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How to Measure Legislative District Compactness If You Only Know It When You See It
Author(s) -
Kaufman Aaron R.,
King Gary,
Komisarchik Mayya
Publication year - 2021
Publication title -
american journal of political science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.347
H-Index - 170
eISSN - 1540-5907
pISSN - 0092-5853
DOI - 10.1111/ajps.12603
Subject(s) - gerrymandering , compact space , legislature , redistricting , measure (data warehouse) , computer science , reliability (semiconductor) , state (computer science) , political science , mathematics , law , data mining , algorithm , pure mathematics , politics , power (physics) , physics , quantum mechanics , democracy
To deter gerrymandering, many state constitutions require legislative districts to be “compact.” Yet, the law offers few precise definitions other than “you know it when you see it,” which effectively implies a common understanding of the concept. In contrast, academics have shown that compactness has multiple dimensions and have generated many conflicting measures. We hypothesize that both are correct—that compactness is complex and multidimensional, but a common understanding exists across people. We develop a survey to elicit this understanding, with high reliability (in data where the standard paired comparisons approach fails). We create a statistical model that predicts, with high accuracy, solely from the geometric features of the district, compactness evaluations by judges and public officials responsible for redistricting, among others. We also offer compactness data from our validated measure for 17,896 state legislative and congressional districts, as well as software to compute this measure from any district.