Skip to Main Content

Bulletin of the American Mathematical Society

The Bulletin publishes expository articles on contemporary mathematical research, written in a way that gives insight to mathematicians who may not be experts in the particular topic. The Bulletin also publishes reviews of selected books in mathematics and short articles in the Mathematical Perspectives section, both by invitation only.

ISSN 1088-9485 (online) ISSN 0273-0979 (print)

The 2020 MCQ for Bulletin of the American Mathematical Society is 0.84.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.

 

Geometry, inference, complexity, and democracy
HTML articles powered by AMS MathViewer

by Jordan S. Ellenberg HTML | PDF
Bull. Amer. Math. Soc. 58 (2021), 57-77 Request permission

Abstract:

Decisions about how the population of the United States should be divided into legislative districts have powerful and not fully understood effects on the outcomes of elections. The problem of understanding what we might mean by “fair districting” intertwines mathematical, political, and legal reasoning; but only in recent years has the academic mathematical community gotten directly involved in the process. Here I report on recent progress in this area, how newly developed mathematical tools have affected real political decisions, and what remains to be done. This survey represents the content of a lecture presented by the author in the Current Events Bulletin session of the Joint Mathematics Meetings in January 2020.
References
  • Mira Bernstein and Moon Duchin, A formula goes to court: partisan gerrymandering and the efficiency gap, Notices Amer. Math. Soc. 64 (2017), no. 9, 1020–1024. MR 3699778, DOI 10.1090/noti1573
  • Matthew Baker and Yao Wang, The Bernardi process and torsor structures on spanning trees, Int. Math. Res. Not. IMRN 16 (2018), 5120–5147. MR 3848228, DOI 10.1093/imrn/rnx037
  • S. Bickerstaff, Election Systems and Gerrymandering Worldwide, Springer (2020).
  • D. Carter, G. Herschlag, Z. Hunter, and J. Mattingly, A Merge-Split Proposal for Reversible Monte Carlo Markov Chain Sampling of Redistricting Plans, arXiv:1911.01503 (2019).
  • Melody Chan, Thomas Church, and Joshua A. Grochow, Rotor-routing and spanning trees on planar graphs, Int. Math. Res. Not. IMRN 11 (2015), 3225–3244. MR 3373049, DOI 10.1093/imrn/rnu025
  • J. Chen and J. Rodden, Unintentional gerrymandering: Political geography and electoral bias in legislatures, Quarterly Journal of Political Science, 8 (2013), no. 3, 239–269.
  • Maria Chikina, Alan Frieze, and Wesley Pegden, Assessing significance in a Markov chain without mixing, Proc. Natl. Acad. Sci. USA 114 (2017), no. 11, 2860–2864. MR 3628186, DOI 10.1073/pnas.1617540114
  • M. Chikina, A. Frieze, J. Mattingly, and W. Pegden, Practical tests for significance in Markov Chains, arXiv:1904.04052 (2019).
  • D. DeFord, M. Duchin, and J. Solomon, A Computational Approach to Measuring Vote Elasticity and Competitiveness (2019).
  • D. DeFord, M. Duchin, and J. Solomon, Recombination: a family of Markov chains for redistricting arXiv:1911.05725 (2019).
  • M. Duchin, Outlier analysis for Pennsylvania congressional redistricting (2018).
  • M. Duchin, T. Gladkova, E. Henninger-Voss, B. Klingensmith, H. Newman, and H. Wheelen, Locating the representational baseline: Republicans in Massachusetts arXiv:1810.09051 (2018).
  • M. Duchin and B. E. Tenner, Discrete geometry for electoral geography, arXiv preprint arXiv:1808.05860 (2018).
  • B. Fifield, M. Higgins, K. Imai, and A. Tarr, A new automated redistricting simulator using Markov chain Monte Carlo, Working Paper, Princeton University, Princeton, NJ (2015).
  • Alexander Gamburd and Igor Pak, Expansion of product replacement graphs, Combinatorica 26 (2006), no. 4, 411–429. MR 2260846, DOI 10.1007/s00493-006-0023-0
  • G. Herschlag, R. Ravier, and J. Mattingly, Evaluating Partisan Gerrymandering in Wisconsin, arXiv:1709.01596 (2017).
  • J. Mattingly, Expert Report on the North Carolina State Legislature, available at https://sites.duke.edu/quantifyinggerrymandering/files/2019/09/Report.pdf (2019).
  • J. C. Mattingly and C. Vaughn, Redistricting and the Will of the People, arXiv preprint arXiv:1410.8796 (2014).
  • Metric Geometry and Gerrymandering Group, GerryChain, available at https://gerrychain.readthedocs.io/en/latest/.
  • Metric Geometry and Gerrymandering Group, Comparison of Districting Plans for the Virginia House of Delegates (2018).
  • L. Najt, D. DeFord, and J. Solomon, Complexity and Geometry of Sampling Connected Graph Partitions, arXiv:1908.08881 (2019).
  • W. Pegden, A. Procaccia, and D. Yu, A partisan districting protocol with provably nonpartisan outcomes, arXiv:1710.08781 (2017).
  • N. Stephanopoulos and E. McGhee, Partisan gerrymandering and the efficiency gap, U. Chi. L. Rev. 82 (2015), 831.
  • Kristopher Tapp, Measuring political gerrymandering, Amer. Math. Monthly 126 (2019), no. 7, 593–609. MR 3979734, DOI 10.1080/00029890.2019.1609324
Similar Articles
  • Retrieve articles in Bulletin of the American Mathematical Society with MSC (2010): 91B12, 05C90
  • Retrieve articles in all journals with MSC (2010): 91B12, 05C90
Additional Information
  • Jordan S. Ellenberg
  • Affiliation: University of Wisconsin-Madison, Madison, Wisconsin
  • MR Author ID: 366432
  • Email: ellenber@math.wisc.edu
  • Received by editor(s): June 24, 2020
  • Published electronically: November 2, 2020
  • © Copyright 2020 American Mathematical Society
  • Journal: Bull. Amer. Math. Soc. 58 (2021), 57-77
  • MSC (2010): Primary 91B12, 05C90
  • DOI: https://doi.org/10.1090/bull/1708
  • MathSciNet review: 4188808