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

Background

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

Student Opportunities

Students can expect to be involved with preparing publications and to become involved with pressing and immediate issues of government by becoming key contributors to lawsuits and/or publicly available redistricting tools. Undergraduate students will work directly with team leaders on researching their projects. Graduate students will be given the opportunity to serve as project managers and mentor undergraduate students, which will allow them to grow as future mentors.

The team will meet regularly. Once a week, selected team members will lecture on individual topics that consist of either research discoveries or challenges, or fundamental skills needed to further the research. In addition to the weekly meetings, team leaders and graduate student mentors will regularly meet with selected undergraduates for mentorship and collaboration.

The ideal composition of the team consists of 12-16 undergraduates and 2-4 graduate students in addition to the team leaders. The undergraduates will work in subgroups:

  • Algorithm/API development (students would ideally be Computer Science or Mathematics majors, and would have expertise in numerical analysis, programming, algorithms and software development)
  • Gerrymandering in real-world district plans (students would ideally be Statistical Science or Mathematics majors, and have expertise in data analysis, statistics, and visualization tools)
  • GIS (students could come from a variety of majors but would ideally have some experience with GIS tools; Public Policy, Political Science and Sociology majors would be ideal)
  • Public policy research (students would ideally be Public Policy Studies or Political Science majors and have experience in public policy research and reading legal documents).

Each subgroup will work closely together. Students will be evaluated and graded for course credit. Evaluations will be based on their progress on chosen projects; however, ample consideration will be given to unforeseen challenges.

Timing

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

Crediting

Independent study credit available for fall and spring semesters

This Team in the News

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).

Faculty/Staff Team Members

Gregory Herschlag, Arts & Sciences-Mathematics
Jonathan Mattingly, Arts & Sciences-Mathematics*
Frederick Mayer, Sanford School of Public Policy*

Graduate Team Members

David Kearney, Political Science-PHD

Undergraduate Team Members

Felicia Chen
Samuel Eure, Mathematics (BS)
Shuyu Fan
Luke Farrell, Computer Science (BS), Neuroscience (BS2)
Anjali Kunapaneni
Max Labaton
Tianxue Mei
Nima Mohammadi
Isaac Nicchitta, Public Policy Studies (AB)
Divya Nimmagadda, Public Policy Studies (AB), Economics (AB2)
Jay Patel
Swathi Ramprasad
Gillian Samios, Public Policy Studies (AB)
Jacob Shulman, Computer Science (BS), Mathematics (AB2)
Haley Sink, Economics (BS), Political Science (AB2)
Rayan Tofique
Matthew Tribby, Computer Science (BS)
Ella Van Engen

Community Team Members

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

* denotes team leader

Status

Active, New