Quantifying Gerrymandering in North Carolina

TL;DR

This paper introduces a statistical framework using Monte Carlo sampling to evaluate the fairness of North Carolina's districting plans by comparing them to an ensemble of realistic, non-partisan plans, revealing significant gerrymandering.

Contribution

It develops a novel ensemble-based methodology for quantifying gerrymandering by sampling from a probability distribution of redistricting plans adhering to realistic criteria.

Findings

Enacted plans are significant outliers compared to the ensemble.

Bipartisan plan aligns well with the ensemble in partisan outcomes.

Method reveals detailed geo-political structures within districts.

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.