Good Policing Strategies Essay Example
Type of paper: Essay
Topic: Information, Strategy, Crime, Social Issues, COP, Community, Public, Intelligence
Pages: 2
Words: 550
Published: 2020/12/23
There are different policing strategies that are in use today; these include intelligence led, problem-oriented policing, COMPSTAT, community oriented and predictive policing. The strategies have various similarities and differences in relation to each other. COMPSTAT differs from ILP in that it is responsive and mostly used at the tactical level while ILP is mostly used proactively and to address long-range problems. COP differs from IPL in that it uses information to define problems while IPL uses information for analysis. In COP, the police receive information from the public and provide safety education in return while, in IPL, public information is used for threat analysis (Bullock 2013).
Predictive policing differs from COMPSTAT in that it focuses on the future possibilities of crime happening while COMPSTAT is reactive. Problem- oriented policing differs from community policing in that it singles out a particular problem and develops strategies to address it while COP is broad-based and addresses all types of problems in the community. ILP differs from COP in that it solves problems by focusing on targets and trafficking while COP solves problems by seeking precursors to crime. ILP differs from problem-oriented policing in that most of the issues it addresses are long-term while problem-oriented policing handles both short-term and long-term problems equally. COP varies from predictive policing in that its primary source of data and information is the public while the primary source of data for predictive policing is past records of criminal activities. Predictive policing uses such calculate the possibility of crime occurring in different areas.
The various strategies also have similarities in the way they operate. ILP and COMPSTAT both rely on data collection and analysis that provides information which is the basis for decision-making. COP and ILP are also similar in that they both rely on the public to provide them with information regarding possible crimes and actual criminal activities (Innes et al. 2009). Predictive policing and problem-oriented policing are similar in that they both use past crime trends when developing strategies on how to deal with future incidences of crime. COMPSTAT and predictive policing are also similar in that past data on crime is needed for analysis. COP and predictive policing are similar in that they both seek precursors to crime. ILP and problem- oriented policing are similar in that they focus on targets.
The various police strategies can work in tandem. Although each of the strategies has its focus and techniques that it employs, the desired end results are similar. They strategies can work in tandem and offer critical support to one another. For example, Intelligence-led policing makes excellent use of information gathered through community oriented policing. The best results are realized when a combination of two or more of the strategies is put into use. The participants in the various policing strategies can coordinate in data gathering and analyzing and evaluation. Sharing of independently collected data is also possible which facilitates a broad coverage of the issues at hand. The Application of data across the strategies is also possible shedding more light on criminal activities that run across the board. The strategies can also work in tandem in order to consolidate their efforts and accomplish more with the resources that each has. Although the strategies always focus on their core business, there is none that is mutually exclusive. None of the approaches perform its duties without even the slightest relation to the others.
Works Cited
Bullock Karen. (2013). Community, Intelligence-led Policing and Crime Control. Policing and Society 23(2):125-144.
Innes, M., Roberts, C., & Laurence A. (2009). Seeing Like a Citizen: Field Experiment in Community Intelligence-led Policing. Police Practice and Research 10(2):99-114.
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