Exploring the Overlap, Saliency, and Consistency of Environmental Predictors in Crime Hot Spots: A Remote Systematic Social Observation and Case-Control Examination

<p>Despite the common finding that crime is highly concentrated in space, the specific locations, characteristics, and contexts of crime hot spots are not consistently the same or generalizable across unique units of analysis and crime types. This dissertation will simultaneously integrate different types of environmental criminology predictors, including crime generators and attractors and environmental disorder indicators, to best identify the situational predictors of hot spot street segments relative to empirical controls in Indianapolis for several different crime types. Hot spot and control units will be compared based on the presence of spatially joined crime generators and attractors and environmental disorder indicators recorded via remote systematic social observation using Google Street View. In addition to uncovering the strongest environmental predictors significantly more likely to predict hot spots, this dissertation will also determine the level of spatial overlap of hot spots across different crime types and statistically assess the consistency of the influence of environmental predictors across each of the separate crime types. The findings will provide new information regarding the locations and composition of different types of crime hot spots at highly localized spatial extents. Also, this dissertation stands to make several methodological contributions by using remote systematic social observation to measure disorder and an innovative case-control research design that empirically matches hot spot and control units within a predefined spatial parameter while holding several key covariates constant.</p>

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Criminal Justice

Grantor

The Graduate School and University Center of The City University of New York

Year dc:date.available

2021

Author dc:creator

• Connealy, Nathan T.

Advisor dc:contributor.advisor

• Eric L. Piza

Committee members dc:contributor.committeemember

• Kevin T. Wolff
• Brian Lawton
• Joel Miller

• Google Street View
• Environmental Criminology
• Generators
• Attractors
• Disorder
• Decay

Repository record dc:identifier

https://academicworks.cuny.edu/gc_etds/4315

OAI identifier oai:identifier

oai:academicworks.cuny.edu:gc_etds-5373