Category: Analysis

[TLDR : See this PDF for guidance:  Ensemble Method Guidance ]

As the country gears up for the next redistricting cycle we have attempted to collect our thoughts and guidance on using the ensemble method to critique a particular redistricting plan. This summarizes our current thinking stretching back to 2013-2014 as one of the originators of the Ensemble Method; it reflects our experience gained through providing expert guidance, including live testimony, to the court in a number of cases.

The document begins with the following summary:

The ensemble of maps translates the specific redistricting design criteria into an understanding of what a redistricting plan should look like if the specified criteria are followed without ulterior motive. The criteria are formalized in a distribution on redistricting plans from which a sufficiently rich ensemble is drawn to capture the properties of the distribution. If the criteria are non-partisan then the ensemble gives a non-partisan normative collection against which other plans can be compared for their partisan and non-partisan properties.

The rest of the text can be found in this PDF document: Ensemble Method Guidance.

With the upcoming redistricting cycle, there are a number of questions about how ensembles can, will, and should be used to audit and restrict gerrymandering.

We have prepared a slide deck illuminating how the ensembles have been used to legally challenge plans during the last redistricting cycle.  We have also examined some of the new indices that are being put forward as measures of gerrymandering.  Under a certain set of votes, it is possible to “game” these indices, in the sense that plans can be typical of an ensemble according to multiple indices while still being gerrymanders.

Finally, for the North Carolina general assembly, we demonstrate the fragility and possible choices when it comes to county clustering.

The slides are available here.

We have recently posted a pre-print of a Multi-Scale Merge-Split sampling algorithm.  The work’s central contribution is to provide a multi-scale representation of the state space which can be used to efficiently sample redistricting plans containing both fine and coarse-scale details.  Because of the coarse-graining, this algorithm promises fast scaling on problems with fine-scale graphs.  It also is capable of naturally preserving nested communities of interest (such as precincts made up of census blocks, and counties made up of precincts) without creating prohibitive energetic barriers which slow mixing. This work builds on our Merge-Split algorithm, which, in turn, builds on the ReCom algorithm.

We will be hosting a conference on gerrymandering from 10am on Monday, March 2nd, until 1pm on Wednesday, March 4th.  For details, see the link.

Today the state court chose to accept the Remedial Map which the legislature produced in response to the maps we have been using since 2016 being declared an illegal gerrymander in Harper v. Lewis.

Sadly this new map still has districts containing an abnormally large number of Democrats and others with comparably few. The result is a map which elects the same number of Democrats and Republicans over an abnormally large range of partisan election outcomes.

We have revised our work quantifying gerrymandering in the N.C. Congressional Districts. The original work was presented in Common Cause  v Rucho. We have taken the opportunity to  use the improved code base which performs more sophisticated  convergence test and update our discussion to better reflect our current perspective. We have also corrected a few inaccuracies and small errors. That being said, the results are fully in line with those from the original version.

The new text can be found HERE.

A collection of related animations can be found “The Animated Firewall.” Two related discussions can be in It’s Not about Proportional Representation and The Fix is in: The votes don’t matter.

The data and code for this work can be found in this git repository: https://git.math.duke.edu/gitlab/gjh/nccongressionalensembles.git.

This post shares Jonathan’s expert report and rebuttal to the defense’s experts are linked below.  The report summarizes some of the research our group has performed on the North Carolina state legislative districts.  See this post for complementary animations.

North Carolina’s constitution requires that state legislative districts should not split counties. However, counties must be split to comply with the “one person, one vote” mandate of the U.S. Supreme Court. Given that counties must be split, the North Carolina legislature and courts have provided guidelines that seek to reduce counties split across districts while also complying with the “one person, one vote” criteria. Under these guidelines, the counties are separated into clusters. For a great explainer about the County Clustering problem see this blog entry on Districks.

A group of high school students from the NC School of Science and Mathematics worked with us over the last academic year and summer to develop computer algorithms to optimally cluster counties according to the guidelines set by the court in 2015. We recently released an article that presents the algorithm along with publicly accessible code which anyone can use.

Additionally, in our article, we use this to investigate the optimality and uniqueness of the enacted clusters under the 2017 redistricting process. We verify that the enacted clusters are optimal, but find other optimal choices. We emphasize that the tool we provide lists all possible optimal county clusterings. We also explore the stability of clustering under changing statewide populations and project what the county clusters may look like in the next redistricting cycle beginning in 2020/2021.

The posting to the ArXiv can be found here.
The article is now published and can be found here.
The code is referenced in the ArXiv post, and may also be accessed here.

[Edits: Added like to Districks  explainer (9/4/2019)]