Introduction
The modern world has since had a significant advancement in technology, causing the need to embrace it in all sectors, including policing. Today, law enforcement agencies in the US heavily rely on technology than corrections and courts to inform them about criminal activities. Police departments rely on technological data to access real-time information about criminal activities. As a result, police officers can even predict the occurrence of a crime, thus ensuring mitigation and public safety. The US criminal justice system has embraced various data-driven policies such as intelligence-based policing, Compstat, and hot-spots policing. Such policies are significantly proactive and are based on information about past crimes. The essay aims to discuss the effectiveness and efficiency of hot-spots policing, including a case example of its application by the local police department.
Hos-Spots Policing
Hot-spots policing is a data-driven policy that was developed as a result of dissatisfaction by a section of scholars with the police tactics adopted during the reform era. The policy was informed by the criminological study and research showing the ineffectiveness of strategies based on the offender. The main argument of this data-driven policy is that crime is a result of the characteristics of a particular area as opposed to people. Members of the public living in a high-crime area are likely to adopt criminal behavior, while putting such people in areas with no crime would cause them to adopt similar behavior. Therefore, crime is a product of a place and not an individual. The rates of crime vary across different areas and become more apparent in more localized areas, which can be referred to as microplaces. Examples of microplaces include convenience stores, abandoned buildings, apartment complexes, and small jurisdictions that have high criminal activity as a result of their social or physical characteristics (Braga et al., 2019). For instance, areas with street children or drug addicts are likely to have significantly high crime rates. Moreover, this policy also includes the aspect of time as a significant factor contributing to criminal activities. Such times are referred to as hot times. For instance, areas of night entertainment can experience times of increased crime rates when the law enforcement agents exit at 2 AM. Due to reduced security, criminals can launch their attacks during such times since they know that patrols have exited the areas.
Hot-spots policing is a policy that ensures the allocation of resources by the police department based on crime data from various places. Areas that post high crime rates are perceived to need more resources to combat criminals and improve public safety. The policy provides a paradigm for figuring out where and how many law enforcement agents should be deployed to ensure public safety. However, one limitation of the policy is that it does not provide information about the type of crime, criminals, or weapons used in such areas. As a result, the police need to have information on what to do after arriving at such areas. Consequently, the police department must ensure having such information to increase the efficiency of hot-spots policing. Fortunately, police administrators have ensured an abundance of research to access information on approaches to areas with high crime rates that are successful and those not. Police officers are encouraged to increase their visibility in such areas to identify the most common patterns of crimes in such areas. In so doing, police officers can anticipate the type of crime and weapons to be employed by criminals, if any (Gau, 2019). The main reason is that crimes across areas vary significantly. For instance, one area can be a hot spot for selling illegal drugs, while another can be a hot spot for street gangs. Therefore, despite both areas being described as hot-spots for crime, the approach by police officers will significantly differ.
Application
The data-driven policy of hot-spots policing has been applied by various departments with significant success. The Nassau County Police Department employed the policy to arrest the suspect of killing at Gilgo Beach. The area has had a long history of high crime rates, causing the police to mark it as one of the hot spots. The suspect, a 59-year-old called Rex Heuermann, was charged with killing three adult females and remains the major suspect in killing a fourth female. Despite the crime happening more than ten years ago, the Nassau County Police Department employed technological data to find evidence of the killings. The bodies of the first three women were found in hunting camouflage burlap near the beach’s stretch. The three were petite girls in their 20s who worked as escorts on the beach. The body of the fourth woman who was killed earlier was found disposed of in a similar way (Cramer et al., 2023). Police pointed out that technology had helped in finding evidence of disposable cellular phones’ location, which the suspect used to call the victims before their disappearance and death.
Conclusion
The essay discusses the effectiveness and efficiency of hot-spots policing, including a case example of its application by the local police department. The US criminal justice system has embraced various data-driven policies such as intelligence-based policing, Compstat, and hot-spots policing. The hot-spots policy was informed by the criminological study and research showing the ineffectiveness of strategies based on the offender. The Nassau County Police Department employed the policy to arrest the suspect of killing at Gilgo Beach. The policy should be embraced across all states.
References
Braga, A. A., Turchan, B., Papachristos, A. V., & Hureau, D. M. (2019). Hot spots policing of small geographic areas effects on crime. Campbell Systematic Reviews, 15(3). https://doi.org/10.1002/cl2.1046
Cramer, M., Rashbaum, W. K., Goldstein, J., & Kilgannon, C. (2023, July 14). Suspect Arrested in Serial Killings of Women Near Gilgo Beach. The New York Times. https://www.nytimes.com/2023/07/14/nyregion/gilgo-beach-murders-long-island-suspect.html
Gau, J. M. (2019). Chapter 13: Policy Policy. In Gau, J. M. (2019). Criminal Justice Policy: Origins and Effectiveness. Oxford University Press.
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