A Logical Model for Predicting Minority Representation
Application to Redistricting and Voting Rights Cases
Bibliographic Data
| ID | 3124805 |
|---|---|
| Authors | Yuki Atsusaka (0000-0001-5365-1876, Rice University, corresponding author) |
| Year | 2021 |
| Volume | 115 |
| Issue | 4 |
| Pages | 1210-1225 |
| Publication date | 2021-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Political Science Review (JOURNAL) |
| Journal identifiers | ISSN: 0003-0554 • E-ISSN: 1537-5943 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s000305542100054x |
| OpenAlex | W3175851148 |
| Language | EN |
| Citations received | 11 |
| References cited | 71 |
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
Gerrymandering · Legislature · Majority rule · Political science · Politics · Redistricting · Representation (politics · Voting · Artificial Intelligence · Computer Science · Electoral Systems and Political Participation · Judicial and Constitutional Studies · Law · Political Influence and Corporate Strategies · Public Administration
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| Unique citing works | 11 |
|---|---|
| Citations per year | 2,75 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 11 |