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Multi-balanced redistricting

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Abstract

The one person–one vote principle for political redistricting requires balancing populations across districts. We address the matter of simultaneously balancing a second attribute across districts, proving that this is always possible to within reasonable tolerances. Feasibility is demonstrated by formulating the problem as a constrained partitioning problem on graphs. The resulting computational results demonstrate the practicality of obtaining dual-balanced districts whose balance for both attributes is well within reasonable deviations from the ideal values. Applications include attempts to avoid differential population growth leading to malapportionment between decennial census counts or simultaneously balancing total and voting-age populations.

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Data availability

The raw data used in this paper is publicly available from [20, 21] and https://redistrictingdatahub.org. Replication code for the empirical experiments is available at [14].

Notes

  1. https://redistrictingdatahub.org.

  2. This is sometimes referred to as “eligible-voter” redistricting where the plans are balanced according to citizen, voting-age population, or CVAP.

References

  1. AAJC, MALDEF, and National Conference on Citizenship (Organizers): Statement on Appropriate Data for Redistricting, https://www.advancingjustice-aajc.org/sites/default/files/2021-04/Statement%20on%20Appropriate%20Data%20for%20Redistricting%20FINAL%204.27.2021.pdf, (2021).

  2. Alexeev, Boris, & Mixon, Dustin G. (2018). Partisan gerrymandering with geographically compact districts. Journal of Applied Probability, 55(4), 1046–1059. https://doi.org/10.1017/jpr.2018.70

    Article  Google Scholar 

  3. Badger, E.: People Who Can’t Vote Still Count Politically in America. What if That Changes?, New York Times Upshot, (2019).

  4. Bar-Natan, A., Najt, L., & Schutzman, Z. (2020). The gerrymandering jumble: map projections permute districts’ compactness scores. Cartography and Geographic Information Science, 47(4), 321–335.

    Article  Google Scholar 

  5. Barnes, R., & Solomon, J. (2021). Gerrymandering and Compactness: Implementation Flexibility and Abuse. Political Analysis, 29(4), 448–466.

    Article  Google Scholar 

  6. Becker, A., & Gold, D. (2022). The gameability of redistricting criteria. Journal of Computational Social Science, 5, 1735–1777.

    Article  Google Scholar 

  7. Bernstein, M., & Duchin, M. (2017). A formula goes to court: Partisan gerrymandering and the efficiency gap. Notices of the American Mathematical Society, 64(9), 1020–1024.

    Article  Google Scholar 

  8. Bespamyatnikh, S., Kirkpatrick, D., & Snoeyink, J. (2000). Generalizing ham sandwich cuts to equitable subdivisions. Discrete and Computational Geometry, 24(4), 605–622.

    Article  Google Scholar 

  9. Boland, J., Rudensky, Y., & Li, M. (2021). Why States Should Wait for Census Data to Draw Voting Districts , Brennan Center for Justice Report, https://www.brennancenter.org/media/7532/download,

  10. Chen, Jowei, & Stephanopoulos, Nicholas. (2021). Democracy’s Denominator. California Law Review, 109, 1019–1065.

    Google Scholar 

  11. DeFord, D., Dhamankar, N., Duchin, M., Gupta, V., McPike, M., Schoenbach, G., & Sim, K. (2021). Implementing partisan symmetry: Problems and paradoxes, Political Analysis, 1-20.

  12. DeFord, D., Duchin, D., & Solomon, J. (2020). A computational approach to measuring vote elasticity and competitiveness. Statistics and Public Policy, 7(1), 69–86.

    Article  Google Scholar 

  13. DeFord, D., Duchin, D., & Solomon, J. (2021). ReCombination: A family of Markov chains for redistricting, Harvard Data Science Review, 3(1),

  14. Deford, D., Kimsey, E., & Zerr, R. (2022). Replication Data and Code for WA experiments in “Multi-Balanced Redistricting”, https://github.com/drdeford/MBR_WA.

  15. Duchin, M., & Tenner, B. E. (2018). Discrete geometry for electoral geography, arXiv:1808.05860.

  16. Edelman, P. H. (2016). Evenwel, Voting Power, and Dual Districting. Journal of Legal Studies, 45(1), 203–221.

    Article  Google Scholar 

  17. Hirsch, S. (2003). The United States House of Unrepresentatives: What Went Wrong in the Latest Round of Congressional Redistricting. Election Law Journal, 2(2), 179–216.

    Article  Google Scholar 

  18. Kaneko, A., & Kano, M. (1999). Balanced partitions of two sets of points in the plane. Computational Geometry: Theory and Applications, 13, 253–261.

    Article  Google Scholar 

  19. Katz, J., King, G., & Rosenblatt, E. (2020). Theoretical Foundations and Empirical Evaluations of Partisan Fairness in District-Based Democracies. American Political Science Review, 114(1), 164–178.

    Article  Google Scholar 

  20. Manson, S., Schroeder, J., Van Riper, D., Kugler, T., & Ruggles, S. (2021). IPUMS National Historical Geographic Information System: Version 16.0 [dataset], Minneapolis, MN: IPUMS. https://doi.org/10.18128/D050.V16.0

  21. NDSU Center for Social Research: ND Compass: State Legislative District Profiles, available at https://www.ndcompass.org/legislative-district-profiles/, accessed on 23 May 2021.

  22. Rudensky, Y., Li, M., & Lìmon, G. (2021). The Impact of Census Timeline Changes on the Next Round of Redistricting, Brennan Center for Justice Report, https://www.brennancenter.org/media/7532/download

  23. Sakai, T. (2002). Balanced convex partitions of measures in \(\mathbb{R} ^n\). Graphs Combin., 18(1), 169–192.

    Article  Google Scholar 

  24. Soberón, P. (2017). Gerrymandering, sandwiches, and topology. Notices of the American Mathematical Society, 64(9), 1010–1013.

    Article  Google Scholar 

  25. Stephanopoulos, Nicholas, & McGhee, Eric. (2015). Partisan Gerrymandering and the Efficiency Gap. University of Chicago Law Review, 82, 831–900.

    Google Scholar 

  26. Ueckerdt, T. (2021). Lecture Notes: Combinatorics in the Plane, available at https://www.math.kit.edu/iag6/lehre/combplane2013s/media/lecture_notes.pdf, accessed on 21 May

  27. Washington State Legislature: Rules Code of Washington: 44.05.140 Residence of certain individuals-Last known place of residence., https://app.leg.wa.gov/Rcw/default.aspx?cite=44.05.140, accessed May 11, 2023.

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Acknowledgements

E. K. was supported by the Ellen Hauge Abelson Scholarship for undergraduate research from the Washington State University College of Arts and Sciences.

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Correspondence to Daryl DeFord.

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D. D. has previously served as an expert in redistricting cases. E. K. and R. Z. have no conflicts to report.

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DeFord, D., Kimsey, E. & Zerr, R. Multi-balanced redistricting. J Comput Soc Sc 6, 923–941 (2023). https://doi.org/10.1007/s42001-023-00217-8

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