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 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">Terra Politica</journal-id>
   <journal-title-group>
    <journal-title xml:lang="en">Terra Politica</journal-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Terra Politica</trans-title>
    </trans-title-group>
   </journal-title-group>
   <issn publication-format="print">3033-537X</issn>
   <issn publication-format="online">3033-7321</issn>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="publisher-id">112025</article-id>
   <article-id pub-id-type="doi">10.63115/1632.2025.27.58.012</article-id>
   <article-id pub-id-type="edn">QVJKQD</article-id>
   <article-categories>
    <subj-group subj-group-type="toc-heading" xml:lang="ru">
     <subject>AD HOC</subject>
    </subj-group>
    <subj-group subj-group-type="toc-heading" xml:lang="en">
     <subject>AD HOC</subject>
    </subj-group>
    <subj-group>
     <subject>AD HOC</subject>
    </subj-group>
   </article-categories>
   <title-group>
    <article-title xml:lang="en">APPLYING NETWORK MODELS FOR ANALYSIS TO SPATIAL ANALYSIS OF GERRYMANDERING PRACTICES IN THE 2000-2020 U.S. CONGRESSIONAL ELECTIONS</article-title>
    <trans-title-group xml:lang="ru">
     <trans-title>Опыт применения сетевых моделей для анализа для пространственного анализа практик джерримендеринга на выборах в Конгресс США в 2000–2020 гг.</trans-title>
    </trans-title-group>
   </title-group>
   <contrib-group content-type="authors">
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Глумов</surname>
       <given-names>Филипп Владиславович</given-names>
      </name>
      <name xml:lang="en">
       <surname>Glumov</surname>
       <given-names>Filipp Vladislavovich</given-names>
      </name>
     </name-alternatives>
    </contrib>
    <contrib contrib-type="author">
     <name-alternatives>
      <name xml:lang="ru">
       <surname>Мальцев</surname>
       <given-names>Артём Михайлович</given-names>
      </name>
      <name xml:lang="en">
       <surname>Mal'cev</surname>
       <given-names>Artem Mihaylovich</given-names>
      </name>
     </name-alternatives>
    </contrib>
   </contrib-group>
   <pub-date publication-format="print" date-type="pub" iso-8601-date="2025-07-01T00:00:00+03:00">
    <day>01</day>
    <month>07</month>
    <year>2025</year>
   </pub-date>
   <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-07-01T00:00:00+03:00">
    <day>01</day>
    <month>07</month>
    <year>2025</year>
   </pub-date>
   <issue>1</issue>
   <fpage>167</fpage>
   <lpage>188</lpage>
   <history>
    <date date-type="received" iso-8601-date="2025-03-01T00:00:00+03:00">
     <day>01</day>
     <month>03</month>
     <year>2025</year>
    </date>
    <date date-type="accepted" iso-8601-date="2025-06-01T00:00:00+03:00">
     <day>01</day>
     <month>06</month>
     <year>2025</year>
    </date>
   </history>
   <self-uri xlink:href="https://terrapolitica.ru/en/nauka/article/112025/view">https://terrapolitica.ru/en/nauka/article/112025/view</self-uri>
   <abstract xml:lang="ru">
    <p>Настоящее исследование посвящено явлению джерримендеринга на примере выборов в Конгресс США. Для анализа были использованы границы избирательных округов в Конгресс США. Деление штатов на округа было основано на данных переписей, проводившихся с 2000 по 2020 годы. Данные о малых административных единицах (графствах) аналогично опираются на данные переписи. В статье теоретизируются перспективы применения методов инферентного сетевого анализа для изучения пространственных данных распределения территорий графств штатов между избирательными округами. Так, в частности, методы статистических моделей, основанных на экспоненциальных случайных графах (Exponential Random Graph Model, ERGM), могут быть адаптированы оценки закономерностей объединения или перераспределения отдельных графств между едиными избирательными округами. Такие модели позволяют идентифицировать статистически значимые эффекты факторов электоральной инженерии в виде стратегической манипуляции границами избирательных округов («ручной отрисовки»), при которой объединение графств осуществляется не на основе географической близости населенных районов, но продиктовано специфическими социо-демографическими и политическими характеристиками отдельных графств. Применение сетевого анализа обуславливается «диадной» структурой пространственных данных, при которых отдельные наблюдения (графства) объединяются парными связями общей принадлежности к избирательным округам, что, в свою очередь, приводит к формированию сетевого графа аффилиации (affiliation network). Указанный метод, потенциально, позволяет описать механизм перераспределения малых электоральных единиц в рамках избирательных округов. Исследователями были проверены гипотезы о социально-политических факторах, оказывающих