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Gary King, Harvard University: “How to Measure Legislative District Compactness If You Only Know it When You See It”

April 18, 2019 @ 4:00 pm - 5:30 pm

Haven Hall

gary king

 

The Statistical Learning Interdisciplinary Workshop is thrilled to announce that Gary King, Albert J. Weatherhead III University Professor at Harvard University, Director of the Institute for Quantitative Social Science, and member of the Steering Committee of the Harvard Data Science Initiative will be at the University of Michigan presenting a workshop. People not in Ann Arbor will be able to join the workshop via bluejeans connection. All the details are below. SAVE THE DATE!

 

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Title: How to Measure Legislative District Compactness If You Only Know it When You See It
Abstract: see slides here
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 then 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 discuss our complex computational requirements, a perspective on research computing from the social sciences, and software to compute our compactness measure from any district.

 

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