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dc.contributor.advisorLuna, Marcosen_US
dc.contributor.advisorRatner, Keithen_US
dc.contributor.advisorStrohschein, Daviden_US
dc.contributor.authorHugenberger, Sarah
dc.creatorHugenberger, Sarahen_US
dc.date2021-11-24T14:05:37.000en_US
dc.date.accessioned2021-11-29T11:28:06Z
dc.date.available2021-11-29T11:28:06Z
dc.date.issued2019-05-01en_US
dc.date.submitted2020-09-02T07:35:26-07:00en_US
dc.identifiergraduate_theses/35en_US
dc.identifier.urihttp://hdl.handle.net/20.500.13013/563en_US
dc.description.abstractPolitical redistricting plans often need to consider the compactness of the district’s shape. For states requiring districts to be compact, there is a need to quantify compactness. Existing measures of compactness unfairly penalize districts with coastlines and islands or whose geography itself is not compact. By incorporating information about the underlying geography into the calculation of a modified compactness score, it would be possible to use a compactness test more effectively and fairly across all districts. Several methods of incorporating such data were explored with test districts. A Python script was created to apply the calculations behind the selected method to any polygon shapefile. The script was run on the 436 districts of the 114th Congress of the United States to consider and analyze the modified compactness calculation and its usefulness. Scores for districts covering areas with a significant amount of water were improved when the modified compactness calculation was applied.en_US
dc.formatflash_audio
dc.titleImproving Compactness Measures For Political Districtsen_US
dc.typeThesisen_US
dc.legacy.embargo2020-09-02T00:00:00-07:00en_US
dc.legacy.pubstatuspublisheden_US
dc.description.departmentGeographyen_US
dc.date.displayMay-19en_US
dc.type.degreeMaster of Science (MS)en_US
dc.legacy.pubtitleGraduate Thesesen_US
dc.legacy.identifierhttps://digitalcommons.salemstate.edu/cgi/viewcontent.cgi?article=1038&context=graduate_theses&unstamped=1en_US
dc.legacy.identifieritemhttps://digitalcommons.salemstate.edu/graduate_theses/35en_US


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