A team of students led by Professors Jonathan Mattingly and Gregory Herschlag will investigate gerrymandering in political districting plans. Students will improve on and employ an algorithm to sample the space of compliant redistricting plans for both state and federal districts. The output of the algorithm will be used to detect gerrymandering for a given district plan; this data will be used to analyze and study the efficacy of the idea of partisan symmetry. This work will continue the Quantifying Gerrymandering project, seeking to understand the space of redistricting plans and to find justiciable methods to detect gerrymandering. The ideal team has a mixture of members with programing backgrounds (C, Java, Python), statistical experience including possibly R, mathematical and algorithmic experience, and exposure to political science or other social science fields.
Read the latest updates about this ongoing project by visiting Dr. Mattingly’s Gerrymandering blog.
Disciplines Involved: Political Science, Public Policy, Sociology, Geography, all quantitative STEM
Project Leads: Jonathan Mattingly, Greg Herschlag
Project Manager: David Kearney
