it, and also a copy of the CDC declaration. I heard from several legal aid folks that that it was quite effective, the number of callbacks they got were significant and a couple folks told me it was the most effective form about reach that they had done to date, because it was so targeted. Just such a such a great example of how, like, really targeted outreach to the places in the people in most need, like can be effective and that there's the capacity to pull it off if the data are there. So that that just knowing, but knowing where you need to expend those efforts is so important critically important to doing this well. Yeah, absolutely and I think, you know, like if you're if you're trying to reach the people who not only are at the greatest risk, but who you know you can help. So that there is a tool that can assist this person, and then I think obviously that's, that's better than just like sending out blanket information about people's rights to every single kind of which probably doesn't have a huge effect. I wanted to talk to about sort of like the longer term use of these data and sort of what you see their their potential or how you envision their potential both for for legal work and for advocacy work moving forward. So I'll start I'll start with advocacy work that the data have actually been been quite useful and advocating for various policies and legislation. And to give an exciting example there's a there's a growing movement and connect it to guarantee legal representation as a right to all tenants facing eviction. So in support of that campaign we were able to generate good data on basic facts like the percentage of tenants with council and the percentage of landlords with council to more granular information that that sort of shows the impact of having an attorney on the outcome of a case. And that data has been used to lobby legislators it's been used in the media it's been it's been sort of widely reported and yesterday actually the the Connecticut House of representatives past right to council bill and the governor has already announced that they intend to allocate $10 million a year over the next couple years which should be sufficient to guarantee a lawyer to most tenants. We should make it only the second state to guarantee the right to counsel in eviction cases. Yeah, I think a couple other states past past legislation this session. But, and I'm not sure precisely where they are in the process whether the legislation has been signed, but that's, yeah, it's very exciting. And then there's also a way that these data could be used for making kind of broader Fair Housing Act claims right. So, so actually this is what we had in mind initially back in 2017 and, you know, stuff happened so we haven't actually completed this project but our, our intent is to build a disparate impact case based on eviction record screening. And so basically when someone applies for an apartment, we've heard a couple references to that screening already today but when someone applies for an apartment background check is typically done and, and if there's an eviction someone's history very often that just leads to, to blacklisting without any sort of details about whether that eviction case actually shows that a tenant or gives any information about whether a tenant would be able right now to meet the obligations of their tenant. So, as the eviction lab has demonstrated, people of color and women are significantly likelier to face eviction. There's a consequence of that any sort of screening policy that limits access to housing based on an eviction record has a disproportionate effect on families of color and women. You know the analysis doesn't end there the idiot and without getting too into the weeds landlord would be able to to survive a challenge like that by showing that the policy is justified that there is a non discriminatory substantial justification for the for the policy. And if, if someone's eviction rate, let's say someone's eviction was withdrawn or dismissed. I think the landlord would have a hard time showing that that there's a justified basis for using that eviction as, as the basis for denial so. So we're, we're building that case. And yeah. Perfect. I mean I think that's points to both how, how these data can be used in the immediate short term, but then can also be critical in answering some of the bigger questions that could lead us to reform how we, how we think about how eviction can and should be used, and how accessible it should be for for landlords. We should probably turn and let to leave some time here for some Q&A. So I'll hand it back to Lauren. I particularly liked your point about targeted outreach with data we're able to have targeted outreach and reach those and greatest needs. With that I'm going to turn it over to Sabia to kick us off with the Q&A. Yeah, thank you so much Lauren and thank you to all of the panelists really for sharing those great examples of how data has been deployed at the local level and just also sharing wisdom from, you know, how to implement some of these, these, these data systems. So I wanted to ask a couple questions of the panelists about, we've had a few questions come in about data privacy and safeguards that would come along with the push for more accessible data being available to the public. And this is certainly a huge issue and component of that would need to be worked through and I know a lot of organizations and people are thinking through these issues really carefully but specifically as it relates to, you know, some of the, some of the, you know, really when when linked with other data, the details from court record data can be reveal highly personal information. And there's not a lot of current eviction data systems that have sort of permissions and access levels in place to sort of differentiate the type of information available to different parties I know that there's a couple of initiatives that are working on that which I'm happy to share in a bit but would love to hear from from any of the panelists is if they have thoughts on the question of sort of data privacy and and equity. I'm going to have Margaret if you want to, I'm going to call on you to maybe share some thoughts given I know at the at the legal design lab in your role there you're you're thinking a lot about this issue. Yes, and I think we're trying to balance just what was coming up with someone and Peter and having really effective targeted outreach and getting to the right zip codes if not the right household as early as possible. But also making sure that that same kind of targeting cannot be used for those with less public interest purposes. So there are, I mean courts have been innovating in the space. I mean, even if there are a lot of interesting experiments around the country around masking around ceiling around protecting that kind of personal data sorry kids screaming in the background. So I think that as we bring in our court partners, they have thought a lot about these kind of collateral consequences are down the road effects of releasing information. So like the state of California has its courts have been very very focused on ceiling and masking protections. So if we have those kind of policymakers in the room with data scientists and folks who can dig through ways to still make that data operational but without those kind of identifiers coming through I think those are the conversations we need to be having. Yeah, because I think there has been a lot of policy making work on other areas, aside from addiction that we can borrow from in this space. Yeah, thanks so much Margaret. And I'll just add to that, before I see if anyone else wants to jump in with their thoughts. You know one of the, one of the groups that co developed these recommendations with us was the Georgetown laws Institute for Technology law and policy are there in the process of developing a civil justice data common so it's broader than just eviction data it encompasses all civil legal data. But my understanding is that it would have sort of different differing levels of access for, you know, people have different relationships to the data. So in, as Margaret said there are a lot of groups thinking through this issue. So I'll drop a link to the civil justice data comments