Data-Smart City Pod

Recast - Driving Racial Equity through Data and Mapping

Episode Summary

In this episode of Data-Smart City Pod, Professor Steve Goldsmith interviews Elana Needle, the director of the Racial Equity Anchor Collaborative, about advancing equity by visualizing, tracking, and sharing data on issues like census responses, voter suppression, and police accountability.

Episode Notes

In this episode of Data-Smart City Pod, Professor Steve Goldsmith interviews Elana Needle, the director of the Racial Equity Anchor Collaborative at the Latino civil rights organization UnidosUS. The Anchor Collaborative is a collection of national, multi-racial organizations that advances equity by visualizing, tracking, and sharing data on issues like census responses, voter suppression, and police accountability. The Collaborative is intent on identifying and repairing the racist power structures that have disenfranchised millions of Americans of color, while best directing their funding in a data-driven way.    

Music credit: Summer-Man by Ketsa

About Data-Smart City Solutions

Data-Smart City Solutions, housed at the Ash Center at Harvard Kennedy School, is working to catalyze the adoption of data projects on the local government level by serving as a central resource for cities interested in this emerging field. We highlight best practices, top innovators, and promising case studies while also connecting leading industry, academic, and government officials. Our research focus is the intersection of government and data, ranging from open data and predictive analytics to civic engagement technology. We seek to promote the combination of integrated, cross-agency data with community data to better discover and preemptively address civic problems. To learn more visit us online and follow us on Twitter

Episode Transcription

Steve Goldsmith: Hello. This is Steve Goldsmith, Professor of Urban Affairs at Harvard's Kennedy School. And you're listening to Data-Smart City Pod, where we bring on top innovators and experts to discuss the future of cities and how to become data smart.

Steve Goldsmith: Today, we have a really interesting podcast that involves two organizations, actually multiple organizations, working on the connection between how you use spatial analytics and visualization to advance equity. We have with us Elana Needle, director of the Racial Equity Anchor Collaborative of the Latino civil rights organization, UnidosUS. Both these organizations have been busy using data, mapping, visualization tools to advance equity. Thanks for being here. You were telling me before we started about your personal path from school buses to social services to where you are now. But just give us a little bit of what is your first view into the importance of visualizing data, not just using data, but visualizing data? And I want to hear a little bit more about the important work you've done on census and voter rights. But let's just start with this GIS spatial information. Kind of how did you learn it and why do you think it's important?

Elana Needle: Great. Thank you so much for having me on the podcast, Steve. It's a real pleasure. I was introduced to GIS and visually mapping data way back in the early 2000s. I was a master's student at Tufts University. You may have heard of it, right down the road from Harvard. And we were introduced to the software itself, but actually walked through an exercise in which we were able to visually place incinerators and then also layered in demographics. And so it was the first time that I could actually play with the data and then see what the impact is visually of having these incinerators in communities where largely people of color lived. And so you could do that mapping with anything and you can discover all sorts of tools. But you can talk about data and you can say 20 percent of incinerators are placed in African-American communities, but it's a whole different thing to actually see it and to be able to tell a story with both the visual and the data itself, and also the writing that you can write about that.

And now we have super-advanced technology. You can make things like story maps and you can actually take a reader through a journey of the data, which I think is just so integral in allowing policies to be evidence-based and research to really dig down into the communities that it's supposed to be looking at.

And so, when we had the opportunity to partner with Esri for our current project -- we are a collaborative of nine racial equity organizations, a bunch of multi-racial and a few serve specific communities -- so we have a very large number of communities that we about and represent. And when we talk about data, it's informative, but in our ability to use Esri and actually look at our network and then look at things like census undercounts, for example, median income levels, we're really able to talk about our communities in a much more nuanced way.

