Quantifying Gerrymandering – Page 4 – A nonpartisan research group centered @ Duke Math

January 30, 2018January 31, 2018

Gerrymandering is Not about Oddly Shaped Districts

It is tempting to assume that gerrymadnering requires the presence of oddly shaped districts. After all, the term gerrymandering derives from the salamander-shaped maps produced by Massachusetts’s 1812 Governor Elbridge Gerry, and pictures of that meandering district are practically required in any discussion of gerrymandering.

The story goes that the irregularly shaped boundary attempts to include or exclude particular voters from the district. Although irregular boundaries might well cause one to suspect gerrymandering, it is quite possible for a gerrymandered map to have quite regular districts. Oddly shaped districts, such as like North Carolina’s 12th congressional district and Pennsylvania’s 7th congressional district, make provocative tee-shirts and posters, but they are only a symptom and not the point of Gerrymandering . Continue reading “Gerrymandering is Not about Oddly Shaped Districts”

January 30, 2018July 9, 2024

Firewalls

A Firewall is a buffer used to block unauthorized access. We adapt the term ‘Firewall,’ in the context of gerrymandering, to describe a districting plan that artificially protects the power of a political party. What follows is an exposition on how we discovered a Firewall in the enacted districting plan for the Wisconsin General Assembly that protects the Republican Party from losing the majority of the seats.

For districting plans of the Wisconsin General Assembly, we generate thousands of compliant redistricting plans. To evaluate the enacted districting plan (the Act 43 plan), we ask if how many officials are elected by each party for each plan for a given a set of votes: Each plan in the ensemble will generate a certain number of Democrats and a complementary number of Republicans (ignoring independent candidates), and we can construct a histogram that measures the number of representatives from each party, out of the 99 available seats.

For example, when looking at the Wisconsin General Assembly districts, we construct histograms of the projected number of Republican elected officials that would have won based on 2012, 2014, and 2016 voting data.

Continue reading “Firewalls”

January 30, 2018January 30, 2018

Drawing New Maps for Pennsylvania

The recent court ruling in Pennsylvania invited “all parties and interveners” to submit their own maps to replace the maps which have been ruled unconstitutional. (See also here.)

In the interest of facilitating such maps and their analysis, the Duke Quantitative Gerrymandering group is making available our processed and cleaned map files and associated data at the following public git repository.

https://git.math.duke.edu/gitlab/gjh/PennsylvaniaRedistrictingData.git

A local copy can be downloaded with

git clone https://git.math.duke.edu/gitlab/gjh/PennsylvaniaRedistrictingData.git

We encourage those who produce maps to share them with us.

January 18, 2018January 18, 2018

Quantifying Gerrymandering in North Carolina

This paper which is posted to the ArXiv here is an expanded and reworked version of our original note on NC which can be found here.

January 18, 2018January 18, 2018

Evaluating Partisan Gerrymandering in Wisconsin

This work is posted on the ArXiv here. Its research which is central in the Amicus Brief written by Eric Lander. That brief was discussed in the oral argument of Gill v. Whitford in the Supreme Court of the United States.

https://arxiv.org/abs/1709.01596

January 18, 2018January 21, 2018

Redistricting: Drawing the Line

This work, which is posted on the arxiv here, summarizes the work which began with the 2016 Data+ team and was built on by the Quantifying Gerrymandering group. It serves as the basis for Jonathan Mattingly’s testimony in Common Cause v. Rucho.

This work was updated in this subsequent article.

https://arxiv.org/abs/1704.03360

January 18, 2018January 30, 2018

Quantifying Gerrymandering : Data+ 2016

The evolution of the project continued with this second Data+ group. Because of our interaction and collaboration with the Beyond Gerrymandering project, we again concentrated on North Carolina.

A new code base in Java was written. The version was tested carefully for reliability and correctness to a level beyond what had been done before.

Because of its increased efficiency longer runs could now be used.

January 18, 2018January 21, 2018

Quantifying Gerrymandering : Data+ 2015

The webpage found here summarizes the work of the Data+ team during the summer of 2015. The work built on the previous summers work described in Redistricting and the Will of the People.

For the first time in the work the county splitting and not conforming to the VRA were penalized in the score function used to construct the measure. A number of different states were considered in this work.

For this iteration of the project, a new code base was written in Julia. Unfortunately some unidentifiable memory leaks (maybe in the language itself) limited the length of the runs posible.

Some middle bugs in this version of the code were corrected in the next version of the project initiated in the Data+ 2016 project. That work is the basis for Redistricting : Drawing line .

https://services.math.duke.edu/projects/gerrymandering/

January 18, 2018January 18, 2018

Redistricting and the Will of the People

This work posted on the ArXiv here, summarize the initial work done by Christy Vaughn Graves and Jonathan Mattingly between Summer 2013 and Fall 2014. It uses the same basic methodology as the subsequent papers: generate an ensemble of redistricting plans, analysis their properties, and then compare an existing plan of interest to the ensemble of maps.

The central idea being that maps which were outliers in the ensemble were should be seen as unrepresentative.

This analysis did not include the VRA or county splitting terms in the score function as latter works did. The work did look at the typical most african american district in each plan after the plan had been drawn.

We also did not have access to the true length of the boundary between various VTDs. Instead we used an approximation which assumed each district was circular and that the boundary was equally shared between neighbors. This work also used a much smaller number of maps. There were also a small bug in the code which was fixed in subsequent summers.

https://arxiv.org/abs/1410.8796