A Technical Guide to Jail Data Analysis

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Analyzing jail data is a crucial part of understanding incarceration trends. Quantitative data from local government sources can help to drive policy and inform change by providing insights into who is in jail and for how long, the reasons why, and which system actors are involved. Used in concert with research on the human and financial costs of jail, jail data analysis can help demonstrate why reducing local jail populations may lead to better outcomes in the community.

Analyzing such data, however, requires several steps and considerations. This guide provides an overview of the broad framing questions and key steps of analyzing jail data. It also explains technical details in language that is accessible to people without statistics or database training. This resource also offers sample analyses, sample data request details, and views into what different kinds of jail data analyses can tell us about trends and potential policy solutions.

Key Takeaway

Quantitative data on jail populations from local government sources is a key tool in understanding and changing a jail’s impact on one’s community. Careful analysis of local jail data provides a basis for fact-based discussions about policy changes to reduce how many people enter jails and how long they stay.

Publication Highlights

  • Jail data analysis should consider reasons for jail admissions overall and factors that lead to longer lengths of stay, as both influence the average daily population.

  • A significant part of jail data analysis is data cleaning: understanding different terms and then organizing and cleaning the data into a format that works for the planned analysis.

  • More granular jail data analyses that take into account factors such as race and gender can show who is booked into jail, why, and what influences how long they stay.