in the chat. And I think one of the challenges for all of us here is to really figure out what kinds of questions we want to ask, because that will help us answer how we have a data governance process for private data for example, in civil court cases it's very rare that you know the transparency of the defendant because it's not reported it's not collected, especially if it's a contractual dispute like a lease. So we use proxies we use geocoding the defendant address to then understand the census tract or map the census surname to the name of the defendant, and those are imperfect. So if we solve for that the root question which is, how is this impacting communities, we might come up with different solutions that, you know, don't take on the sticky problem of how PII gets released and how it gets control. Absolutely. Does anyone else want to opine on that question? Okay. So another question came in from a participant that said I'd be curious on any perspective on sharing legal services data. Lawyers and lawyers often tend to be risk averse and cautious around sharing the data understandably so. Are there successful ways to bring them into the fold. I think a natural person to start with would be someone. And I also actually wanted to build on that question, someone earlier in the chat had asked how you, how you are able to access court data so if you want to also touch on that. So another part of that are judicial branch makes the data available by subscription $600 a year. So it's fairly straightforward to get access to but it's it's in a format that that requires some work to be able to actually use as far as legal services data. So the question is about like their client files, their case files, that sort of data, and I think there is the potential for really interesting work around using that data I haven't actually like engaged in it and I don't know the extent to which it's connected but they have in many instances significantly more granular information about person situation about demographics about, you know, household composition about other things that are happening in people's lives and they're probably. Yeah, I think I think with that information you can you can supplement the eviction data to be able to, to find other trends and find, find, or I guess just investigate to interesting investigations and follow up from there. So be if you don't mind my chiming and also, I know from conversations with our friends at Legal Aid and Community Legal Services. They're seeing a relatively narrow stripe of the data because as as one of their attorneys pointed out to us this morning, they're not likely to touch a tenant who has a good experience of the rental assistance program right if you get a three day notice on and you go on the county's website and go find the assistance program and get some dollars and get your landlord paid and get caught up. You're not likely to touch Legal Aid or Community Legal Services so they're farther down the path in more contentious cases but the data that they would have I think is colored by who they're touching the system within kind of the broader context of evictions and rental assistance and eviction prevention. Yeah. Yeah, thank you for that point. Um, so I wanted to ask kind of a to sort of close us out here ask kind of a big question that I think Jeff you had you and Jen had you had alluded to kind of this tension oftentimes between between access to data and sort of creating a more just system that we want to see when it relates to as it relates to housing and and I'm curious if if any of you have thoughts on sort of the, you know, the short term need for data to protect tenants during kind of, you know, during things like the pandemic and you know Jen you talked a lot about how it was really effective to have data to be able to show that the CDC moratorium was not working as intended. You know so we have all these use cases of why it's it's really really important but I'm wondering if we could speak a little bit to the tension between the need for better data to sort of improve some of these systems that I think we all believe are fundamentally broken versus the larger drive towards just sort of creating a housing infrastructure that is, is more just and some of some of that work doesn't necessarily stem from data but might stem more from, you know, things, you know, things like, you know, creating, creating more equitable housing systems and you know, universal programs and and income and things like that so just wanted to close us out on that really big question and see if anyone has any thoughts to offer. I can offer something very brief. One is that you know, in order to quantify the scale of the system, you have to have data. And if you don't even have that data, then the scale of the system is surprising when you see these numbers and you break them down. I think that's the level that we're at at least in Houston where a year and a half ago two years ago when you talked about eviction as a policy issue, you were laughed out of the room. Now it's a primary concern so the, the, the movement of government has kind of gone in that direction towards a more equitable and just housing system but from a temporary measure standpoint, rental assistance things like that. I'm really curious about how we can continue to keep up that pressure continue to get better data and continue to quantify the scale post pandemic so to speak. I believe that we see so much of our eviction filing data is at a county level, but you know I think about that wonderful displaced in the Sun Belt report that New America did. When you drill down to the census tract level, it's clear that at a county level one in 50 tenants is facing eviction, but in some census tracks that are predominantly historically black neighborhoods and continue to be majority black neighborhoods, it's one in 10 it's one in seven it's way above the county average so we need that more granular data. And if we could update that data, so that we could show the crossover between eviction filings and rental assistance, then we could show here's the gap in getting the dollars to the communities that most need them and really drive toward housing equity because that's the piece I feel like is missing here. I loved what DJ and Cecilia were saying on the first conversation that that we need to get something going quickly. You know that's better than having perfect data, three years from now when we're past the pandemic. Let's get something that points us in the direction of really driving toward housing equity quickly and then adjust as we go as we get better data. Yeah, absolutely. And just jumping in here, I would say why we need better data. So we know what services to provide you know rental assistance was mentioned but diversion strategies mediation, you know without the data, you have duplicative services which is not helpful and then people are not getting helped and people are getting help from the system. And you have this never ending cycle that begins and so you're just throwing money at a problem. But if we start now, building out the system, we can have a more just housing system where people are. Not only services, but most importantly, cities, towns and villages, they have the toolboxes to help people, not only cities, towns and villages but counties and states and it's very important to continue to have this conversation, but begin putting down strategies that are standardized and people know what they're doing we're creating the blueprint. Yeah, definitely. Thank you all so much for those remarks. I think we're at time here so I just wanted to take a moment really quickly to thank everyone so much for attending this event. As you can probably tell we could have probably dealt into any of the issues raised today for hours on end. And we plan to do that in the future. And I wanted to thank the panel all the panelists who spoke today for sharing their experience and their knowledge with us. We see New America and National League of Cities and Stanford Legal Design Lab. We look forward to engaging with you all further to build on your expertise to to really start to move the needle and bring all of these pieces together as we talked about. So we will certainly be in touch. And thank you so much.