A challenge to a partisan redistricting plan in Wisconsin goes before the Supreme Court this fall in the case of Gill v. Whitford. In the New York Times article “The New Front in the Gerrymandering Wars: Democracy vs. Math,” Emily Bazelon writes of the significance of the case, “The outcome of the Supreme Court’s decision in Gill v. Whitford is likely to shape American politics for years and perhaps decades to come."
Social Explorer Co-Founder and CEO Andrew Beveridge collaborated on an amicus brief for the trial (filed yesterday). Professor Beveridge is a nationally recognized research scholar in the area of redistricting and an expert on drawing district lines.
The brief is unique in its focus on the role of big data and modern redistricting tools and analysis. Now more than ever, political leaders in power are able to draw more and more nuanced maps that favor their parties’ candidates. At the same time, experts and courtrooms can also use these advances to better evaluate and challenge redistricting plans.
Read the introduction and summary of argument to find out more. (The full brief is available here.)
The past decade has seen an explosion in data gathering and data analytics. This explosion is poised to have a significant impact on mapmaking and plan analysis in the redistricting context. Mapmakers have at their disposal more data—and more accurate data—about individual voters than ever before. Mapmakers have access to sophisticated analytical software and technology allowing them to leverage this data to predict and exploit voter behavior with a high degree of accuracy. These new and enhanced data and tools—coupled with the demonstrated stability of partisan identity and increasing stability of partisan behavior—allow mapmakers seeking to engineer a gerrymander to sort through a vast array of maps and select those that would entrench the most extreme partisan bias, all without violating historical redistricting principles. As a result, gerrymandering techniques that were only theoretical in the 2010 redistricting cycle could become commonplace in the 2020 redistricting cycle and beyond.
The most recent redistricting cycle already saw less complex versions of these techniques deployed at the national and local level. The use of these techniques corresponded with the emergence of maps that are durably biased, predictably and consistently favoring the party that controlled the redistricting process. In light of intervening developments, however, voters face a future of gerrymanders that are even more biased and more durable, and yet less irregular-looking than ever before. As a result, district shape will be a less reliable guide for identifying an unconstitutional partisan gerrymander.
Crucially for the courts, the tools that enable mapmakers to draw such precise and durable maps also enable factfinders to diagnose the most extreme examples of bias in redistricting. Just as social science and technology have facilitated and will facilitate partisan gerrymandering, they can be used to identify such gerrymandering when it does occur.
Learn more about the case at ScotusBlog.