<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2395-8669</journal-id>
<journal-title><![CDATA[Nóesis. Revista de ciencias sociales]]></journal-title>
<abbrev-journal-title><![CDATA[Nóesis, Rev. cienc. soc.]]></abbrev-journal-title>
<issn>2395-8669</issn>
<publisher>
<publisher-name><![CDATA[Universidad Autónoma de Ciudad Juárez, Instituto de Ciencias Sociales y Administración]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2395-86692025000200002</article-id>
<article-id pub-id-type="doi">10.20983/noesis.2025.2.2</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Autocorrelación espacial y distribución del voto en Ciudad Juárez: un análisis comparativo (2018 &#8211; 2024)]]></article-title>
<article-title xml:lang="en"><![CDATA[Spatial Autocorrelation and Vote Distribution in Ciudad Juárez: A Comparative Analysis (2018&#8211;2024)]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández Hernández]]></surname>
<given-names><![CDATA[Vladimir]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Haro De León]]></surname>
<given-names><![CDATA[Liliana de]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de Ciudad Juárez  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma de Ciudad Juárez  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<volume>34</volume>
<numero>68</numero>
<fpage>25</fpage>
<lpage>45</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2395-86692025000200002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2395-86692025000200002&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2395-86692025000200002&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Examinar las elecciones requiere comprender no solo el sistema político, sino también su expresión en el espacio geográfico. En este contexto, el objetivo del trabajo es analizar cómo la concentración del voto y su interdependencia geográfica configuraron los resultados de las elecciones presidenciales de 2018 y 2024 en Ciudad Juárez, México. Se utilizaron datos a nivel de sección electoral recopilados del Instituto Nacional Electoral. Mediante las técnicas de autocorrelación espacial local se estimaron agrupamientos con significancia estadística. En el análisis de los datos se muestra una marcada polarización geográfica. Andres Manuel López Obrador obtuvo en promedio 53 por ciento del total de votos en cada una se las secciones electorales; mientras que, en los resultados del 2024, Claudia Sheinbaum obtuvo 72 por ciento, ambos con apoyos en las zonas norponiente y suroriente; en contraste, los candidatos de oposición con preferencias en la zona nororiente. La evidencia empírica aporta argumentos de la relación entre las condiciones socioeconómicas y el voto. El efecto &#8220;vecindario&#8221; prueba el agrupamiento de secciones con características similares, confirmando el papel del &#8220;lugar&#8221; como una de las dimensiones explicativas de los patrones homogéneos de votación. Este trabajo contribuye tanto al campo de conocimiento de la geografía electoral y de los estudios urbanos. Aporta un marco analítico para futuras investigaciones que exploren la relación entre espacio y política.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Examining elections requires understanding not only the political system but also its manifestation in geographic space. In this context, the objective of this study is to analyze how vote concentration and its geographic interdependence shaped the outcomes of the 2018 and 2024 presidential elections in Ciudad Juárez, Mexico. Electoral precinct-level data collected from Mexico&#8217;s National Electoral Institute were utilized. Local spatial autocorrelation techniques were applied to identify statistically significant clusters. The data analysis reveals marked geographic polarization: Andrés Manuel López Obrador secured, on average, 53% of votes per electoral precinct in 2018, while Claudia Sheinbaum obtained 72% in 2024, both garnering stronger support in the northwestern and southeastern zones of the city. In contrast, opposition candidates concentrated their support in the northeastern zone. Empirical evidence supports the relationship between socioeconomic conditions and voting patterns. The neighborhood effect demonstrates the clustering of precincts with similar socioeconomic characteristics, confirming the role of &#8220;place&#8221; as an explanatory dimension for homogeneous voting patterns. This work contributes to the fields of electoral geography and urban studies, providing an analytical framework for future research exploring the interaction between space and politics.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Autocorrelación espacial]]></kwd>
<kwd lng="es"><![CDATA[Polarización socioespacial]]></kwd>
<kwd lng="es"><![CDATA[Geografía electoral]]></kwd>
<kwd lng="es"><![CDATA[Efecto vecindario]]></kwd>
<kwd lng="es"><![CDATA[Teoría urbana del voto]]></kwd>
<kwd lng="en"><![CDATA[Spatial Autocorrelation]]></kwd>
<kwd lng="en"><![CDATA[Socio-spatial Polarization]]></kwd>
<kwd lng="en"><![CDATA[Electoral Geography]]></kwd>
<kwd lng="en"><![CDATA[Neigh-borhood Effect]]></kwd>
<kwd lng="en"><![CDATA[Urban Voting Theory]]></kwd>
</kwd-group>
</article-meta>
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