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The gameability of redistricting criteria

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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.

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Data Availability Statement

The data analyzed in this paper, along with replication code, are available at https://github.com/daragold/subdivision_metrics_paper

Notes

  1. The term “gameable” is used throughout the paper to mean “exploitable” or “manipulable,” as opposed to a more classic game-theoretic definition.

  2. One notable difference is that counties tile the entire state, whereas some subdivisions like municipalities and communities of interest do not always tile the entire state. Non-tiling subdivisions often offer more opportunities to avoid splitting by drawing district boundaries through the ‘un-tiled’ parts of the state.

  3. By “designed” we mean constructed by hand to showcase properties of the metrics in this section. We did not rely on our optimization algorithms to make any of the sample grid plans in this paper.

  4. Precincts here can be swapped for any base geographic unit, such as census blocks, block groups, wards, etc.

  5. We subtract the ratio from 1 so that a plan that is identical to the original has a change score of 0. All metrics in this section are designed to be minimized.

  6. \(2\text {log}(k)\) is the normalizing constant in the case where both partitions have k population-balanced districts[32].

  7. All VTD plan assignments can be found at https://github.com/daragold/subdivision_metrics_paper.

  8. The plans use VTDs as geographic building blocks. The only imposed requirements on the newly-created sample maps were that each district be contiguous and within 1% of ideal population using the 2020 Census data [52]. Although the 2022 court-ordered map is population-balanced, it is not built from whole-precinct units; coarsening to precincts for this analysis introduced a 1.3% population deviation that is not reflective of the actual districts. These maps are used only to demonstrate real-world examples of splits and least-change performance and are not intended to represent valid districting proposals under the U.S. constitution’s one-person, one-vote doctrine for congressional maps [29].

  9. Incumbent addresses were found in the Minnesota Secretary of State Candidate Filing records. [2].

  10. We transferred block assignments for the plans onto wards, so the scores in Table 4 would be slightly different if computed at the more granular level. Ward-level plans can be found at https://github.com/daragold/subdivision_metrics_paper.

  11. Our sample grid, Minnesota and Wisconsin plans, as well as the data and code to reproduce the tables in this paper can be found at https://github.com/daragold/subdivision_metrics_paper.

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Acknowledgements

The authors thank Daryl DeFord, Sam Hirsch and Amara Jaeger for extremely detailed and insightful feedback on previous drafts of this paper. The authors also thank Jessie Amunson and Moon Duchin for helpful conversations on these topics.

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  1. A Becker Consulting LLC, Cambridge, MA, USA

    Amariah Becker

  2. The Washington Post, News Engineering - Elections, Washington, DC, USA

    Dara Gold

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Correspondence to Dara Gold.

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This paper is based on work that was funded by Jenner & Block LLP.(Both authors worked at the Metric Geometry and Gerrymandering Group (MGGG) at Tufts University while conducting this research.)

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Becker, A., Gold, D. The gameability of redistricting criteria. J Comput Soc Sc 5, 1735–1777 (2022). https://doi.org/10.1007/s42001-022-00180-w

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