влияние на устройство данного механизма: рассмотрена роль партийных интересов, а также роль подавления и защиты расовых меньшинств как важных факторов, формирующих американский политический дискурс. Результаты сетевого анализа демонстрируют значимость социо-демографических предикторов, что подтверждает наличие взаимосвязи между расо вым составом населения графств и геопространственной нарезкой избирательных округов. Эффекты для любого фактора являются неоднородными в рамках страны, демонстрируя существенно различные результаты между штатами. Полученные оценки не позволяют сделать однозначного вывода о выдвинутых гипотезах, так как группы штатов, где проявляются те или иные признаки не всегда подлежат осмысленному обобщению. Полученные результаты в целом иллюстрируют эвристический потенциал адаптации методологии сетевого анализа для решения теоретических задач политической географии.</p>
   </abstract>
   <trans-abstract xml:lang="en">
    <p>The present study is devoted to the phenomenon of gerrymandering on the example of US Congressional elections. The boundaries of US Congressional electoral districts were used for the analysis. The division of states into districts was based on census data from 2000 to 2020. Data on small administrative units (counties) similarly relied on census data. This article theorizes the prospects of applying inferential network analysis methods to study spatial data of state county area distributions among electoral districts. In particular, methods of statistical models based on Exponential Random Graph Model (ERGM) can be adapted to assess patterns of aggregation or redistribution of individual counties between single electoral districts. Such models allow identifying statistically significant effects of electoral engineering factors in the form of strategic manipulation of constituency boundaries (“hand-drawing”), whereby the unification of counties is not based on the geographical proximity of populated areas, but is dictated by the specific socio-demographic and political characteristics of individual counties. The use of network analysis is conditioned by the “dyad” structure of spatial data, in which individual observations (counties) are united by pairwise ties of common affiliation to constituencies, which in turn leads to the formation of an affiliation network graph. This method potentially allows describing the mechanism of redistribution of small electoral units within constituencies. The researchers tested hypotheses about the socio-political factors that influence this mechanism - the role of partisan interests, as well as the role of suppression and protection of racial minorities as important factors shaping American political discourse. The results of the network analysis demonstrate the significance of socio-demographic predictors, confirming the relationship between the racial composition of county populations and the geospatial slicing of electoral districts. The effects for any factor are not homogeneous within the country, showing significantly different results between states. The resulting estimates do not allow for a clear conclusion about the hypotheses, as the groups of states where particular attributes are evident are not always subject to meaningful eneralization. The results generally illustrate the euristic potential of adapting the methodology of network analysis to solve theoretical problems of political geography.</p>
   </trans-abstract>
   <kwd-group xml:lang="ru">
    <kwd>сетевой анализ</kwd>
    <kwd>джерримендеринг</kwd>
    <kwd>электоральная география</kwd>
    <kwd>США</kwd>
    <kwd>выборы</kwd>
   </kwd-group>
   <kwd-group xml:lang="en">
    <kwd>network analysis</kwd>
    <kwd>gerrymandering</kwd>
    <kwd>electoral geography</kwd>
    <kwd>USA</kwd>
    <kwd>elections</kwd>
   </kwd-group>
  </article-meta>
 </front>
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 <back>
  <ref-list>
   <ref id="B1">
    <label>1.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Cain B.E. (1985), Assessing the partisan effects of redistricting, American Political Science Review, vol. 79, no. 2, pp. 320-333.</mixed-citation>
     <mixed-citation xml:lang="en">Cain B.E. (1985), Assessing the partisan effects of redistricting, American Political Science Review, vol. 79, no. 2, pp. 320-333.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B2">
    <label>2.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Campagna J., Grofman B. (1990), Party control and partisan bias in 1980s congressional redistricting, The Journal of Politics, vol. 52, no. 4, pp. 1242-1257.</mixed-citation>
     <mixed-citation xml:lang="en">Campagna J., Grofman B. (1990), Party control and partisan bias in 1980s congressional redistricting, The Journal of Politics, vol. 52, no. 4, pp. 1242-1257.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B3">
