The Uniform Crime Report: Definition and Description
The Uniform Crime Reporting Program (UCR) was established by the International Association for Chiefs of Police was in 1929, and UCR has formed the basis of accessing information on crimes and crime rates about any country ( Document Library ). The initial idea of establishing UCR was to help in ensuring access to reliable and accurate data on crime in the entire country. Consequently, the FBI was tasked with collection, publishing, and archiving of the publications containing such crime statistics; the FBI was put at the helm of these tasks in 1930 due to its credibility in conducting thorough research and providing accurate statistics. According to reports released by the FBI in 2009, more than 295 million of the inhabitants of the United States of America had received representation in a court of law by active law enforcement agencies(Document Library). This number translates to 96.3% of the total population, representing the high rate of representation in the country during that time. Notably, such crime statistics go beyond helping compute the crime rate, since they help government officials and law enforcers in making informed decisions in terms of resource allocation, budget planning, and evaluating the efficiency of utilization of police resources ( Document Library ). The information is also used by criminal justice officials in planning more effective community outreach programs, ensuring citizens become better informed on crime rates in their neighborhoods, and media coverage outlets utilize it in draw comparisons between different cities in terms of crime rates and security status.
The UCR is composed of three categories of crimes: Part I and Part II. Part I crimes are the index crimes, and statistics from this category is used for calculating the crime rate. Part II is composed of non-index crimes, and these are not involved in the computation of crime rates ( Document Library ). The information only contains arrest data for a particular region within a given period. Initially, crimes categorized as index crimes under Part I included aggravated murder, robbery, forcible rape, murder and manslaughter, theft of motor vehicles, larceny-theft, and burglary. Arson was added to Part I crimes in October 1978 following a law passed by Congress. However, the FBI advisory board decided in 2004 that index crimes needed to be broken down into two different categories instead of one class since the inclusion of larceny-theft was thought to have skewed the crime index ( Document Library ). The new categories under Part I included forcible rape, robbery and property burglary, aggravated assault, murder, motor vehicle theft, non-negligent manslaughter, arson, and larceny-theft. Offenses under Part I include DUI, disorderly conduct, embezzlement, forgery, fraud, and drug abuse, and any crime related to all these.
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The role of the UCR is establishing the crime rate of a region in 100,000 people to allow equal judgment of a city regardless of its population size. However, its main challenge is no weight given to different crimes. For instance, murder and motor vehicle theft are treated equally. Further, the accuracy of UCR statistics is influenced by such factors as economic conditions, cultural factors, conventional means of transport, clime, population stability, level of urbanization, and divorce rates. It is also notable that the Hierarchy Rule applies to the UCR; it states that only the highest crime or offense gets reported ( Document Library ). For instance, if an offender breaks into a house, steals, rapes the house occupant, and murders them, then it is likely that only murder will be reported. Such factors also adversely affect the accuracy of statistics from UCR.
Data-gathering strategy and Rationale for this Report
There were various strategies available for use when retrieving data on the crime rates of the surrounding cities to compare them. Eventually, documentation review was selected for this exercise as it can help in accounting for the statistics provided by the Uniform Crime Reporting Programs on both parts I and II ( Document Library ). The information provided assisted in conducting an in-depth analysis of annual crime rate reports for each of the cities. Further, newspapers tend to misjudge rates since they do not directly relate them to the severity of the crime or population size. Such observations help in analyzing the rise and fall of the population in every nation and build the idea that people tend to move to areas they consider to be safer. However, more in-depth exploratory research would be required to understand crime statistics, such as why there is a fluctuation in the rates. Therefore, documentation analysis is further justified as it helped in getting more in-depth analysis and interpretation of the crime statistics.
The use of reported statistics for crimes was also selected because it is the most appropriate approach to getting a rational answer on the crime rates affecting the cities without necessarily incorporating other research and data collection and analysis methods ( Document Library ). The fact that the population is huge and that crime statistics have to be tracked and compared for the cities mean that documentation analysis is more effective than other methods as life histories, focus groups, case studies, and participant studies. Therefore, using well-documented statistics is the only approach to ensure sufficient identification of crime trends in the cities. Besides, crime rates and police reports are more accurate and reliable compared to questionnaires and interviews, which could otherwise lead to distorted information. The method used in this case enhanced the overall reliability and validity of data collection and analysis.
Crime Trends in Happy Town, Frown Town, Smooth Town, and Cool Town over the Last 5 Years
The crime statistics from the UCR show that the city and the surrounding ones have registered a rise and fall in crime rates over the last five years. Cool Town has the lowest crime rate, making it the safest town despite having the highest population. The stats show an all-time low for the last five years. Despite zero reports of murders for two consecutive years, cases of robbery have increased significantly, by 225%, between 2010 and 2015, and this sounds alarm of growing insecurity. In the last five years, Smooth Town has registered a population increase of more than 30,000 people. The violent crime rate has also increased slightly, but it has registered the lowest since 2015. However, Tamara Justice falsely reported that Smooth Town is the community with the lowest property crime rate and that the town had a crime rate 97% lower compared to Georgia. Despite the town’s crime rate being low at 189.9% in 2015, it had a higher property crime rate than Cool Town and Frown Town. However, its violent crime rate was lower than that of Happy Town. The statistics also show that overall crime in Frown Town dropped by 17% from 2014, registering a low violent crime rate, despite the population remaining relatively the same at 3000 people over the last five years.
On the other hand, Happy Town has registered a significant rise in the crime rate. The overall crime rate is 85%, and seven more murders have been recorded since 2010. Population has increased by about 43,000 people. In this regard, the statement that Tamara Fearless of the Tribune made on March 5th, 2016, was incorrect. She stated that major crimes had increased by only 5% and attributed the same to increased theft cases. Although theft cases have doubled over the last five years, cases of robbery, rape, non-negligent manslaughter, and murder have also multiplied, and this adds to the increased significant crime rates in the town. The crime rate in the city in much higher compared to Cool Town. However, the issue could be addressed through community outreach and effective policing efforts. Such measures can help in lowering the crime rate and making the area a safer place for the inhabitants.
References
Document Library. Retrieved from https://blackboard.strayer.edu/bbcswebdav/institution/CRJ/105/1198/CRJ105_ASSIGNMENT2.pdf#%5B%7B%22num%22%3A18%2C%22gen%22%3A0%7D%2C%7B%22name%22%3A%22XYZ%22%7D%2C69%2C720%2C0%5D
