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Spatial patterns of urban sex trafficking
This study examines the extent of spatial concentration of sex trafficking within an urban setting. The influence of situational and socio-demographic neighborhood variables on such patterns is then investigated within the framework of crime opportunity and social disorganization theories. Kernel de...
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Published in: | Journal of criminal justice 2018-09, Vol.58, p.87-96 |
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creator | Mletzko, Deborah Summers, Lucia Arnio, Ashley N. |
description | This study examines the extent of spatial concentration of sex trafficking within an urban setting. The influence of situational and socio-demographic neighborhood variables on such patterns is then investigated within the framework of crime opportunity and social disorganization theories.
Kernel density estimation and spatial clustering tests are used to analyze the distribution of sex trafficking offenses recorded between 2013 and 2015 in Austin, Texas. Negative binomial regression models are then estimated to examine the influence of situational and neighborhood variables on sex trafficking, using the census block group as the unit of analysis.
The analyses reveal a significant geographic clustering of sex trafficking offenses that is positively associated with proximity to the interstate highway, the number of cheaper hotels/motels and sexually oriented businesses, and concentrated disadvantage. Other variables (distance from the local truck stop, residential instability, and racial/ethnic heterogeneity) were not significantly associated with sex trafficking.
These findings are largely consistent with criminological theories that emphasize the physical and social environment in facilitating crime. An understanding of the situational and neighborhood factors driving these spatial concentrations can inform intervention efforts by law enforcement and other agencies aimed at disrupting the underlying support structure of sex trafficking.
•Sex trafficking is spatially concentrated within the urban environment.•Opportunity and social disorganization theories explain sex trafficking clusters.•Sex trafficking is predicted by proximity to the interstate highway and motels.•Concentrated disadvantage also predicts where sex trafficking occurs.•The spatial patterns observed can guide prevention and disruption efforts. |
doi_str_mv | 10.1016/j.jcrimjus.2018.07.008 |
format | article |
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Kernel density estimation and spatial clustering tests are used to analyze the distribution of sex trafficking offenses recorded between 2013 and 2015 in Austin, Texas. Negative binomial regression models are then estimated to examine the influence of situational and neighborhood variables on sex trafficking, using the census block group as the unit of analysis.
The analyses reveal a significant geographic clustering of sex trafficking offenses that is positively associated with proximity to the interstate highway, the number of cheaper hotels/motels and sexually oriented businesses, and concentrated disadvantage. Other variables (distance from the local truck stop, residential instability, and racial/ethnic heterogeneity) were not significantly associated with sex trafficking.
These findings are largely consistent with criminological theories that emphasize the physical and social environment in facilitating crime. An understanding of the situational and neighborhood factors driving these spatial concentrations can inform intervention efforts by law enforcement and other agencies aimed at disrupting the underlying support structure of sex trafficking.
•Sex trafficking is spatially concentrated within the urban environment.•Opportunity and social disorganization theories explain sex trafficking clusters.•Sex trafficking is predicted by proximity to the interstate highway and motels.•Concentrated disadvantage also predicts where sex trafficking occurs.•The spatial patterns observed can guide prevention and disruption efforts.</description><identifier>ISSN: 0047-2352</identifier><identifier>EISSN: 1873-6203</identifier><identifier>DOI: 10.1016/j.jcrimjus.2018.07.008</identifier><language>eng</language><publisher>New York: Elsevier Ltd</publisher><subject>Built environment ; Censuses ; Chaos theory ; Clustering ; Companies ; Crime ; Criminology ; Density ; Ethnicity ; Hotels & motels ; Human trafficking ; Law enforcement ; Neighborhoods ; Offenses ; Opportunity theory ; Proximity ; Sex trafficking ; Social disorganization ; Social environment ; Sociodemographics ; Spatial analysis ; Spatial patterns ; Trafficking ; Urban areas ; Variables</subject><ispartof>Journal of criminal justice, 2018-09, Vol.58, p.87-96</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Pergamon Press Inc. Sep/Oct 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c340t-8f97219192e93e6f0dae74f05459a2de325b0948ea370f7d17f2ebcc745320a33</citedby><cites>FETCH-LOGICAL-c340t-8f97219192e93e6f0dae74f05459a2de325b0948ea370f7d17f2ebcc745320a33</cites><orcidid>0000-0001-8674-5369</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925,30999,33774</link.rule.ids></links><search><creatorcontrib>Mletzko, Deborah</creatorcontrib><creatorcontrib>Summers, Lucia</creatorcontrib><creatorcontrib>Arnio, Ashley N.</creatorcontrib><title>Spatial patterns of urban sex trafficking</title><title>Journal of criminal justice</title><description>This study examines the extent of spatial concentration of sex trafficking within an urban setting. The influence of situational and socio-demographic neighborhood variables on such patterns is then investigated within the framework of crime opportunity and social disorganization theories.
