How to Quantify (and Fight) Gerrymandering

Episode Summary

Executive Summary: The episode examines how mathematicians, political scientists, and social scientists are building quantitative tools to detect and challenge partisan gerrymandering. It explains why courts have struggled to define unfair maps, highlights new measures like compactness, partisan symmetry, and the efficiency gap, and shows how simulations and expert testimony are reshaping litigation, especially in Wisconsin and Maryland.

Main Topics: The legal problem of defining gerrymandering (Priority: 5/5): The Supreme Court has long said extreme partisan gerrymandering is unconstitutional, but it has never struck down a map under that principle because there is no universally accepted fairness standard. Compactness as a partial but insufficient standard (Priority: 5/5): Mathematicians at Tufts are organizing workshops to clarify compactness measures and train expert witnesses, but the segment emphasizes that compactness alone cannot guarantee fair maps. The efficiency gap and partisan symmetry (Priority: 5/5): Researchers propose measuring whether both parties have equal opportunity to convert votes into seats, using the efficiency gap to quantify wasted votes and identify biased maps. Simulation methods to detect intentional bias (Priority: 5/5): Wendy Cho’s group and others use massive map simulations to see whether an enacted district plan is an outlier compared with millions of reasonable alternatives, helping infer intentional gerrymandering. Geography can create bias without intent (Priority: 4/5): Studies in Florida and elsewhere show that clustered urban voters can produce biased outcomes even under random or compact redistricting, meaning some unfairness arises from population geography rather than deliberate manipulation. What standard the Supreme Court may adopt (Priority: 4/5): Possible legal tests differ on whether courts should require proof of intent, proof of durable partisan bias, outlier status, or some combination of these factors. Interdisciplinary collaboration and future litigation (Priority: 4/5): The episode stresses collaboration among mathematicians, political scientists, computer scientists, and lawyers to create methods courts will trust in future gerrymandering cases.

Key Arguments: No single standard has yet persuaded the Supreme Court to define when partisan gerrymandering becomes unconstitutional. Compactness is useful as a constraint but cannot by itself produce fair district maps. The efficiency gap offers a simple, court-friendly way to measure wasted votes and partisan asymmetry. Simulation-based outlier tests can distinguish intentional gerrymanders from maps that are biased mainly because of geography. Some apparent gerrymanders are not purely intentional; urban clustering can make maps look biased even when drawn nonpartisanly. A legal rule focusing only on intentional gerrymandering may have limited national effect, while a broader rule could substantially change redistricting outcomes. Mathematicians can contribute most by translating technical measures into standards usable by courts and expert witnesses.

Data Points: Year of key Supreme Court ruling: 1986 - The Court said extreme partisan gerrymandering is unconstitutional in theory but did not invalidate the Indiana maps. Year Court called the question unanswerable: 2004 - The Court rejected nearly every available test for gerrymandering. Years since last federal court invalidation before Wisconsin case: More than 30 years - The Wisconsin state assembly map was the first federal map struck down as unconstitutionally partisan in over three decades. Workshop applications: More than 1,000 - Interest in the Tufts workshop to train mathematicians as expert witnesses exceeded expectations. Florida election vote share: Almost identical number of votes for George W. Bush and Al Gore - Used to show how district maps can still be biased despite close statewide vote totals. Bush-voter district share: 68% of districts - Under Florida’s post-2000 census congressional map, Bush voters outnumbered Gore voters in 68% of districts. Maryland simulation maps: 250 million - Cho’s team generated 250 million reasonably imperfect maps to compare with Maryland’s enacted plan. Maryland outlier result: More biased than 99% of simulated maps - The official Maryland plan was an extreme outlier in favor of Democrats. Wisconsin efficiency gap (2012): 13% - The challenged Wisconsin State Assembly map showed a large partisan efficiency gap. Wisconsin efficiency gap (2014): 10% - The same map remained highly biased in the next election cycle. Average state legislature efficiency gap (2012): Slightly more than 6% - Used as a comparison point for judging the Wisconsin map. Florida congressional districts struck down: 8 of 27 - The Florida Supreme Court later invalidated part of the 2012 congressional plan. National effect of banning only intentional gerrymandering: Likely little effect on U.S. House balance - A study by Chin and Cottrell found that intentional bias often cancels out nationally.

Pivotal Quotes: "we've never declared a partisan gerrymander" — Wendy K. Tam Cho: She explains the Supreme Court’s failure to enforce the constitutional prohibition in practice. "We are absolutely fundamentally motivated by being useful to this problem, not by publishing, but by having an impact." — Moon Duchin: She describes the Tufts workshop’s applied mission and collaboration with legal and civil rights groups. "There's just a deeper question about what is objectionable about gerrymandering" — Jonathan Rodden: He frames the unresolved debate over whether courts should care about intent or simply outcomes.

Implications: The episode suggests redistricting fights will increasingly hinge on data, simulations, and expert testimony. Future court rulings could reshape how states draw districts, but the biggest impact will depend on whether judges accept measurable fairness standards.