The criminal justice system affects everyone through the implementation of public policies. Policies ensure everyone follows the law by control people’s action. Policies are passed or changed to solve problems usually identified by politicians, media, citizens or advocacy groups. There is significant debate on the merits of the policy before implementing it (Radermacher, 2019). Implementation of a policy may be done differently from what the author intended. Evaluation of both the outcome and process periodically is paramount. Research is indispensable in policymaking. Policy research requires the participation of key stakeholders and the community. Communities help in identifying and addressing specific issues and problems. (Kay, 2011).
This is a proposal in support of the sexual offenders registries policy. The national sex offender registry is a public website run by the department of justice. It contains information about sex offenders and their location within the 50 states. The registry has reduced sexual offences in all the states (Lussier & Mathesius, 2016). Studies have shown that people who have committed sexual assault before are likely to be repeat offenders. The registry aims to protect children from sexual predators. It also enabled police to respond effectively to sexual crimes. Perpetrators of sexual offences are commonly friends or acquaintances of the victim. Sexual offenders commit these crimes within a 20-minute walk of a given location. The registries warn parents (Tewksbury, 2006).
Data Collection
Data retrieved from sex offenders registry records show the number of sexual offenders registered from the day of implementation of the policy. Adult criminal history records are electronic criminal records that identify sexual charges and convictions (Lussier & Mathesius, 2016). It is important that the data collected is accurate, usable and complete. Data collection from these records is strenuous. The data files are allocated numeric codes according to the offence. These codes are sometimes incorrect and therefore requires an investigator to go through the description of the assault. Definitions are altered once in a while to maintain data comparability (Harris & Cudmore, 2018).
Data Analysis
Sexual offender registries prevent sex offenders from repeating the same crime. An example of an analysis is the determination of the rate of recidivism. In a study by McManus, male offenders above the age of 16 are the basis of the study. Between January 1990 and December 2004, there were 6837 offenders, of which 773 were in prison for the entire study duration. 55% of the offences involved minors. The follow-up duration was 8.4 years. Approximately half of the offenders were arrested again at some point during the follow-up. During the follow-up period, 8% of new sex crime charges and 5% of new convictions were noted (McManus, 2013). This analysis determines the need for sex offender registries.
The second analysis is the association between failure to register and chances of recidivism, showing the impact of sexual offenders registries. In a study led by Professor Levenson, the supposition that sexual offenders that fail to register are more dangerous is disproved. 11% of those who failed to register had a recidivism charge compared to the 9% of compliant registrants (Levenson et al., 2009)
Use of Data
The use of data matters as the interpretation of data informs the making of policies. Data shows that registries deter first-time offenders. It does not have a significant effect on repeat offenders. The data also show that it does not increase the fear in community members (Harris & Cudmore,2018). Some even argue that being on the list increases crime as these offenders are unable to get jobs. Registries help in cases of abductions. We have also seen instances where the registry has enabled teachers to identify sex offenders lurking around schools. There are many unknowns. Informed decisions are through obtaining and interpreting data. (Lussier & Mathesius, 2016).
Utilization of Statistical Data in Policy Making
Information technology has improved in the past decade. Data is readily available. Formerly decisions have been made based on empirical evidence such as observation and personal experience. At the moment we use data to determine which policies implementable and which ones are not. Statistical data allows for predictive analytics using models. Predictive analytics allows for timely delivery of services to the people who need them the most (Radermacher, 2019). More data allows for better analysis. Big data allows for the development of accurate and representative data sets. Sometimes data gaps make it impossible to make an informed decision within the justice system, but governments can now harness the power of technology. Text analysis is used to measure community impressions on social media platforms such as Twitter. Image analysis can be used in poverty-stricken countries to develop an accurate understanding of the poverty levels. Statistical data is used to audit regulated industries and identify biases (Kay, 2011).
Conclusion
In the paper-based system, it was impossible to analyze data and generate credible results. Statistical data analysis enables governments to come up with policies that are tailored and targeted. The problem and its parameters are determined accurately. Statistical data also allows for testing and observing how problems respond. The ability to process data faster also permits for a more responsive government. Real-time data collections empower government officials. Analysis of statistical data also provides information on the nature of the problem, factors contributing to the problem and the communities are affected most.
