<?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>0188-4611</journal-id>
<journal-title><![CDATA[Investigaciones geográficas]]></journal-title>
<abbrev-journal-title><![CDATA[Invest. Geog]]></abbrev-journal-title>
<issn>0188-4611</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Geografía]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-46112016000100107</article-id>
<article-id pub-id-type="doi">10.14350/rig.48763</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[El robo de vehículos y su relación espacial con el contexto sociodemográfico en tres delegaciones centrales de la Ciudad de México (2010)]]></article-title>
<article-title xml:lang="en"><![CDATA[The motor vehicle theft and its spatial relationship with the socio-demographic context in three Central Delegations of Mexico City (2010)]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sánchez Salinas]]></surname>
<given-names><![CDATA[Omar Armando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fuentes Flores]]></surname>
<given-names><![CDATA[César Mario]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Secretaría de Seguridad Pública del Distrito Federal  ]]></institution>
<addr-line><![CDATA[ Distrito Federal]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,El Colegio de la Frontera Norte  ]]></institution>
<addr-line><![CDATA[Ciudad Juárez Chihuahua]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2016</year>
</pub-date>
<numero>89</numero>
<fpage>107</fpage>
<lpage>120</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-46112016000100107&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-46112016000100107&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-46112016000100107&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Este artículo tiene como objetivo analizar los patrones espaciales del delito de robo de vehículos en la Ciudad de México. Las grandes áreas metropolitanas de America Latina han atestiguado el incremento de la violencia urbana y la Zona Metropolitana de la Ciudad de México (ZMCM) no es la excepción. Uno de los delitos con el mayor número de averiguaciones previas en la ZMCM es el robo de vehículos con un promedio de 40 336 durante el periodo 1995-2007. En 2010 el robo de vehículos alcanzo las 44 446 averiguaciones previas, representando el 38% del total de las averiguaciones previas registradas en la entidad. Sin embargo, este delito no muestra una distribución homogénea en todo el territorio sino que muestra una alta concentración en algunas delegaciones de la Ciudad de México como Benito Juárez, Coyoacán y Cuauhtémoc. En este contexto nos preguntamos. Existe relación espacial entre la concentración de los robos de vehículos y las características socioeconómicas del entorno? El soporte teórico del artículo lo proporcionan teorías como la desorganización social y las actividades rutinarias. La información usada del robo de vehículos corresponde a las denuncias hechas por las personas afectadas y que se convirtieron en averiguaciones previas, la fuente de información es la Procuraduría General de Justicia del Distrito Federal (PGJDF, 2010). El resto de las variables socioeconómicas corresponden al XII Censo de Población y Vivienda (2010), ambas a nivel de área geoestadística básica (AGEB). La metodología es mixta, para medir la relación espacial se aplicaron algunas técnicas de análisis regional como el cociente de localización, un modelo de regresión lineal múltiple y análisis exploratorio de datos espaciales en específico el Índice de Moran. Los resultados identifican cuatro variables tales como el uso del suelo no residencial, la densidad de población, los hogares con jefatura femenina y concentración de población joven como factores que influyen en el robo de vehículos. Lo anterior permite diseñar políticas públicas de seguridad centradas en los lugares en los que se puedan poner en marcha programas orientados a la prevención situacional del delito, así como la prevención social del delito, orientados a la reconstrucción del tejido social y organización comunitaria.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This paper analyzes the spatial patterns of motor vehicle theft crimes in Mexico City. The largest metropolitan areas in Latin-America are witnessing a sharp escalation of urban violence and the Metropolitan Area of Mexico City is not the exception. In the Metropolitan Area of Mexico City the motor vehicle theft is one of the crimes that have higher arrest and criminal warrants with 40 336 in average during the 1995 to 2007 period. In 2010 motors vehicle theft reached 44 446 criminal warrants, representing the 39% of all criminal warrants in the city. However, such crime does not show a homogenous spatial pattern but shows a high spatial concentration in some delegations of Mexico City such as Benito Juárez, Coyoacán and Cuauhtémoc. In this context, the research question is: Does exists spatial relationship between concentration of motor vehicle theft and environmental factors?. The theoretical background is provided by the social disorganization theory, the routine activities and crime patterns. Both theories explain criminal spatial variation as responses to environmental conditions. The causal mechanism underlying both theories is that individuals make decisions based on the aggregated behavior around them. Individuals are constantly exposed to social stimuli, and they make use of the information derived from the environment (e.g. behavioral contagion).The data includes arrests and criminal warrants of motor vehicle theft provided by the General Office of Justice of the Federal District (PGJDF, 2010) and the rest of socioeconomic variables were provided by the Housing and Population Census , 2010, all of them at census tract level. The methodology used includes regional analysis techniques such as location quotient, multiple regression analysis and exploratory spatial data analysis ESDA in specific the Moran Indice. This is performed within reasonable limits of data reliability, sampling error, and in disconnection from theoretical postulates. The results of the multiple regression identify variables such as none residential land use, population density, female-headed households, single and concentration of young population influence motor vehicle theft crimes. These findings allow us to design public security polices focused in places where could implement programs oriented to the situational prevention of the crime and the social prevention of crime. Besides, the results provide findings for urban planning and social development policies with police strategies.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Robo de vehículos]]></kwd>
<kwd lng="es"><![CDATA[patrón espacial]]></kwd>
<kwd lng="es"><![CDATA[Distrito Federal]]></kwd>
<kwd lng="en"><![CDATA[Motor vehicle theft]]></kwd>
<kwd lng="en"><![CDATA[spatial pattern]]></kwd>
<kwd lng="en"><![CDATA[Federal District]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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