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        <identifier>oai:drops-oai.dagstuhl.de:20090</identifier>
        <datestamp>2024-06-10T05:20:53Z</datestamp>
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          <dc:title>Drawing Competitive Districts in Redistricting</dc:title>
          <dc:creator>Chuang, Gabriel</dc:creator>
          <dc:creator>Hanguir, Oussama</dc:creator>
          <dc:creator>Stein, Clifford</dc:creator>
          <dc:subject>Redistricting</dc:subject>
          <dc:subject>Computational Complexity</dc:subject>
          <dc:subject>Algorithms</dc:subject>
          <dc:description>In the process of redistricting, one important metric is the number of competitive districts, that is, districts where both parties have a reasonable chance of winning a majority of votes. Competitive districts are important for achieving proportionality, responsiveness, and other desirable qualities; some states even directly list competitiveness in their legally-codified districting requirements. In this work, we discuss the problem of drawing plans with at least a fixed number of competitive districts. In addition to the standard, "vote-band" measure of competitivenesss (i.e., how close was the last election?), we propose a measure that explicitly considers "swing voters" - the segment of the population that may choose to vote either way, or not vote at all, in a given election. We present two main, contrasting results. First, from a computational complexity perspective, we show that the task of drawing plans with competitive districts is NP-hard, even on very natural instances where the districting task itself is easy (e.g., small rectangular grids of population-balanced cells). Second, however, we show that a simple hill-climbing procedure can in practice find districtings on real states in which all the districts are competitive. We present the results of the latter on the precinct-level graphs of the U.S. states of North Carolina and Arizona, and discuss trade-offs between competitiveness and other desirable qualities.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Gabriel Chuang and Oussama Hanguir and Clifford Stein</dc:contributor>
          <dc:date>2024</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 295, 5th Symposium on Foundations of Responsible Computing (FORC 2024)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.FORC.2024.7</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-200902</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2024.7</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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