Measuring partisan fairness

Mira Bernstein and Olivia Walch
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Mira Bernstein: Metric Geometry and Gerrymandering Group (MGGG)
Olivia Walch: University of Michigan–Ann Arbor

A chapter in Political Geometry, 2022, pp 39-75 from Springer

Abstract: Abstract What does fairness in the context of redistricting look like? Can you identify a gerrymander based on election results alone? In this chapter, two mathematicians examine a variety of metrics that have been proposed in the courts as tools to detect partisan gerrymandering and to quantify its effects. The takeaway is that most of these metrics can lead to counterintuitive results. They are also unstable: slightly different conditions can yield markedly different outcomes. Fundamentally, these metrics share a common problem: you cannot interpret them without the context of what is “normal” for a particular state, based on the geographic distribution of its voters.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-69161-9_2

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DOI: 10.1007/978-3-319-69161-9_2

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