Sam Wang & Brian Remlinger

Sam Wang is professor of neuroscience at Princeton University. He and Brian Remlinger, a statistical research specialist, run the Princeton Gerrymandering Project.

Recent Articles

Slaying the Partisan Gerrymander

With extreme gerrymanders on the rise, it is time for the Supreme Court—and the states—to curb a practice that has gotten out of control.

Corey Lowenstein/The News & Observer, File via AP
This article appears in the Fall 2017 issue of The American Prospect magazine. Subscribe here . Gerrymandering is an old phenomenon with new dimensions and heightened significance for American democracy. Thanks to technology and political polarization, the effects of partisan gerrymandering since 2012 have been more pronounced than at any point in the previous 50 years. Close to a hundred congressional seats and thousands of state legislative seats have been strategically drawn to be noncompetitive at the expense of all other interests. As a consequence, tens of millions of voters have had no meaningful say in who represents them. In this year’s Supreme Court term, the justices have taken up the constitutionality of partisan gerrymandering in a case involving state legislative districts drawn by Republicans in Wisconsin. A key question for the Court will be whether neutral statistical tools can reliably detect partisan gerrymanders. We believe that such tools are available, and...

Can Math Assist in Saving Democracy?

Statistics to the rescue

This is a sidebar to " Slaying the Partisan Gerrymander ," which appears in the Fall 2017 issue of The American Prospect magazine. Subscribe here . When it comes to creating a test for detecting gerrymanders, getting stuck on the details of maps hinders an efficient evaluation. Courts need simple and straightforward tools for detecting gerrymanders. Partisan gerrymandering is perpetrated using two complementary methods: cracking and packing. “Packing” occurs when as many supporters of one party as possible are crammed into a small number of districts, creating a few overwhelming wins for the victim party. The remaining members of the victim party are then “cracked,” or spread evenly across a large number of districts that the gerrymandering party can dominate. Fortunately, cracking and packing create a distinctive statistical pattern that can be detected with the help of a little math. Two tests, Student’s t-test and the mean-median difference, probe...