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A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases

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  • ATSUSAKA, YUKI

Abstract

Understanding when and why minority candidates emerge and win in particular districts entails critical implications for redistricting and the Voting Rights Act. I introduce a quantitatively predictive logical model of minority candidate emergence and electoral success—a mathematical formula based on deductive logic that can logically explain and accurately predict the exact probability at which minority candidates run for office and win in given districts. I show that the logical model can predict about 90% of minority candidate emergence and 95% of electoral success by leveraging unique data of mayoral elections in Louisiana from 1986 to 2016 and state legislative general elections in 36 states in 2012 and 2014. I demonstrate that the logical model can be used to answer many important questions about minority representation in redistricting and voting rights cases. All applications of the model can be easily implemented via an open-source software logical.

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  • Atsusaka, Yuki, 2021. "A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases," American Political Science Review, Cambridge University Press, vol. 115(4), pages 1210-1225, November.
    • Handle: RePEc:cup:apsrev:v:115:y:2021:i:4:p:1210-1225_8
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