Kernel density estimation and spatial clustering tests are used to analyze the distribution of sex trafficking offenses recorded between 2013 and 2015 in Austin, Texas. Negative binomial regression models are then estimated to examine the influence of situational and neighborhood variables on sex trafficking, using the census block group as the unit of analysis.
The analyses reveal a significant geographic clustering of sex trafficking offenses that is positively associated with proximity to the interstate highway, the number of cheaper hotels/motels and sexually oriented businesses, and concentrated disadvantage. Other variables (distance from the local truck stop, residential instability, and racial/ethnic heterogeneity) were not significantly associated with sex trafficking.
These findings are largely consistent with criminological theories that emphasize the physical and social environment in facilitating crime. An understanding of the situational and neighborhood factors driving these spatial concentrations can inform intervention efforts by law enforcement and other agencies aimed at disrupting the underlying support structure of sex trafficking.
•Sex trafficking is spatially concentrated within the urban environment.•Opportunity and social disorganization theories explain sex trafficking clusters.•Sex trafficking is predicted by proximity to the interstate highway and motels.•Concentrated disadvantage also predicts where sex trafficking occurs.•The spatial patterns observed can guide prevention and disruption efforts.</description><subject>Built environment</subject><subject>Censuses</subject><subject>Chaos theory</subject><subject>Clustering</subject><subject>Companies</subject><subject>Crime</subject><subject>Criminology</subject><subject>Density</subject><subject>Ethnicity</subject><subject>Hotels & motels</subject><subject>Human trafficking</subject><subject>Law enforcement</subject><subject>Neighborhoods</subject><subject>Offenses</subject><subject>Opportunity theory</subject><subject>Proximity</subject><subject>Sex trafficking</subject><subject>Social disorganization</subject><subject>Social environment</subject><subject>Sociodemographics</subject><subject>Spatial analysis</subject><subject>Spatial patterns</subject><subject>Trafficking</subject><subject>Urban areas</subject><subject>Variables</subject><issn>0047-2352</issn><issn>1873-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>7QJ</sourceid><sourceid>BHHNA</sourceid><recordid>eNqFkDtPwzAUhS0EEqXwF1AkJoaE60dykw1UUUCqxADMlutcI4eSFDtB8O9xVZiZznIeOh9j5xwKDry66orOBv_eTbEQwOsCsACoD9iM1yjzSoA8ZDMAhbmQpThmJzF2ABwBccYun7Zm9GaTJRkp9DEbXDaFtemzSF_ZGIxz3r75_vWUHTmziXT2q3P2srx9Xtznq8e7h8XNKrdSwZjXrkHBG94IaiRVDlpDqByUqmyMaEmKcg2NqslIBIctRydobS2qUgowUs7Zxb53G4aPieKou2EKfZrUgguZTimsk6vau2wYYgzk9DYxMOFbc9A7LLrTf1j0DosG1AlLCl7vg5Q-fHoKOlpPvaXWB7Kjbgf_X8UPfp9tlQ</recordid><startdate>201809</startdate><enddate>201809</enddate><creator>Mletzko, Deborah</creator><creator>Summers, Lucia</creator><creator>Arnio, Ashley N.</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QJ</scope><scope>7U4</scope><scope>BHHNA</scope><scope>DWI</scope><scope>K7.</scope><scope>WZK</scope><orcidid>https://orcid.org/0000-0001-8674-5369</orcidid></search><sort><creationdate>201809</creationdate><title>Spatial patterns of urban sex trafficking</title><author>Mletzko, Deborah ; Summers, Lucia ; Arnio, Ashley N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c340t-8f97219192e93e6f0dae74f05459a2de325b0948ea370f7d17f2ebcc745320a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Built environment</topic><topic>Censuses</topic><topic>Chaos theory</topic><topic>Clustering</topic><topic>Companies</topic><topic>Crime</topic><topic>Criminology</topic><topic>Density</topic><topic>Ethnicity</topic><topic>Hotels & motels</topic><topic>Human trafficking</topic><topic>Law enforcement</topic><topic>Neighborhoods</topic><topic>Offenses</topic><topic>Opportunity theory</topic><topic>Proximity</topic><topic>Sex trafficking</topic><topic>Social disorganization</topic><topic>Social environment</topic><topic>Sociodemographics</topic><topic>Spatial analysis</topic><topic>Spatial patterns</topic><topic>Trafficking</topic><topic>Urban areas</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mletzko, Deborah</creatorcontrib><creatorcontrib>Summers, Lucia</creatorcontrib><creatorcontrib>Arnio, Ashley N.