And so, we were able to map, using Esri ArcGIS as the software, undercounts from the 2010 Census using two data streams. And most of the other undercount maps only used one data stream. So we had a much more nuanced look into targeted census tracks and cities and where the undercounts actually were. And we layered in demographics of our communities. And we also were able to lay in our Anchor -- we're the Racial Equity Anchor Collaborative, so we were able to layer in our infrastructure as well. So we could see where we had folks on the ground that could actually do the work and reach out to those undercounted communities to try and get out the count. Our on the ground implementation was in Florida and Michigan. And we were able to use mapping that we had created to also geotarget ad buys. So we could actually drill down into El Paso, Texas and see which census tracks, for example, had a high undercount of Latino communities, of Asian communities, and then really target our ad buys to that. So we're not "wasting money" on areas that have already responded.

Steve Goldsmith: That's very helpful. Let me take that apart for a second and ask you one question in two parts. So you have this GIS spatial analytics, and you're using the data for targeting, whether it's to get people to vote or register or to be counted in the census. So that's one, I think is what you're saying. But another, two, might be how do you use the visualization of the data to cause people to act, whether they're public officials, or…how do you use that to improve the narrative?

Elana Needle: Yeah. That's a great point, Steve. So we're working on another project with Esri, which is in its early stages, but it's been so informative. The process itself has been super informative. So we're working on sending out a survey to jurisdictions to understand their police budget from soup to nuts. And as you can imagine, there are a lot of jurisdictions around the country. And so we've been actually doing some data visualization initially to just figure out where they are, what they look like, are they in proximity to high profile police encounter or shooting or death? And so that process itself has allowed us to zero in and target specific jurisdictions where we really want to hear from. And we're hoping that the data that we get from this, both on the jurisdictions that decided to reply and the ones that didn't, right, because those are both stories in and of themselves. We're hoping that we're able to use this during the next ledge process as cities, states and localities are actually going through what, in 2021, will be a rough budgeting process in our current economic environment, that we'll be able to show them visually “this jurisdiction has X amount in their police budget and Y amount in their mental health resources or their substance abuse or their public education”. 

So really tell a story through the data and utilizing, A, at a minimum during their state ledge processes. And then also for us, buttressing the narrative around defunding the police or police accountability, whatever the term is that you want to use, having a much more informed discussion with robust data and visualization nationally, I think will allow us to push jurisdictions from the local, the state, regional, et cetera, to have a much more nuanced understanding of their police budgets and what it looks like.

Steve Goldsmith: One of the interesting things about their cloud tools is the ability of one jurisdiction to take advantage of what you've put together, right, either adding local data or local analysis. So one of the things that interests me about your Anchor Collaborative, you are a combination of some pretty important national organizations but you're supporting folks on the ground that are in, I don't know, I'll use the word affiliates. They're local organizations. Talk to me a little bit about how you're thinking of not just advancing the cause, but advancing the capacity of folks on the ground to implement some of the changes you're in favor of.

Elana Needle: Yeah, so the power of the technology is that if you have access to it and know how to use it, it can make your case essentially. So we are thinking of working with affiliates in multiple ways. And so we had, as I said, that wonderful partnership with Esri. We were actually able to give licenses to our affiliates so that they can use the technology on the ground. And so most of them are accessing it through our data hub, but there are obviously other apps and a ton of data that folks can access within the whole universe of what ArcGIS has to offer. So we're hoping that we're, A, providing a license and ensuring that that's not a cost inhibition on the ground locally. We did provide some minimal training as well. And that's an area that we're looking to enhance and make more robust. But our on the ground affiliates have used for the census, for example, in Florida, have used our mapping to make very detailed call sheets for their Get Out the Count activities.

You could make a walk list if you were doing door knocking, for example, for the election. We're also hoping that this police budgeting project actually gives local folks the tools to go to a town council meeting or a police budgeting meeting and speak to their elected representatives with the actual data access that we've provided. So our hope is that we're pushing the policy levers at the micro, mezzo and macro level in all that we're doing.

