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Replication Data for: Partisan Dislocation: A Precinct-Level Measure of Representation and Gerrymandering

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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/MERAIC
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We introduce a fine-grained measure of the extent to which electoral districts combine and split local communities of co-partisans in unnatural ways. Our indicator -- which we term Partisan Dislocation -- is a measure of the difference between the partisan composition of a voter's geographic nearest neighbors and that of her assigned district. We show that our measure is a good local and global indicator of district manipulation, easily identifying instances in which districts carve up clusters of co-partisans (cracking) or combine them in unnatural ways (packing). We demonstrate that our measure is related to but distinct from other approaches to the measurement of gerrymandering, and has some clear advantages, above all as a complement to simulation-based approaches, and as a way to identify the specific neighborhoods most affected by gerrymandering. It can also be used prospectively by district-drawers who wish to create maps that reflect voter geography, but according to our analysis, that goal will sometimes be in conflict with the goal of partisan fairness.
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Harvard Dataverse
创建时间:
2020-12-15
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