Selected studies show that community policing practices help deter crime, meaning that an inverse relationship exists between the two of them. This project does an in-depth analysis of this relationship using a variety of control variables, all of which have been shown to be predictive of crime. Crime is measured as the total crime rate (violent crimes + property crimes per 100,000 population). The data are city level, and my key control variables include city size, economic inequality, race, educational level, and strength of gun laws. There are eight variables that define community policing practices; they correlate strongly in a composite index has been developed from them. I examine how well this index can predict the total crime rate, taking into consideration the key control variables. In addition to the control variables, this project is distinguished by the high quality of the data sets used – including the 2013 Law Enforcement Management Administrative Statistics (LEMAS) study conducted in 2013 by the Bureau of Justice Statistics. Key findings include that the proposed hypothesis that community policing practices has an inverse relationship with crime rates was proven to be untrue by the data analysis. The relationship is actually a positive relationship; meaning that community policing practices rises as crime rates do. Another key finding was that the hypotheses for the social demographic variables were all proven by the data analysis. One particularly important finding was that gun regulation holds an inverse relationship with crime, as hypothesized, so the stronger the gun regulation the less crime a city would experience.
Recommended CitationRichardson, Keighan, "The Effects of Community Policing Practices and Related Social Demographic Variables on City Crime Rates" (2018). Honors Projects in History and Social Sciences. Paper 34.