And additionally, another tool that we've been able to use is we created a partnership with DemLabs SeeSay app during the election. And so we were able to monitor in real time voter intimidation and voter suppression through the ArcGIS backend. And we were able to connect lawyers to people in specific polling places if they had an issue or questions, and actually talk them through a circumstance -- in one situation to ensure that we could intervene with an armed person at a poll for example, and that happened in Pennsylvania. And so we're looking at it from the national level, but we're also able to localize it to a specific polling place in a national election.

Steve Goldsmith: That's a set of both practical and sophisticated uses of the platform itself. As we think a little bit about day-to-day importance of equity in local communities, we have policing, you've mentioned a couple times. But there's a broader conversation about equity in almost every aspect. So if you were to advocate or think about the platform that you've made so much use of, how might it be utilized by either an NGO or a government official in X, Y city in a transformation,  better use of and more equitable allocation of city services or the like?

Elana Needle: So you could use it in a lot of ways, but I want to put a plug here for really good disaggregated data as well. So often what we see is that groups are lumped together and talked about in the aggregate and that actually, it makes it so that you can't tell what's happening with specific groupings. So the largest example or the easiest one is the Asian American community. If you combine them all into one big group, then it looks like, in total, the median income and the education level are very high. But when you disaggregate that down, you can see, for example, that Hmong populations have lower educational attainment, lower incomes. And so what we're finding is that if we're able to have good nuanced disaggregated data, then our equity conversations are much more fruitful because we actually have information on what is inequitable and where we need to pull the levers to make things more equitable.

And so, you could use data mapping to visualize almost anything: health infrastructure, mental health infrastructure, substance use, hell, parking tickets. From soup to nuts, it would be hard press for me to say, find an example where if you don't have good data and mapping and the story mapping that you can build from that, then you would be worse off having that. And so I think if a city official is working in a specific department, there is data -- and if there's not data, then that's also a story. And part of what we figured out through the Black Lives Matter and pushback on police accountability and police reform is that there is no good federal database on police shootings. And so someone had to fill the gaps. And what we have now are sort of disparate databases, none of which are government responsibility, that we're using to drive policy.

And so, we're using these tools in different ways and we're trying to use them to drive policy for equity, but the same can be said for the other side. So we understand redistricting and gerrymandering, for example, very easily through maps. And GIS is wonderful with the ability to draw a boundary and then to layer in what the community looks like. So it's not the easiest to just jump in as a lay person and use this, and we're hoping that through partnerships like this, we can train folks and ensure that they have access to and can speak cogently about whatever their desire is with data and mapping.

Steve Goldsmith: You remind me when I was working for Mayor Bloomberg in New York City right at the beginning of the Uber entry into the city, we had this argument with the yellow taxi cab drivers about service. We wanted more medallions at the time in the outer boroughs. And the taxi yellows said, "Well, we're fully capable of servicing the outer boroughs." Well, it turns out that when one mapped visually from the GPS information, every time you throw a flag in a yellow, you get a GIS point of pickup. 97.5 percent of the pickups were in Manhattan, south of 119th Street, 97. 2.5 percent were north of that and in every other borough. So the picture of that led to the green taxis that are in the outer boroughs actually. So it's kind of to your point.

I think the work that you all are doing with Jamal and the NAACP and the larger Anchor Collaborative has much to teach us both about the use of GIS tools as well as visualizations, but more importantly, on a core of values of the equity and fairness and day-to-day governance. So I want to thank you, Elana Needle, director of racial equity for the Anchor Collaborative for your hard work on behalf of those causes and for spending some time with us today on this podcast. This is Steve Goldsmith saying goodbye.

Elana Needle: Thank you so much for having me.


Steve Goldsmith: If you liked this podcast, please visit us at, or follow us @DataSmartCities on Twitter. Find us on iTunes, Spotify, or wherever you get your podcasts. This podcast was produced by Betsy Gardner and hosted by me, Steve Goldsmith. We're proud to serve as a central resource for cities interested in the intersection of government, data and innovation. Thanks for listening.