Replication Data for: How to Measure Legislative District Compactness If You Only Know It When You See It
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'To deter gerrymandering, many state constitutions require legislative districts to be“compact.” Yet, the law offers few precise definitions other than “you know it whenyou see it,” which effectively implies a common understanding of the concept. Incontrast, academics have shown that compactness has multiple dimensions and havegenerated many conflicting measures. We hypothesize that both are correct—thatcompactness is complex and multidimensional, but a common understanding existsacross 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 forredistricting, amon' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Machine learning","Measurement","Redistricting"]} <|eot_id|>
 Here is the Description of a dataset. Description:'To deter gerrymandering, many state constitutions require legislative districts to be“compact.” Yet, the law offers few precise definitions other than “you know it whenyou see it,” which effectively implies a common understanding of the concept. Incontrast, academics have shown that compactness has multiple dimensions and havegenerated many conflicting measures. We hypothesize that both are correct—thatcompactness is complex and multidimensional, but a common understanding existsacross 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 forredistricting, amon' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
To deter gerrymandering, many state constitutions require legislative districts to be“compact.” Yet, the law offers few precise definitions other than “you know it whenyou see it,” which effectively implies a common understanding of the concept. Incontrast, academics have shown that compactness has multiple dimensions and havegenerated many conflicting measures. We hypothesize that both are correct—thatcompactness is complex and multidimensional, but a common understanding existsacross 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 forredistricting, amon
Machine learning; Measurement; Redistricting