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The Efficiency Gap After Gill v. Whitford

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  • Mark Rush

Abstract

Objective The objective of this article is to analyze the reasoning underpinning the Supreme Court's rejection of the efficiency gap in Gill v. Whitford as a useful measure of partisan fairness in redistricting. Methods I undertake this analysis by reviewing prior judicial commentary on measures of partisan fairness and debates among political science professionals concerning how and whether to use aggregate statewide seat and vote totals to assess whether there is bias across legislative district elections. Results The analysis reveals that the Supreme Court's rejection of the efficiency gap and other statewide measures of partisan fairness is based upon thoughtful skepticism of the extent to which votes cast under different conditions in different legislative districts for choices among discrete slates of candidates can be aggregated meaningfully into statewide measures that ignore these district‐specific conditions. This skepticism is reinforced by debates among scholars about how and whether partisan votes can be aggregated in this manner. Conclusion The Court's rejection of the efficiency gap and skepticism about other aggregate measures of partisan fairness in redistricting reinforces the extensive criticism of using the single‐member district electoral system. It distorts electoral outcomes, limits voter choice, and, thereby, renders comparisons of partisan votes in different districts quite questionable. A shift to multimember districts with some form of proportional representation such as ranked choice voting would resolve much of the criticism of and uncertainty in redistricting analysis based on the statewide aggregation of discrete legislative district election results.

Suggested Citation

  • Mark Rush, 2020. "The Efficiency Gap After Gill v. Whitford," Social Science Quarterly, Southwestern Social Science Association, vol. 101(1), pages 53-67, January.
  • Handle: RePEc:bla:socsci:v:101:y:2020:i:1:p:53-67
    DOI: 10.1111/ssqu.12742
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