English

Quantifying Gerrymandering in North Carolina

Physics and Society 2018-01-12 v1 Applications

Abstract

Using an ensemble of redistricting plans, we evaluate whether a given political districting faithfully represents the geo-political landscape. Redistricting plans are sampled by a Monte Carlo algorithm from a probability distribution that adheres to realistic and non-partisan criteria. Using the sampled redistricting plans and historical voting data, we produce an ensemble of elections that reveal geo-political structure within the state. We showcase our methods on the two most recent districtings of NC for the U.S. House of Representatives, as well as a plan drawn by a bipartisan redistricting panel. We find the two state enacted plans are highly atypical outliers whereas the bipartisan plan accurately represents the ensemble both in partisan outcome and in the fine scale structure of district-level results.

Cite

@article{arxiv.1801.03783,
  title  = {Quantifying Gerrymandering in North Carolina},
  author = {Gregory Herschlag and Han Sung Kang and Justin Luo and Christy Vaughn Graves and Sachet Bangia and Robert Ravier and Jonathan C. Mattingly},
  journal= {arXiv preprint arXiv:1801.03783},
  year   = {2018}
}

Comments

This is a revised and expanded version of arxiv:1704.03360, entitled "Redistricting: Drawing the Line."

R2 v1 2026-06-22T23:42:42.466Z