Researcher Information

Abstract

The purpose of this project is to apply environmental criminology theories to spatially examine the distribution of 2013 Part 1 Uniform Crime Report (UCR) offenses and Crime Clearance Rates (CCRs) by Florida judicial circuits (n=20). The goal is to identify judicial circuits with the highest and lowest CCRs; and present a spatial analysis that visually represents statistically significant judicial circuits for the criminal offenses of murder, forcible rape, robbery, aggravated assault, burglary, larceny, and motor vehicle thefts. Additionally, the current study identifies and analyzes cities (n=30) within the 11 th judicial circuit (Miami-Dade county) because it had the lowest CCR; and compares Part I UCR offense data, CCRs, and entry-level officer salary for possible correlations. ArcGIS mapping software is used to perform hotspot, cluster and outlier, and grouping analyses. Findings suggest that judicial circuits with more property crimes have lower CCRs – and no correlation between officer salary and CCRs.

Faculty Sponsors

Kendra Gentry, M.S.

Project Type

Event

Location

Alvin Sherman Library

Start Date

4-10-2015 1:00 PM

End Date

4-10-2015 5:30 PM

Share

COinS
 
Apr 10th, 1:00 PM Apr 10th, 5:30 PM

Spatial Analysis of Uniform Crime Reports, Crime Clearance Rates, and Office Entry-Level Salaries

Alvin Sherman Library

The purpose of this project is to apply environmental criminology theories to spatially examine the distribution of 2013 Part 1 Uniform Crime Report (UCR) offenses and Crime Clearance Rates (CCRs) by Florida judicial circuits (n=20). The goal is to identify judicial circuits with the highest and lowest CCRs; and present a spatial analysis that visually represents statistically significant judicial circuits for the criminal offenses of murder, forcible rape, robbery, aggravated assault, burglary, larceny, and motor vehicle thefts. Additionally, the current study identifies and analyzes cities (n=30) within the 11 th judicial circuit (Miami-Dade county) because it had the lowest CCR; and compares Part I UCR offense data, CCRs, and entry-level officer salary for possible correlations. ArcGIS mapping software is used to perform hotspot, cluster and outlier, and grouping analyses. Findings suggest that judicial circuits with more property crimes have lower CCRs – and no correlation between officer salary and CCRs.