    <label>3.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Caughey D., Tausanovitch C., Warshaw C. (2017), Partisan gerrymandering and the political process: effects on roll-call voting and state policies, Election Law Journal: Rules, Politics, and Policy, vol. 16, no. 4, pp. 453-469.</mixed-citation>
     <mixed-citation xml:lang="en">Caughey D., Tausanovitch C., Warshaw C. (2017), Partisan gerrymandering and the political process: effects on roll-call voting and state policies, Election Law Journal: Rules, Politics, and Policy, vol. 16, no. 4, pp. 453-469.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B4">
    <label>4.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Chatterjee T. et al. (2020), On theoretical and empirical algorithmic analysis of the efficiency gap measure in partisan gerrymandering, Journal of Combinatorial Optimization, vol. 40, no. 2, pp. 512-546.</mixed-citation>
     <mixed-citation xml:lang="en">Chatterjee T. et al. (2020), On theoretical and empirical algorithmic analysis of the efficiency gap measure in partisan gerrymandering, Journal of Combinatorial Optimization, vol. 40, no. 2, pp. 512-546.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B5">
    <label>5.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Cohen-Zemach A., Lewenberg Y., Rosenschein J.S. (2018), Gerrymandering over graphs, Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, Stockholm, pp. 274-282.</mixed-citation>
     <mixed-citation xml:lang="en">Cohen-Zemach A., Lewenberg Y., Rosenschein J.S. (2018), Gerrymandering over graphs, Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, Stockholm, pp. 274-282.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B6">
    <label>6.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Fan C. et al. (2015), A spatiotemporal compactness pattern analysis of congressional districts to assess partisan gerrymandering: a case study with California and North Carolina, Annals of the Association of American Geographers, vol. 105, no. 4, pp. 736-753.</mixed-citation>
     <mixed-citation xml:lang="en">Fan C. et al. (2015), A spatiotemporal compactness pattern analysis of congressional districts to assess partisan gerrymandering: a case study with California and North Carolina, Annals of the Association of American Geographers, vol. 105, no. 4, pp. 736-753.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B7">
    <label>7.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Friedman J.N., Holden R.T. (2009), The rising incumbent reelection rate: what's gerrymandering got to do with it?, The Journal of Politics, vol. 71, no. 2, pp. 593-611.</mixed-citation>
     <mixed-citation xml:lang="en">Friedman J.N., Holden R.T. (2009), The rising incumbent reelection rate: what's gerrymandering got to do with it?, The Journal of Politics, vol. 71, no. 2, pp. 593-611.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B8">
    <label>8.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Glazer A., Grofman B., Robbins M. (1987), Partisan and incumbency effects of 1970s congressional redistricting, American Journal of Political Science, vol. 31, no. 3, pp. 680-707.</mixed-citation>
     <mixed-citation xml:lang="en">Glazer A., Grofman B., Robbins M. (1987), Partisan and incumbency effects of 1970s congressional redistricting, American Journal of Political Science, vol. 31, no. 3, pp. 680-707.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B9">
    <label>9.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Goedert N. (2014), Gerrymandering or geography? How Democrats won the popular vote but lost the Congress in 2012, Research &amp; Politics, vol. 1, no. 1, pp. 205-212.</mixed-citation>
     <mixed-citation xml:lang="en">Goedert N. (2014), Gerrymandering or geography? How Democrats won the popular vote but lost the Congress in 2012, Research &amp; Politics, vol. 1, no. 1, pp. 205-212.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B10">
    <label>10.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Lublin D. (1997), The paradox of representation: Racial gerrymandering and minority interests in Congress, Princeton, NJ: Princeton University Press, 176 p.</mixed-citation>
     <mixed-citation xml:lang="en">Lublin D. (1997), The paradox of representation: Racial gerrymandering and minority interests in Congress, Princeton, NJ: Princeton University Press, 176 p.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B11">
    <label>11.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Lusher D., Koskinen J., Robins G. (eds.) (2013), Exponential random graph models for social networks: Theory, methods, and applications, Cambridge: Cambridge University Press, 331 p.</mixed-citation>
