Gerrymandering and the Extent of Democracy in America (2018-2019)


Gerrymandering has been increasingly used to undermine the Democratic process. Although there remains no standard to detect partisan gerrymandering, we have begun to develop promising and potentially justiciable techniques. These techniques expose the natural geopolitical structure of a region, and understanding this structure can be used to identify political and racial gerrymandering.

Project Description

This Bass Connections project will test the hypothesis that bipartisan or nonpartisan redistricting committees will not gerrymander. To this end, the team will compare districting plans across U.S. states with and without nonpartisan redistricting committees. In addition to such policy questions, team members will analyze the effectiveness of a number of simple statistical tests currently used to detect gerrymandering, using techniques that provide fine-scale details that can be used to critique and test the simple tests, so that they are not misapplied by the courts. The first hypothesis is expected to lead to one publication, and the examination of simple statistical tests to lead to another.

Team members will also develop tools to be released publicly that will facilitate the free exploration of redistricting plans by both political parties, the public and the press, and contribute to public understanding of the extent and impact of gerrymandering. This may include sponsoring map-drawing contests in which students and members of the general public create maps that are then evaluated using the team’s statistical tests.

The team will also finish analyzing the extent of gerrymandering in the North Carolina General Assembly. There are many open challenges in this process that includes developing county clustering algorithms and analyzing the space of redistricting plans within each cluster. This work is expected to lead to one or two publications, dependent on the complexity and challenges of the county clustering algorithm.

In addition to the academic publications, all of the project’s results will be reported publicly.

Anticipated Outcomes

Publications; affidavits for court cases dealing with gerrymandering; publicly available software/APIs to employ the team’s methodologies; website for educational purposes; grant to continue the work


Fall 2018 – Spring 2019  

  • Fall 2018: Automate data extractors; examine districting policies in the U.S.; analyze existing metrics; conduct data analysis and geometric classification; examine effect of bipartisan commissions; develop clustering algorithms; continue Data+ summer work on analysis of NC General Assembly and redistricting algorithm development
  • Spring 2019: Publish results of analysis of NC General Assembly; examine districting policies (world) and make public report; analyze existing metrics and publish results; continue data analysis and geometric classification and publish results; continue examining effect of bipartisan commissions and publish results; API development and release

This Team in the News

Supreme Court to Hear North Carolina Gerrymandering Case With Ties to Duke Research

US Supreme Court Hears Gerrymandering Case With Ties to Duke Research

The Supreme Court Takes on Gerrymandering. A Cottage Industry Wants to Prove it's Gone Too Far

All That Hard Work Paid Fff’: Duke Students Road-trip to DC to Hear Research They Worked on Cited by Supreme Court

Duke Mathematics Has Its Day in Court

Looking for a Way Forward on Redistricting Reform

Party Lines

Meet the Members of the 2018-19 Student Advisory Council

The Fight Against Partisan Gerrymandering Continues

Duke Research Makes Mark on Federal Court Cases over North Carolina Gerrymandering

See related Data+ summer project, Gerrymandering and the Extent of Democracy in America (2018).

Map of districts

Team Leaders

  • Jonathan Mattingly, Arts & Sciences-Mathematics
  • Frederick Mayer, Sanford School of Public Policy

/graduate Team Members

  • David Kearney, Political Science-PHD, Political Science-AM

/undergraduate Team Members

  • Felicia Chen, Computer Science (BS), Economics (BS2)
  • Samuel Eure, Mathematics (BS)
  • Shuyu Fan, Statistical Science (BS), Political Science (AB2)
  • Luke Farrell, Interdept Comp Sci/Neuro (BS)
  • Mitra Kiciman
  • Anjali Kunapaneni, Public Policy Studies (AB)
  • Max Labaton, Public Policy Studies (AB)
  • Yashas Manjunatha, Computer Science (BS)
  • Tianxue Mei, Art History (AB), Computer Science (BS2)
  • Nima Mohammadi, Public Policy Studies (AB)
  • Isaac Nicchitta, Public Policy Studies (AB)
  • Divya Nimmagadda, Public Policy Studies (AB)
  • Jay Patel
  • Rahul Ramesh
  • Swathi Ramprasad, Public Policy Studies (AB), Computer Science (AB2)
  • Jacob Rubin, Computer Science (AB)
  • Gillian Samios, Public Policy Studies (AB)
  • Jacob Shulman, Computer Science (BS), Statistical Science (BS2)
  • Haley Sink, Economics (BS), Political Science (AB2)
  • Rayan Tofique, Computer Science (BS)
  • Matthew Tribby, Computer Science (BS)
  • Ella Van Engen, Mathematics (AB)
  • Chris Welland, Mathematics (AB), Public Policy Studies (AB2)
  • Claire Wiebe, Mathematics (AB)

/yfaculty/staff Team Members

  • Gregory Herschlag, Arts & Sciences-Mathematics

/zcommunity Team Members

  • Andrew Chin, UNC School of Law
  • Common Cause
  • North Carolinians for Redistricting Reform