March 26th, 2019
Algorithms created by Duke’s Jonathan Mattingly and his team, are the principal evidence in NC partisan gerrymandering case before the Supreme Court March 26. They’re in Washington DC now as part of the...
July 5th, 2018
This article from the Proceedings of the National Academy of Sciences on the use of math tools to show gerrymandering features the work of iiD’s Jonathan Mattingly.
April 13th, 2017
Jonathan Mattingly’s iiD projects on gerrymandering recently resulted in a published paper on the topic in Arxiv. The paper represents the most comprehensive analysis of the team’s work and was the...
September 1st, 2016
Jonathan Mattingly, professor of mathematics and statistical science at Duke and iiD faculty member, and his Data+ team are mentioned in this article about gerrymandering.
January 11th, 2018
Duke Mathematics Professor Jonathan Mattingly’s algorithm demonstrating political gerrymandering in North Carolina’s district mapping was a focal point in the ruling of the 4th Circuit of Appeals judge earlier this week. The...
January 23rd, 2018
Duke Mathematics chair Jonathan Mattingly’s computer algorithm work on district gerrymandering in North Carolina has been referenced in a January 9, 2018 Federal Court ruling that Republicans have unfairly mapped North Carolina...
July 3rd, 2018
This article highlights iiD faculty member Jonathan Mattingly’s work mathematically dissecting the structure of a typical redistricting to identify gerrymandering.
December 2nd, 2016
Duke mathematics professor and iiD faculty member Jonathan Mattingly talks about his work with mathematical modeling and gerrymandering.
Data+, Gerrymandering, Social Sciences
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...
Sophie Guo, Math/PoliSci major, Bridget Dou, ECE/CompSci major, Sachet Bangia, Econ/CompSci major, and Christy Vaughn spent ten weeks studying different procedures for drawing congressional boundaries, and quantifying the effects of these procedures on the fairness of actual election results. Project Results There has already been research done with North Carolina districts, described in http://today.duke.edu/2014/10/mathofredistricting. There, Jonathan...
Martin Guo (MIDS), Dani Trejo (CS), James Wang (CS/Math), and Grayson York (Math/CS) spent ten weeks building tools to understand voting patterns and gerrymandering of districts in North Carolina. They used dimension reduction techniques to cluster different elections into common groups, and they tested various methods for generating synthetic elections...