The article by Alfred Blumstein (2013) examines the relationship between evidence and criminal justice policies. The first section elaborates on three research papers that show evidence in three different domains. The research by Fagan (2013) focuses on crime prevention by highlighting the significance of policy decision-making. The second research by Mears explains the existence of tension between presumptions of great effectiveness in prison control. Additionally, the study explains the concerns of psychological damage among persons assigned to carry out forms of solitary confinement (Blumstein, 2013). The third research by Nagin & Weisburd (2013) focuses on police operation management. Specifically, this study used four significant quasi-experiments to show how changes in police departments affect crime rates. The three studies state that linking evidence to policy is one of the complicated tasks in the criminal justice system.
The article shows the differences in linking evidence to policy between the criminal justice system and the medical field. In medicine, evidence is ingrained as the only method of introducing medical policy change. On the other hand, lawyers focus on advocacy skills in criminal justice. At the judicial level, the standards for making decisions are based on the consistency of constitution and law and not scientific standards (Blumstein, 2013). The majority of the criminal justice system policy choices are formulated by legislatures where political appeal and ideology are salient. In the medical field, scientific findings have been in place for centuries of tradition. Notably, new knowledge continues to emerge in neuroscience and genetics. Policy choices like testing frequency and identification of new tests have been challenged on their costs and effectiveness. According to the author, one significant feature in criminal justice policies is their multidimensional state. Crime reduction is a crucial criterion for most studies, but it only appears alone.
The article explores several research approaches in the criminal justice system that are used to measure treatment effects. The first approach is randomized control trials based on the rehabilitative treatment of offenders. Lawrence Sherman introduced the first RCTs on policing operations in the 1980s, One crucial principle in science is replication in findings. Notably, the domestic and assault experiment by Sherman and Berk in 1984 played a significant role in the criminal justice system (Blumstein, 2013). The study results showed that arrest is more effective than counseling while reducing recidivism rates. The second method is quasi-experimental trials. Quasi trials can be applied when randomization fails since they provide strong effect estimates. Quasi trials also use regression discontinuity designs where researchers have several outcome designs. The last approach researcher in the criminal justice system use is statistical analysis. The common method is regression analysis, which usually enumerates several factors contributing to outcome measures.
The article examines several ways of strengthening the association of evidence and policies in the criminal justice system. The authors acknowledge that estimating treatment impacts in criminal justice is complicated. However, with strong scientific evidence, there are several ways of improving criminal justice research. One of the strongest evidence originates from randomized controlled trials, although this method is unclear since there are several contaminants in such trials (Blumstein, 2013).In certain circumstances, when RCT is not feasible, there are numerous opportunities for conducting observational analysis. Notably, when such cases arise, the models used for analysis should be robust, and variable combinations should be challenged and tried to promote good results. Additionally, if experiments are conducted, they should be preceded through analytic methods that involve observational opportunities for identifying the most effective structure in experimental designs.
It is significant to ensure that the contextual variables influencing measured effects are integrated using statistical models when using statistical analysis. Additionally, policymakers should conduct analysis based on relevant observations within domains like the mayor’s city. However, if the project is funded through a federal grant, it is important to test its robustness by gathering observations using different settings (Blumstein, 2013). Notably, it is important to collect data by measuring treatments together with multiple impacts on the variables characterizing the context of treatment surroundings when implementing policy innovations. An independent analyst should conduct the basic evaluation by deriving preliminary forecasts of their effects.
The author acknowledges that criminology research is a significant contributor towards the development of policy concerning crimes control and valuable operations in criminal justice agency. Two crucial streams within criminology research affect policies in several ways. The first method is developed to change policy evaluation, and it should involve certain innovations or change mostly found in quasi and experimental models (Blumstein, 2013). Most evaluations in the criminal justice system are collected in places like federal websites (CrimeSolutions.gov.) and the Blueprints program offered by the University of Colorado in collaboration with Campbell University. The other approach is finding new tests and theories concerning the emerging issues in criminology. Analytic perspectives and new methods are helpful since they provide better opportunities to organize contemporary data series differently. There are several opportunities for criminologists experts to understand sensitized towards complexities in the policy process. One of the crucial institutions that sort conflicting interpretations for effective policy application is Committee for Law and Justice in National Research Council.
Blumstein, A. (2013). Linking evidence and criminal justice policy. Criminology & Pub. Pol’y, 12, 721.