On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences
Use of optimization models in science and policy applications is often problematic because the best available models are very inaccurate representations of the originating problems. Such is the case with electoral districting models, for which there exist no generally accepted measures of compactnes...
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sg-smu-ink.sis_research-34752015-03-24T08:00:23Z On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences CHOU, Christine KIMBROUGH, Steven O. MURPHY, Frederic H. SULLIVAN-FEDOCK, John WOODARD, C. Jason Use of optimization models in science and policy applications is often problematic because the best available models are very inaccurate representations of the originating problems. Such is the case with electoral districting models, for which there exist no generally accepted measures of compactness, in spite of many proposals and much analytical study. This article reports on an experimental investigation of subjective judgments of compactness for electoral districts. The experiment draws on a unique database of 116 distinct, legally valid districting plans for the Philadelphia City Council, discovered with evolutionary computation. Subjects in the experiment displayed, in the aggregate, remarkable agreement with several standard measures of compactness, thus providing warrant for use of these measures that has heretofore been unavailable. The exercise also lends support to the underlying methodology on display here, which proposes to use models based on subjective judgments in combination with algorithms that find multiple solutions in order to support application of optimization models in contexts in which they are only very approximate representations. 2014-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2476 info:doi/10.2139/ssrn.2446417 https://ink.library.smu.edu.sg/context/sis_research/article/3475/viewcontent/EmpiricalValidation_CKMSW_SSCR_2014.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University systems design evolutionary design emotive design genetic algorithms evolutionary computing districting zone design compactness redistricting reapportionment interactive evolutionary computing Computer Sciences |
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systems design evolutionary design emotive design genetic algorithms evolutionary computing districting zone design compactness redistricting reapportionment interactive evolutionary computing Computer Sciences CHOU, Christine KIMBROUGH, Steven O. MURPHY, Frederic H. SULLIVAN-FEDOCK, John WOODARD, C. Jason On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
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Use of optimization models in science and policy applications is often problematic because the best available models are very inaccurate representations of the originating problems. Such is the case with electoral districting models, for which there exist no generally accepted measures of compactness, in spite of many proposals and much analytical study. This article reports on an experimental investigation of subjective judgments of compactness for electoral districts. The experiment draws on a unique database of 116 distinct, legally valid districting plans for the Philadelphia City Council, discovered with evolutionary computation. Subjects in the experiment displayed, in the aggregate, remarkable agreement with several standard measures of compactness, thus providing warrant for use of these measures that has heretofore been unavailable. The exercise also lends support to the underlying methodology on display here, which proposes to use models based on subjective judgments in combination with algorithms that find multiple solutions in order to support application of optimization models in contexts in which they are only very approximate representations. |
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CHOU, Christine KIMBROUGH, Steven O. MURPHY, Frederic H. SULLIVAN-FEDOCK, John WOODARD, C. Jason |
author_facet |
CHOU, Christine KIMBROUGH, Steven O. MURPHY, Frederic H. SULLIVAN-FEDOCK, John WOODARD, C. Jason |
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CHOU, Christine |
title |
On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
title_short |
On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
title_full |
On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
title_fullStr |
On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
title_full_unstemmed |
On Empirical Validation of Compactness Measures for Electoral Redistricting and Its Significance for Application of Models in the Social Sciences |
title_sort |
on empirical validation of compactness measures for electoral redistricting and its significance for application of models in the social sciences |
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Institutional Knowledge at Singapore Management University |
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2014 |
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https://ink.library.smu.edu.sg/sis_research/2476 https://ink.library.smu.edu.sg/context/sis_research/article/3475/viewcontent/EmpiricalValidation_CKMSW_SSCR_2014.pdf |
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