Improving policing through better analysis: an empirical assessment of a crime analysis training and enhancement project within an urban police department

2020 ◽  
pp. 1-18
Author(s):  
Rob T. Guerette ◽  
Kimberly Przeszlowski ◽  
Joelle Lee-Silcox ◽  
Kristen M. Zgoba
Keyword(s):  
Police Department ◽  
Crime Analysis ◽  
Empirical Assessment ◽  
Urban Police

From Beats to Tracts

2010 ◽  
Vol 1 (2) ◽  
pp. 92-106
Author(s):  
Gang Gong
Keyword(s):  
Remote Sensing ◽  
Police Department ◽  
Crime Analysis ◽  
Crime Statistics ◽  
Houston Police Department ◽  
Interpolation Technique ◽  
Different Types ◽  
Socioeconomic Data ◽  
Geographical Space ◽  
The U.S

In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.

170 Impact of an Urban, Police Department-Initiated Jail Diversion of Inebriates to a Sobering Center

2016 ◽  
Vol 68 (4) ◽  
pp. S66-S67 ◽  
Author(s):  
A.F. Weltge ◽  
L. Kincaid ◽  
A. Ochoa ◽  
D.S. Buck ◽  
D. Persse ◽  
...  
Keyword(s):  
Police Department ◽  
Jail Diversion ◽  
Urban Police

Officer force versus suspect resistance: A gendered analysis of patrol officers in an urban police department

2007 ◽  
Vol 35 (2) ◽  
pp. 183-192 ◽  
Author(s):  
Thomas D. Bazley ◽  
Kim Michelle Lersch ◽  
Thomas Mieczkowski
Keyword(s):  
Police Department ◽  
Patrol Officers ◽  
Urban Police

Crisis Intervention Team Training and Special Weapons and Tactics Callouts in an Urban Police Department

2009 ◽  
Vol 60 (6) ◽  
pp. 831-833 ◽  
Author(s):  
Michael T. Compton ◽  
Berivan Demir ◽  
Janet R. Oliva ◽  
Trudy Boyce
Keyword(s):  
Crisis Intervention ◽  
Police Department ◽  
Team Training ◽  
Crisis Intervention Team ◽  
Intervention Team ◽  
Urban Police

From Beats to Tracts

2012 ◽  
pp. 273-288
Author(s):  
Gang Gong
Keyword(s):  
Remote Sensing ◽  
Census Tract ◽  
Police Department ◽  
Crime Analysis ◽  
Crime Statistics ◽  
Enumeration District ◽  
Houston Police Department ◽  
Socioeconomic Data ◽  
Geographical Space ◽  
The U.S

In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.

Police Response to Domestic Violence: The Influence of Extralegal Factors on Arrest Decisions

Partner Abuse ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 215-229 ◽  
Author(s):  
Marie Mele
Keyword(s):  
Domestic Violence ◽  
New Jersey ◽  
Police Department ◽  
The State ◽  
Police Response ◽  
Initial Analysis ◽  
Growing Body ◽  
Extralegal Factors ◽  
Victim Gender ◽  
Urban Police

AbstractThis study examines extralegal factors that predict arrest in domestic violence cases from one urban police department in the state of New Jersey. Initial analysis revealed that 40% of reported cases (N = 5,728) resulted in the suspect’s arrest. Bivariate analyses identified several predictors of arrest, including victim gender, victim/suspect relationship, cohabitation, and victim unemployment. At the multivariate level, cohabitation and victim unemployment were the strongest predictors of arrest. These findings are discussed in the context of a growing body of literature that examines the influence of extralegal factors on arrest decisions in domestic violence cases.

Sign in / Sign up

Export Citation Format

Share Document