Math vs Gerrymandering
Abstract: Courts at all levels are struggling with the increasingly pressing and complex issue of political gerrymandering. Deadlines for the post-2020 census redistricting are quickly approaching. At the heart of our difficulties to fairly divide ourselves in voting district lies a math problem – how do we measure fairness? How can we use that measure to draw fair district boundaries?
Our project is part of nationwide collaboration of mathematicians, demographers, lawyers, mapmakers, political leaders, and citizens attempting to develop tools for this purpose. We will survey Markov Chain Monte Carlo methods used in the PA Supreme Court case and our recent work to improve and apply it to more states. We will discuss several commonly used compactness metrics and present a new idea called transit time compactness that aims to use the Google Maps API to measure cohesiveness of people, not just land.
This project derives from participation in the Voting Right Data Institute at MIT, Harvard, and Tuft Univ in Summer 2018 under Dr. Moon Duchin.
Preston Ward*, Maria Tover*, Casey Sutton*, and Diana Dinh-Andrus*
Judging Forms – Official judges only