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Replication Data for: Theoretical Foundations and Empirical Evaluations of Partisan Fairness in District-Based Democracies

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NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://doi.org/10.7910/DVN/FTYHPJ
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资源简介:
We clarify the theoretical foundations of partisan fairness standards for district-based democratic electoral systems, including essential assumptions and definitions that have not been formalized or in some cases even discussed. We also offer extensive empirical evidence for assumptions with observable implications. Throughout, we follow a fundamental principle of statistical inference too often ignored — defining the quantity of interest separately so its measures can be proven wrong, evaluated, or improved. This enables us to prove which of the many newly proposed fairness mea- sures are statistically appropriate and which are biased, limited, or not measures of the theoretical quantity they seek to estimate at all. Because real world redistricting and gerrymandering involves complicated politics with numerous participants and conflicting goals, measures biased for partisan fairness sometimes still provide use- ful descriptions of other aspects of electoral systems.
创建时间:
2019-08-26
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