PolicePatrol Allocation and Deployment
PolicePatrol Allocation and Deployment
Thebroken window theory was first stated by Wilson and Kelling in 1982in a seminal article. The model relates the importance of disorder tocausing and supporting more severe crime. Though there are nocritical linkages between disorder and serious crimes, it is assumedthat disorder decreases the levels of informal social control of theresidents (Fritsch, Eric, John, and Robert, 2008). It furtherincreases fear and withdrawal of residents and hence more severecrime moves in. To disrupt this process, the police should prioritizetackling disorder and fewer grave crimes within the neighborhoodsthat are not yet overwhelmed by serious offenses(Carter, 2012).The police can assist the resident to put in check their area byincreasing both formal and informal social control hence reducingfear and resident withdrawal.
AccordingtoWain & Ariel (2014), thereis statistical significance in the policing methods that focus ondisorder. This strategy has proven its efficiency in deterring allforms of crime than the use of more radical approaches to crimeprevention. The police can efficiently cut down disorder andnon-disorder crime through the broken window model. According toCarter (2012), themodel may prove to be helpful when it comes to reclaiming the crimeprone areas and restoring them back to their safety status.
Themodel, however, possess some weaknesses: there are disagreements onwhether there exists a relationship between disorder and crime andthe proper measurement strategy if the relationship exists. Ifincreasing informal control influences the reduction in seriousoffenses, then it would take quite some time for such high levels ofsocial control to be attained(Fritsch, Liederbach& Taylor, 2009).Police observations utilize short follow-up strategies and may misson the neighborhood dynamics(Carter, 2012).There is also a concern on the effective formula to calculate brokenwindow treatment. The highly used indicator is the offensive arrestsbecause of the high availability of the data.
Amongthese weaknesses, the greatest criticism I have is the disagreementof the existence of a relationship between the theory’s mainparameters of disorder and crime. This difference brings some levelsof contradictions of the theory and therefore a person could not beconfident when using the approach(Wain & Ariel, 2014).
Reactivepolice patrol is a policy employed by the police to interact with acommunity when the society calls upon them (Fritsch,Liederbach& Taylor, 2008).Reactive police patrol is a classical method of policing a community.Although the police’s methods have been successful, they have facedcriticisms from within and outside policing for being reactive thanproactive(Carter, 2012).The reactive policing method makes them to be criticized for failingto deter crime.
Carter(2012), points that thepolice distance themselves from the community so as to retain theirimpartiality. They report to where crimes have occurred and when thecitizens summon them. Otherwise, they do not intrude or develop anyrelationship that could impair their responsiveness to criminalincidences. Community policing that does not incorporate an explicitfocus on crime risk has no impact on crime (Wain& Ariel, 2014).
Whenthe police make reactive arrests, they serve as random patrol castingout a wide net (Wain& Ariel, 2014).This responsive arrest warns the citizens that they can end up behindbars for breaking laws at any time. The police prefer to make arrestswith legal basis and hence the reactive police patrol would serve thepurpose
Thefirst among the limitations of the modern patrol methods is that thenumber of police that is required for allocation depends on theaccuracy of the data in the model (Fritsch,Liederbach& Taylor, 2008).If the model data such as, calls-for-services is not accurate, thenthe estimation of the police needed for a patrol will be incorrect.
Secondly,the officers used in patrol are also entitled to some other tasks.All variables impacting on patrol resources should be taken intoaccount to determine the optimum number of officers being allocatedfor patrol (Fritsch,Liederbach& Taylor, 2009).Third, the estimates by an allocation model are highly erroneous.This error is as a result of assuming some variables affectingdistribution in that jurisdiction. Other errors may arise from theneed to estimate some data components. This error arises from theunavailability of the data, for instance, the data on patrol speedmay not be available at the station. These estimations may be out oftouch with reality hence incorrect results.
Fourth,the data used to compute the model is out of time. Some data such ascalls for service data is usually a record of the previous year’sactivities. Therefore, the usage of such data results in incorrectfigures, as it does not relate to the present year’s occurrences.The fifth limitation is in the application of a mathematical model tocompute patrol allocation whereas policing keeps changing. Thesedynamics depend on upon the workload of calls-for-service that theyreceive. When there is a light call load, officers will spend moretime on personal calls, administrative duties, and breaks (Fritsch,Liederbach& Taylor, 2008).However, when the workload increases, officers put more focus more onthe problems reported.
Carter,J. (2012). The Philadelphia Foot Patrol Experiment: A RandomizedControlled Trial of Police Patrol Effectiveness in Violent CrimeHotspots. Policing, 35(1).http://dx.doi.org/10.1108/pijpsm.2012.18135aaa.002
Fritsch,Eric J., John Liederbach, and Robert W. Taylor. Police PatrolAllocation and Deployment. Upper Saddle River, NJ: Pearson PrenticeHall, 2008. Print.
Fritsch,E., Liederbach, J., & Taylor, R. (2009). Policepatrol allocation and deployment.Upper Saddle River, N.J.: Pearson Prentice Hall.
Wain,N. & Ariel, B. (2014). Tracking of Police Patrol. Policing, 8(3),274-283. http://dx.doi.org/10.1093/police/pau017