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The purpose of this study is to determine the impact of incarceration on public safety. For the research topic “The Impact of Incarceration on Public Safety,” a thorough sampling strategy is essential to guarantee the validity and dependability of the study’s findings. To fully assess the effect of incarceration on public safety, the sample plan for this study subject will include probability and non-probability sampling techniques (Bhattacharya & Aslam, 2020). Finding the target population is the first step in creating a sample plan. The demographic of interest in this situation would be people who have been imprisoned and their effects on public safety.
The research population will be defined; it will include people who have been incarcerated and people in the wider public who have been influenced in some manner by incarceration. For example, family members of jailed individuals and residents in communities with high incarceration rates. The sample size will then be calculated using n = (Z^2 * p * (1-p)) / E^2. Where n is the sample size, Z is the standard normal deviate, set at 1.96 for a 95% confidence level, p is the estimated proportion of the population with a specific attribute, set at 0.5 for this study, and E is the maximum acceptable error, set at 0.05 for this study (Bhattacharya & Aslam, 2020). Therefore, to compute the total sample size, the sample size for each stratum will be determined individually. This step will be determined by several factors, including the size of the research population, the level of accuracy desired for the results, and the resources available to conduct the study. A sample size of 500 people from the general population and 500 people who have been imprisoned will be appropriate for this investigation.
The appropriate sample technique for this inquiry will then be determined. The two main types of sampling procedures are probability sampling and non-probability sampling. When using probability sampling, each person in the population has a known, non-zero chance of being chosen for the sample. Non-probability sampling is a strategy in which it is hard to predict which population members will be selected for the sample. For this project, a probability sampling strategy will be the best alternative. This sampling allows for reliable estimation of population parameters and generalizations about the population based on the sample. A probability sampling technique will also ensure that the sample is representative of the population, which is critical for ensuring that the results are accurate. The research population will be divided into subgroups based on criteria such as race and gender, and a stratified random sample will be drawn from each category (Loeffler & Nagin, 2022). Thus, the sample will be guaranteed to be representative of the entire research population. Another option is a cluster sample, where people are drawn from fewer geographical areas, such as towns and neighborhoods.
Surveys, interviews, and focus groups will be used to collect data. For example, a survey will be distributed to both the general public and convicts to learn more about their perspectives and experiences regarding the impact of incarceration on public safety (Public Safety Canada, 2022). Interviews and focus groups will be conducted with key stakeholders, including criminal justice professionals, to gather their perspectives and experiences. The data will then be evaluated to make decisions about how incarceration affects public safety. The data collected will be examined using descriptive statistics such as frequencies and percentages, as well as inferential statistics such as the chi-square test, t-test, and regression analysis (Stone et al., 2021). Regression analysis will be utilized to study the links between incarceration and other public safety outcomes, such as crime and recidivism rates. Therefore, using the analysis findings, recommendations for policy and practice will be developed to improve the effect of incarceration on public safety.
References
Bhattacharya, R., & Aslam, M. (2020). Generalized multiple dependent state sampling plans in presence of measurement data. IEEE Access, 8, 162775–162784. Web.
Loeffler, C. E., & Nagin, D. S. (2022). The impact of incarceration on recidivism. Annual Review of Criminology, 5(1), 133–152. Web.
Public Safety Canada. (2022). The effects of prison sentences and intermediate sanctions on recidivism: General effects and individual differences. Public Safety Canada. Web.
Stone, A. G., Lloyd, C. D., & Serin, R. C. (2021). Dynamic risk factors reassessed regularly after release from incarceration predict imminent violent recidivism. Law and Human Behavior, 45(6), 512–523. Web.
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