Uniform Crime Reporting (UCR) Program is the federal program that encourages law enforcement agencies to collect data about crimes in their jurisdictions and regularly report them to the FBI. Upon receiving these data, the FBI compiles a yearly Uniform Crime Report that reflects crime rates and trends throughout the U.S. The program was launched in 1929 because there was a need for credible unified statistics of criminal activity in the country (U. S. Department of Justice [DOJ], 1). Originally, the UCR program was designed to provide law enforcement with accurate data (DOJ, 1). However, over time, these reports have become a source of information about crime for everyone concerned.
The participation of law enforcement agencies in the UCR Program is voluntary. It is estimated that over “18,000 city, university and college, county, state, tribal, and federal law enforcement agencies” report the information about crimes either to responsible state bodies or directly to the FBI (DOJ, 1). Four data series constitute the UCR Program: “the National Incident-Based Reporting System (NIBRS), the Summary Reporting System (SRS), the Law Enforcement Officers Killed and Assaulted (LEOKA) Program, and the Hate Crime Statistics Program” (DOJ, 1). Each of these sets of crime data turns into a separate yearly report. Apart from that, the FBI issues several topical crime reports that are devoted, for example, to human trafficking or cargo theft.
There are several ways of how crime data for the UCR Program can be collected. There are primary and secondary data, and there are different ways of obtaining them (Kabir, 2). Strategies for gathering primary data include experiments, surveys, questionnaires, interviews, and observations (Kabir, 2). They are appropriate for law enforcement agencies who collect first-hand data to transfer them to the FBI.
For example, law enforcement officers often receive information about offenses via self-reporting, i.e., when a victim informs the police of the crime (DOJ, 3). Secondary data collecting strategies include the review of records, newspapers, data archives, etc. (Kabir, 2). For the present report, I chose the data-gathering strategy involving document review. The documents under review will be crime statistics collected by the police departments in the towns of concern.
The rationale for using this data-gathering method is that it spares the time and effort needed for collecting primary data. Generally, the advantage of using secondary data is that someone has already done the necessary background work (Kabir, 2). If the sources are reliable, there is no need to double-check the validity of the data (Kabir, 2). Police officers often directly communicate with complainants, examine crime scenes and evidence, and cross-check the details of a case to eliminate the probability of mistakes. For this reason, document review with the use of crime statistics collected by police departments is a reliable data-gathering strategy.
Next, crime trends in Happy Town, Frown Town, Smooth Town, and Cool Town will be explored. The statistics show that murder and nonnegligent manslaughter rates increased in Happy Town and Smooth Town from 2010 to 2015 (CRJ 105, 4). Frown Town and Cool Town saw an increase in rates of these crimes in 2012 and 2013, but, by 2015, murder rates had decreased (CRJ 105, 4). Forcible rape rates significantly increased in Happy Town over five years, from 2 in 2010 to 12 in 2015 (CRJ 105, 4).
In Cool Town and Frown Town, forcible rape rates were relatively low, totaling 1-2 per year (CRJ 105, 4). In Smooth Town, rates of forcible rape increased from 3 in 2011 to 5 in 2015 (CRJ 105, 4). In all four towns, there was an increase in robbery rates. The least growth was in Smooth Town that had the lowest robbery rates in 2010-2015 (CRJ 105, 4). The rise in Cool Town and Frown Town was identical, but since the total population of Frown Town was smaller, its forcible rape rates per 1000 people were greater.
Aggravated assault rates were changing differently from 2010 to 2015. In Cool Town and Frown Town, the number of these crimes was rising from 2010 to 2014 but decreased in 2015 (CRJ 105, 4). In Smooth Town, aggravated assault rates were initially higher than in the two previously mentioned towns, and varied from 75 to 80 over five years (CRJ 105, 4). In Happy Town, the increase was the most significant, from 72 in 2010 to 86 in 2015 (CRJ 105, 4).
Burglary rates increased in all four towns up to 18 in 2012, but by 2015, they had decreased in Cool Town and Frown Town and remained almost unchanged in Smooth Town and Happy Town (CRJ 105, 4). Larceny-theft was the most frequent Part I crime committed in these towns. In Cool Town and Frown town, its rate was the lowest and decreased over five years, while in Smooth Town, it varied from 161 to 167 (CRJ 105, 4). In Happy Town, the larceny-theft rate demonstrated the most significant growth over five years.
The final Part I crime to be reviewed is motor vehicle theft. In Cool Town, Smooth Town, and Frown Town, its rate was identical in all four towns in 2010-2013, with an increase in 2011 and a decrease in 2012-2013 (CRJ 105, 4). Despite the similar indexes, the crime rates per 1000 population were different. In Frown Town, the motor vehicle theft rate per 1000 people was the highest because the total population there is the smallest. In 2014, motor vehicle theft rates increased in Cool Town, Happy Town, and Frown Town, but decreased in Smooth Town (CRJ 105, 4). In 2015, Happy Town had the highest rates of this crime (CRJ 105, 4). Overall, Happy Town had the worst crime trends from 2010 to 2015 since all Part I crime rates increased.
Sources
U. S. Department of Justice, 2018, Uniform Crime Reporting (UCR) Program. Web.
Syed Muhammad Sajjad Kabir, 2016, Methods of Data Collection. Web.
U.S. Department of Justice, 2018, Criminal Justice Information Services Division: Uniform Crime Reporting Program. Web.
CRJ 105, Uniform Crime Report (UCR) Performance Task, this is my course assignment.