</creatorcontrib><collection>CrossRef</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>Sociological Abstracts</collection><collection>Sociological Abstracts</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>Journal of criminal justice</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mletzko, Deborah</au><au>Summers, Lucia</au><au>Arnio, Ashley N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial patterns of urban sex trafficking</atitle><jtitle>Journal of criminal justice</jtitle><date>2018-09</date><risdate>2018</risdate><volume>58</volume><spage>87</spage><epage>96</epage><pages>87-96</pages><issn>0047-2352</issn><eissn>1873-6203</eissn><abstract>This study examines the extent of spatial concentration of sex trafficking within an urban setting. The influence of situational and socio-demographic neighborhood variables on such patterns is then investigated within the framework of crime opportunity and social disorganization theories.
Kernel density estimation and spatial clustering tests are used to analyze the distribution of sex trafficking offenses recorded between 2013 and 2015 in Austin, Texas. Negative binomial regression models are then estimated to examine the influence of situational and neighborhood variables on sex trafficking, using the census block group as the unit of analysis.
The analyses reveal a significant geographic clustering of sex trafficking offenses that is positively associated with proximity to the interstate highway, the number of cheaper hotels/motels and sexually oriented businesses, and concentrated disadvantage. Other variables (distance from the local truck stop, residential instability, and racial/ethnic heterogeneity) were not significantly associated with sex trafficking.
These findings are largely consistent with criminological theories that emphasize the physical and social environment in facilitating crime. An understanding of the situational and neighborhood factors driving these spatial concentrations can inform intervention efforts by law enforcement and other agencies aimed at disrupting the underlying support structure of sex trafficking.
•Sex trafficking is spatially concentrated within the urban environment.•Opportunity and social disorganization theories explain sex trafficking clusters.•Sex trafficking is predicted by proximity to the interstate highway and motels.•Concentrated disadvantage also predicts where sex trafficking occurs.•The spatial patterns observed can guide prevention and disruption efforts.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.jcrimjus.2018.07.008</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8674-5369</orcidid></addata></record> |
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source | Applied Social Sciences Index & Abstracts (ASSIA); Elsevier; Sociological Abstracts |
subjects | Built environment Censuses Chaos theory Clustering Companies Crime Criminology Density Ethnicity Hotels & motels Human trafficking Law enforcement Neighborhoods Offenses Opportunity theory Proximity Sex trafficking Social disorganization Social environment Sociodemographics Spatial analysis Spatial patterns Trafficking Urban areas Variables |
title | Spatial patterns of urban sex trafficking |
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