Can Big Data Help Cities Measure and Act on Racial Inequities?

By Emily Warren, postdoctoral fellow, 21st Century Cities Initiative, Johns Hopkins University

New research by Paul Jargowsky reveals that economic segregation – that is the differences in average incomes across neighborhoods – is growing at an even faster rate than household income inequality in U.S. metro areas, the indicator most commonly used in media accounts of rising inequality in the U.S.

Jargowsky’s research and its implications for city leaders were the topics of a panel at our 21st Century Neighborhoods symposium held last December in Baltimore. The panel had a far-reaching conversation about the relationship between economic segregation and racial segregation, which prevent residents of color from accessing economic opportunities enjoyed by many white residents. According to Jargowsky, about 30 percent of economic segregation in metro areas is simply a function of racial segregation.

Michael McAfee, President of PolicyLink pointed out the challenges cities face in addressing the enduring legacy of race-based policies that continue to contribute to inequities. McAfee noted that while city leaders and other officials are drawn more than ever to the power of big data and analytics to drive policy, such applications of data science are not adequately measuring the impact of policies on vulnerable populations and people of color. He urged cities and other institutions to develop plans for using data systems for reducing racial inequity.

In this post, we explore the idea of an “equity index” more closely and take a look at how some cities are using big data to measure racial inequities; and how they are responding to challenges to make use of this data in ways that focus on long-term solutions.

How are cities examining inequity?

In recent years, cities have become more proactive in addressing local inequities through the use of administrative data systems to identify the prevalence of structural and distributional inequality. From agencies such as planning, health, housing, human services, transportation, and public safety, cities have a wealth of data at their disposal for investigating local inequities, both in terms of equity distributed across neighborhoods and across race. Here are some examples:

• In 2017, the Baltimore city planning department found that investments for projects such as infrastructure, recreation centers, parks, and other public spaces varied by the racial composition of the neighborhood. Neighborhoods in which residents are predominantly white received on average two times as much capital investment per year as neighborhoods where residents are predominantly people of color.
• In 2017, the city of St. Paul, Minnesota, used administrative data to examine neighborhoods with the largest number of tickets issued during snow emergencies. They found that tickets were disproportionately issued in low-income areas with large numbers of rental properties and a significant proportion of immigrant populations.
• A 2015 report from the Justice Department on Ferguson, Missouri, found the city was targeting low-income residents, who were disproportionately African-American, for exorbitant fines and fees. Since that report, many other cities have also examined the extent to which communities of color pay a disproportionate share of city-issued fines and fees.

There also have been efforts to make these kinds of data publicly available in a dashboard format, so that residents can examine local inequities for themselves. Seattle’s Race and Social Justice Initiative (RSJI) provides public data on racial disparities in domains such as housing, jobs, health, and criminal justice. RSJI provides recent data for these indicators in addition to information on local programs and services intended to address these inequalities.

In collaboration with PolicyLink, Bloomberg Associates, and the My Brother’s Keeper Initiative, the city of Oakland is working on its own data indicators project to track aggregated outcomes for boys and men of color in the city. The project, called Equity Intelligence Platform, is expected to eventually expand to other cities. The project aims to help city officials, community leaders, and residents track disparities in outcomes such as criminal justice, education, and employment by creating a centralized, publicly available data system.

Despite these few examples, evidence suggests there is still much to be done. The recently released Boston University 2017 Menino Survey of Mayors reported that while most respondents were able to provide examples of metrics important for policies such as education, most mayors were unable to identify even a single metric or piece of information they rely on for assessing how their cities are addressing equity. As individual cities experiment with various measurements of equity, it will be important to come up with a few simple, yet effective measures that can be used across cities.

Making use of big data to address equity

As cities work to refine the metrics for measuring equity, they also need to put in place structures for moving beyond measuring to acting on the data.

Some cities have already started to take such action through the use of designated offices or staff focusing on racial equity. Seattle’s RSJI project includes a three-year strategic plan to address equity issues, using both process and outcome-based goals. Cities including New Orleans, Boston, Philadelphia, Oakland, Austin, and Minneapolis all have racial equity initiatives that include strategic plans across a variety of domains such as health, employment, public safety, and housing. The most robust of these plans make use of data to track outcomes and allocate city staff and resources for community outreach and organizing.

Data can be a powerful tool to help shape policies that address racial equity imbalances. Over the next several years, it will be important to track these efforts and learn from the cities that are most effective at creating more equal access to opportunities.

Watch a brief highlight video of the panel below. Watch a video of the entire panel here.