Redistricting: Drawing the Line
Sachet Bangia, Christy Vaughn Graves, Gregory Herschlag, Han Sung, Kang, Justin Luo, Jonathan C. Mattingly, Robert Ravier

TL;DR
This paper introduces a method to evaluate the fairness of political districting by generating numerous non-partisan redistrictings and analyzing their election outcome distributions, highlighting the representativeness of actual district plans.
Contribution
We develop a Monte Carlo-based approach to assess districting fairness, providing a statistical baseline and critique of existing and proposed district maps.
Findings
2012 and 2016 districtings are highly atypical and unrepresentative.
A bipartisan panel's districting is highly typical and representative.
Generated redistrictings reveal a broad range of possible election outcomes.
Abstract
We develop methods to evaluate whether a political districting accurately represents the will of the people. To explore and showcase our ideas, we concentrate on the congressional districts for the U.S. House of representatives and use the state of North Carolina and its redistrictings since the 2010 census. Using a Monte Carlo algorithm, we randomly generate over 24,000 redistrictings that are non-partisan and adhere to criteria from proposed legislation. Applying historical voting data to these random redistrictings, we find that the number of democratic and republican representatives elected varies drastically depending on how districts are drawn. Some results are more common, and we gain a clear range of expected election outcomes. Using the statistics of our generated redistrictings, we critique the particular congressional districtings used in the 2012 and 2016 NC elections as…
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Taxonomy
TopicsElectoral Systems and Political Participation · Game Theory and Voting Systems · Judicial and Constitutional Studies
