Subtracting one number from another, that’s all it takes.
William & Mary Professor of Sociology Salvatore Saporito and Associate Professor of Government Dan Maliniak ’06 have created a unique, easy-to-understand measure that quantifies racial segregation of individual legislative districts. Online maps eventually will make the information for every district in the country accessible to anyone.
As the Supreme Court hears oral arguments for a case involving redistricting in Alabama, the pair published their paper “Using the areal unit segregation measure to identify racially ‘packed’ and ‘cracked’ legislative districts” in Electoral Studies. It explains their method, provides a test case by examining Virginia’s districts ruled unconstitutional in Bethune-Hill v. Virginia Board of Elections and shows why their measure of segregation provides information differently from typical ways of detecting gerrymanders.
“One of the things that members of the public want to know is that their districts are fair, not segregated,” Saporito said. “So members of the public can click on our web-enabled map and see what the segregation score is for their district.”
Saporito and Maliniak joined forces after crossing paths on the soccer field they used to play on together 10 years earlier when Maliniak was an undergraduate. Chatting about their work, they decided to combine their research.
Using data for all 2022 Congressional districts, the professors worked with the W&M Center for Geospatial Analysis to create web-enabled maps that will be available to the public, including potential litigants in challenges to voting districts. They started with the southern states and will build out to include the entire country.
Though their project focused on race, their model works for groupings such as partisanship.
“The goal is that anyone with internet can click on a legislative district and figure out how racially segregated it is,” Saporito said.
They realized that gerrymandering is actually segregation, which the pair believes better describes what state legislatures do when they draw districts that disenfranchise people by race or partisanship.
“What legislatures are doing is packing a racial group into a district in much greater numbers than you’d expect given the distribution of racial groups across residential areas and cracking a geographically dense group into multiple districts,” Saporito said.
As explained in their paper, they created their measure on this premise: People who live in a district should expect the racial composition of the district to be similar to the racial composition of their nearest neighbors. The number of neighborhoods to consider varies with the population of a district.
For Alabama’s congressional districts, they count every person’s 717,754 closest neighbors since that is how many people live in each district.
If the racial composition of an average person’s nearest neighbors is the same as the district, it is not segregated. As Saporito described it: “The greater the difference for the average person, the more problematic a district is.”
For example, Alabama’s 7th Congressional District has a segregation value of about 18, since 57% of the people in the district are Black and 39% of the nearest neighbors are Black — a difference of 18 percentage points.
“So the district is an artificially created community that does not actually exist in Alabama; one that is racially different from what people in the district see when they look at the people around them,” Maliniak said.
Alabama’s 7th District is among the three most racially segregated districts nationwide created during the most recent redistricting cycle, close behind Louisiana’s 2nd and Florida’s 20th Congressional districts. The Supreme Court is currently deciding the constitutionality of districts like these.
In the past, eyeing the geographic shape of a voting district was used to challenge whether a district truly represented the racial diversity of residential areas surrounding it. This new measure relies on hard, demographic data that the researchers processed with the help of W&M’s high performance computers.
“The courts have made it very clear that they want individual districts to be challenged,” Maliniak said. “If you say that a district is gerrymandered, you must prove that a specific district has a problem.
“Prior metrics tend to focus on the plan as a whole. Our measure is better because it’s going to give potential litigants and justices an actual segregation value for a specific district.”
Saporito’s previous research measured segregation in school districts, figuring out if school attendance zones were more segregated than the segregation in the school district’s residential areas. Asked by someone what else his method was useful for, he realized he could use it with legislative districts.
Saporito’s initial work focused on segregation across an entire state, but Maliniak suggested going district by district.
For example, the segregation score for the 2nd District of Louisiana is 19.8. To explain the meaning of the score, Maliniak offers a baseball analogy involving balls and strikes.
“The goal is to quantify segregation to determine how far inside or outside the strike zone a district is,” he said.
“The plate is 17 inches wide. So if zero is dead center, a segregation value of zero, two, three, through eight is fine,” Saporito added. “A pitch 10 or 12 inches from center is a ball. Once you get to 20, you’re not even close to the plate. It is in the batter’s box.
“If you can subtract one number from another, the difference describes segregation for one district. We’re not saying to that people should disregard district shape. But this is just one more tool that is easy to understand.”
Editor’s note: Data and democracy are two of four cornerstone initiatives in W&M’s Vision 2026 strategic plan. Visit the Vision 2026 website to learn more.
Jennifer L. Williams, Communications Specialist