Intimate partner violence: An examination of ecological factors
Item
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Title
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Intimate partner violence: An examination of ecological factors
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Identifier
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d_2009_2013:07b45d052d3f:10284
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identifier
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10272
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Creator
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Ranjan, Sheetal,
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Contributor
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Maureen O'Connor
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Date
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2009
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Language
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English
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Publisher
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City University of New York.
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Subject
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Criminology | Individual & family studies | Ecological Factors | Geographic Information Systems | Intimate partner violence | Neighborhood factors
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Abstract
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Intimate Partner Violence has commonly been examined using an individual-psychological or a socio-structural perspective. Little research has examined IPV using an integrated approach. Specifically, little research has focused on understanding IPV in the context of neighborhood or ecology. In ecological studies the units of analysis are spatially defined population aggregates (Anselin, Cohen, Cook, Gor and Tita 2000). The Steering Committee for the Workshop on Issues in Research on Violence against Women, National Research Council clearly identifies the need for ecological research in relation to IPV: "The committee recommends research to estimate the extent of variation in violence against women among census tracts or small neighborhoods, police precincts or districts, or other theoretically meaningful social area aggregations. Research should also be aimed at determining which features of area composition influence rates and types of violence against women." (Kruttschnitt, McLaughlin and Petrie, 2004, p5). The present study, therefore, uses both individual level and community level data to understand the features of area composition that influence IPV. A combination of primary data from survey participants and secondary data from the Census, Infoshare, New York Police Department (NYPD) and the Domestic Violence Research Unit of the NYS Division of Criminal Justice Services were modeled using Hierarchal Linear Models (HLM) software. The data were also geo-coded on electronic maps using Geographic Information Systems (GIS) software. Multi-level binomial regression results indicate no neighborhood effects for the survey sample, whereas Moran's I tests using Geoda software indicate significant spatial clustering of IPV rates in police precincts. Further, regression analysis shows that concentrated disadvantage (beta=.55), immigrant concentration (beta=-.22) and community violence (beta=.31) significantly predict IPV rate in police precincts accounting for about 71 percent of variance in the model.
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Type
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dissertation
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Source
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2009_2013.csv
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degree
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Ph.D.
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Program
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Criminal Justice
