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The gameability of redistricting criteria

Author

Listed:
  • Amariah Becker

    (A Becker Consulting LLC)

  • Dara Gold

    (The Washington Post, News Engineering - Elections)

Abstract

During decennial redistricting, mapmakers are often instructed to preserve political subdivisions and prior district cores as much as possible. Political subdivisions can include counties, municipalities, wards, precincts and (precisely defined) communities of interest (COIs). And while “district core” may not be well defined, courts overseeing redistricting may ask for “least-change” maps if they want to limit their role to adopting districts similar to those most recently enacted. In addition to some ambiguity in the definition of subdivisions and district cores, how to measure the amount of splitting in a plan is rarely defined and is inconsistent across states. This leaves map drawers, redistricting litigators, and courts free to interpret these guidelines in multiple ways, some of which could be favorable to their redistricting interests. In this paper, we outline several ways to measure how much a plan splits subdivisions, and how much a plan has changed from a baseline map. We show that maps with strikingly different features could each perform well by these standards, all depending on how they’re measured. This is just one of many “gameable” pieces of the redistricting process.

Suggested Citation

  • Amariah Becker & Dara Gold, 2022. "The gameability of redistricting criteria," Journal of Computational Social Science, Springer, vol. 5(2), pages 1735-1777, November.
    • Handle: RePEc:spr:jcsosc:v:5:y:2022:i:2:d:10.1007_s42001-022-00180-w
    DOI: 10.1007/s42001-022-00180-w
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    References listed on IDEAS

    as
    1. Barnes, Richard & Solomon, Justin, 2021. "Gerrymandering and Compactness: Implementation Flexibility and Abuse," Political Analysis, Cambridge University Press, vol. 29(4), pages 448-466, October.
    2. Daryl DeFord & Moon Duchin & Justin Solomon, 2020. "A Computational Approach to Measuring Vote Elasticity and Competitiveness," Statistics and Public Policy, Taylor & Francis Journals, vol. 7(1), pages 69-86, January.
    3. Daniel Carter & Zach Hunter & Dan Teague & Gregory Herschlag & Jonathan Mattingly, 2020. "Optimal Legislative County Clustering in North Carolina," Statistics and Public Policy, Taylor & Francis Journals, vol. 7(1), pages 19-29, January.
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