Social disorganization theory proposes that neighborhood characteristics, such as residential instability, racial and ethnic heterogeneity, concentrated disadvantage, and immigrant concentration contribute to an increase in crime rates. Informal social controls act as a mediator between these neighborhood characteristics and crime and delinquency. Informal social controls are regulated by members of a community and in a disorganized community these controls are not present, therefore, crime and delinquency flourish (Sampson, 2012). Researchers have focused on these measures of social disorganization and the ability to explain a variety of crimes, specifically public crimes. Recently, researchers have focused their attention to characteristics of socially disorganized areas and the ability to predict private crimes, such as domestic violence. This study contributes to the research on social disorganization theory and domestic violence by examining domestic offenses at three different units of analysis: Chicago census tracts, Chicago neighborhoods, and Illinois counties. Demographic variables from the 2005-2009 American Community Survey were utilized to measure social disorganization within Chicago census tracts, Chicago neighborhoods, and Illinois counties. Data on domestic offenses in Chicago were from the City of Chicago Data Portal and data on domestic offenses in Illinois counties were retrieved from the Illinois Criminal Justice Information Authority (ICJIA). This study incorporated geographic information systems (GIS) mapping to examine the relationships between locations of domestic offenses and the measures of social disorganization in each unit of analysis. Results of this study indicate that different measures of social disorganization are significantly associated with domestic offenses in each unit of analysis.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-3564 |
Date | 01 January 2013 |
Creators | Morgan, Rachel |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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