     <mixed-citation xml:lang="en">Lusher D., Koskinen J., Robins G. (eds.) (2013), Exponential random graph models for social networks: Theory, methods, and applications, Cambridge: Cambridge University Press, 331 p.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B12">
    <label>12.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">McCarty N., Poole K.T., Rosenthal H. (2009), Does gerrymandering cause polarization?, American Journal of Political Science, vol. 53, no. 3, pp. 666-680.</mixed-citation>
     <mixed-citation xml:lang="en">McCarty N., Poole K.T., Rosenthal H. (2009), Does gerrymandering cause polarization?, American Journal of Political Science, vol. 53, no. 3, pp. 666-680.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B13">
    <label>13.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">McGhee E. (2020), Partisan gerrymandering and political science, Annual Review of Political Science, vol. 23, no. 1, pp. 171-185.</mixed-citation>
     <mixed-citation xml:lang="en">McGhee E. (2020), Partisan gerrymandering and political science, Annual Review of Political Science, vol. 23, no. 1, pp. 171-185.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B14">
    <label>14.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Morrill R. (2018), Electoral geography and gerrymandering: Space and politics, Reordering the World: Geopolitical perspectives on the 21st century, eds. Demko G.J., Wood W.R. NY: Routledge, pp. 117-138.</mixed-citation>
     <mixed-citation xml:lang="en">Morrill R. (2018), Electoral geography and gerrymandering: Space and politics, Reordering the World: Geopolitical perspectives on the 21st century, eds. Demko G.J., Wood W.R. NY: Routledge, pp. 117-138.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B15">
    <label>15.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Noragon J.L. (1973), Redistricting, political outcomes, and gerrymandering in the 1960s, Annals of the New York Academy of Sciences, vol. 219, no. 1, pp. 314-333.</mixed-citation>
     <mixed-citation xml:lang="en">Noragon J.L. (1973), Redistricting, political outcomes, and gerrymandering in the 1960s, Annals of the New York Academy of Sciences, vol. 219, no. 1, pp. 314-333.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B16">
    <label>16.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Polsby D.D., Popper R.D. (1993), Ugly: An inquiry into the problem of racial gerrymandering under the Voting Rights Act, Michigan Law Review, vol. 92, no. 3, pp. 652-682.</mixed-citation>
     <mixed-citation xml:lang="en">Polsby D.D., Popper R.D. (1993), Ugly: An inquiry into the problem of racial gerrymandering under the Voting Rights Act, Michigan Law Review, vol. 92, no. 3, pp. 652-682.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B17">
    <label>17.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Stephanopoulos N.O. (2017), The causes and consequences of gerrymandering, William &amp; Mary Law Review, vol. 59, pp. 2115-2158.</mixed-citation>
     <mixed-citation xml:lang="en">Stephanopoulos N.O. (2017), The causes and consequences of gerrymandering, William &amp; Mary Law Review, vol. 59, pp. 2115-2158.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B18">
    <label>18.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Stephanopoulos N.O., McGhee E.M. (2015), Partisan gerrymandering and the efficiency gap, University of Chicago Law Review, no. 82, pp. 831-900.</mixed-citation>
     <mixed-citation xml:lang="en">Stephanopoulos N.O., McGhee E.M. (2015), Partisan gerrymandering and the efficiency gap, University of Chicago Law Review, no. 82, pp. 831-900.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B19">
    <label>19.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Waymer D., Heath R.L. (2016), Black voter dilution, American exceptionalism, and racial gerrymandering: The paradox of the positive in political public relations, Journal of Black Studies, vol. 47, no. 7, pp. 635-658.</mixed-citation>
     <mixed-citation xml:lang="en">Waymer D., Heath R.L. (2016), Black voter dilution, American exceptionalism, and racial gerrymandering: The paradox of the positive in political public relations, Journal of Black Studies, vol. 47, no. 7, pp. 635-658.</mixed-citation>
    </citation-alternatives>
   </ref>
   <ref id="B20">
    <label>20.</label>
    <citation-alternatives>
     <mixed-citation xml:lang="ru">Xu C. et al. (2023), Hybrid tree visualizations for analysis of gerrymandering, International Symposium on Visual Computing, Cham: Springer Nature Switzerland, pp. 85-96.</mixed-citation>
     <mixed-citation xml:lang="en">Xu C. et al. (2023), Hybrid tree visualizations for analysis of gerrymandering, International Symposium on Visual Computing, Cham: Springer Nature Switzerland, pp. 85-96.</mixed-citation>
    </citation-alternatives>
   </ref>
  </ref-list>
 </back>
</article>
