Statistics and criminal justice leadership

Using statistics in criminal justice leads to evidence-based policy and practice. Criminal justice leadership can rely on statistical data to understand which policies are working and why, and how to change policies that are not yielding desired results. Leaders who rely on statistics are less likely to base policy decisions and judgments regarding criminal justice practices on politics rather than on achieving specific goals such as crime rate reduction. Therefore, criminal justice statistics can help improve organizational efficiency and integrity, allowing leaders to focus resources on policies and programs that yield demonstrable and significant results.
Statistical data helps criminal justice policy makers divert resources appropriately to fund studies that yield measurable results. Moreover, statistical research can help promote new techniques, tactics, programs, policies, procedures, and technologies that can help reduce rates of crime and create safer communities. According to the United States Department of Justice (2017), “research is critical to the development of sound criminal justice policy, as well as to the development of advanced technologies that support the work of law enforcement agencies,” (p. 1). Evidence-based practice seems like common sense, but has not always been fully integrated into criminal justice policy. As Bouchey (2016) points out, stereotyping and bias factor strongly into policy decisions in criminal justice. The Bouchey (2016) study finds, “state governments are more likely to adopt innovations that extend benefits to strong, popular, and powerful target populations or that impose burdens on weak and politically marginalized groups,” (p. 198). The failed war on drugs is a prime example of how criminal justice policy has been based too long on superstition, bias, and political whims rather than on statistical evidence. Increased reliance on statistical data can prevent public policy from being biased, so long as the research itself is conducted ethically, reliably, and validly.
Another benefit of relying on evidence-based practice, policy, and procedure in policing is that it allows diverse jurisdictions to implement programs that directly impact their own communities. Criminal justice policy can be based on data that is not necessarily generalizable to different population groups. Therefore, science literacy helps criminal justice policymakers to advise local departments of how to interpret results of research in credible and ethical ways. Statistical analysis can show, for example, how to create an optimal community policing model in a rural neighborhood or in a neighborhood where the majority of people do not speak English as a first language. The Bureau of Justice Statistics (BJS, 2017) “collects, analyzes, publishes, and disseminates information on crime, those who commit crime, victims of crime, and the operation of justice systems at all levels of government,” (p. 1). Using unbiased raw statistical data can also show how specific populations are being affected by criminal justice policies.
One of the reasons why community policing and community engagement in police policy has become increasingly common is in fact because statistical evidence proves these types of policies and programs to be effective. Many of the studies that measure outcomes of community policing cannot rely solely on universal crime reports, victimization data, or other statistical data collected by the BJS (2017). Researchers in criminal justice can assess other factors that promote public safety and offer long-term results in crime reduction. For example, meta-analyses of dozens of studies on community policing showed statistically significant improvements in public perceptions of police in the communities using community policing models (Gill, Weisburd & Telep, 2016). Public perceptions of police are not a crime-related statistical measure, but it is a crucial variable in determining overall effectiveness of police programs. Increasingly, sociological statistics can become integrated into criminal justice policy.
Because of the tendency to manipulate or misunderstand statistical data, criminal justice leaders and researchers need to take a more ethical and science literate approach to interpreting and using statistics. The differences between correlation and causation need to be clearly defined, in order to inform better and more ethical public policy. In some situations, though, statistical evidence fails to impress policy makers. Khan & Martin (2016), for example, found that statistical evidence highlights racial disparities in policing but the research has not yet led to substantive policy changes. Policy makers and criminal justice leaders need to resolve more to ignore the pleas of a misinformed and biased public and the politicians that pander to them, and to instead base their policies and programs on statistical evidence. Statistical evidence can be used to inform policing policies such as urging police to build bridges with residents of the communities rather than resort to stop-and-frisk programs. Likewise, statistical evidence can be used to show that police who wear body cameras are less likely to commit racially motivated stops or use force unnecessarily.
As with all the social sciences, criminology is ultimately a research-based field of study. Research in criminology does not exist in an academic vacuum, even when research is conducted and funded by universities. Criminal justice research needs to be fully integrated with criminal justice policy. Statistical evidence can be used to inform federal criminal justice policy or policies implemented at the state or local level. Correct, accurate, and ethical interpretations of statistical data ensure that research is not manipulated or misunderstood. Finally, policy makers can use statistical data to suggest future criminal justice policies and programs. Statistical data provides feedback on whether programs are working and what might be done to change them if they are not.



References

Boushey, G. (2016). Targeted for diffusion? American Political Science Review 10(1): 198-214.
Bureau of Justice Statistics (BJS, 2017). Criminal Justice Data Improvement Program. Retrieved online: https://www.bjs.gov/index.cfm?ty=tp&tid=4
Gill, C., Weisburd, D. & Telep, C. (2016). Community policing. In Advancing Criminology and Criminal Justice Policy. Routledge, pp. 119-129.
Khan, K. & Martin, K.D. (2016). Policing and race. Social Issues and Policy Review 10(1): 82-121.
United States Department of Justice (2017). Research, statistics, and evaluation. Retrieved online: https://ojp.gov/programs/research_stats.htm