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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Main Authors: CHOU, Christine, KIMBROUGH, Steven O., MURPHY, Frederic H., SULLIVAN-FEDOCK, John, WOODARD, C. Jason
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access: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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spelling 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
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic systems design
evolutionary design
emotive design
genetic algorithms
evolutionary computing
districting
zone design
compactness
redistricting
reapportionment
interactive evolutionary computing
Computer Sciences
spellingShingle 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
description 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.
format text
author 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
author_sort 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
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url 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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