Crime in an Affluent City: Spatial Patterns of Property Crime in Coral Gables, Florida
This study investigates the spatial and temporal patterns of property crime at the census block level in the mid-sized, medium- to high-income city of Coral Gables, Florida, USA, between 2004 and 2016. Specifically, we analyzed residential and vehicular burglary. We used Emerging Hot Spot Analysis (...
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| Format: | Electronic Article |
| Language: | English |
| Published: |
2020
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| In: |
European journal on criminal policy and research
Year: 2020, Volume: 26, Issue: 4, Pages: 547-570 |
| Online Access: |
Volltext (Resolving-System) |
| Journals Online & Print: | Drawer...
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| Check availability: | HBZ Gateway |
| Keywords: |
MARC
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| 520 | |a This study investigates the spatial and temporal patterns of property crime at the census block level in the mid-sized, medium- to high-income city of Coral Gables, Florida, USA, between 2004 and 2016. Specifically, we analyzed residential and vehicular burglary. We used Emerging Hot Spot Analysis (EHSA) to locate and identify crime hot and cold spots over time. In order to understand the role that various sociodemographic variables play in predicting crime patterns, geographically weighted regression (GWR) was used to analyze the spatial clustering of crime, and commercial areas, renter percentage, median household income, and multifamily households. Our results revealed consistent hotspots for residential and vehicle burglary within the northeast area of the city, while vehicle burglary had hotspots along U.S. Route 1 (US-1)—a main road in Coral Gables—and around the University of Miami, with emerging hotspots within the northwest part of the city bordering lower-income areas. Hotspots were associated with structural factors within and around the city including more multifamily homes, higher poverty rates, more renters, and greater economic disadvantage in surrounding municipalities. Social disorganization and routine activity perspectives are supported as frameworks to understand crime patterns in this context. The findings suggest that policymakers should target specific locations using geospatial analyses to better address property crime. | ||
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