As of February 2025, El Salvador had the highest prisoner rate worldwide, with over 1,600 prisoners per 100,000 of the national population. Cuba, Rwanda, Turkmenistan, and the United States, rounded out the top five countries with the highest rate of incarceration. Homicides in El Salvador Interestingly, El Salvador, which long had the highest global homicide rates, has dropped out of the top 20 after a high number of gang members have been incarcerated. A high number of the countries with the highest homicide rate are located in Latin America. Prisoners in the United StatesThe United States is home to the largest number of prisoners worldwide. More than 1.8 million people were incarcerated in the U.S. at the beginning of 2025. In China, the estimated prison population totaled 1.69 million people that year. Other nations had far fewer prisoners. The largest share of the U.S. prisoners in federal correctional facilities were of African-American origin. As of 2020, there were 345,500 black, non-Hispanic prisoners, compared to 327,300 white, non-Hispanic inmates. The U.S. states with the largest number of prisoners in 2022 were Texas, California, and Florida. Over 160,000 prisoners in state facilities were sentenced for rape or sexual assault, which was the most common cause of imprisonment. The second most common was murder, followed by aggravated or simple assault.

As of December 2022, there was a total of 139,631 prisoners in the state of Texas, the most out of any state. California, Florida, Georgia, and Ohio rounded out the top five states with the most prisoners in the United States.

This project sought to prove that research files could be created through the extraction of personnel management systems data. There were five goals associated with designing and creating the Florida Criminal Justice Workforce Research Information System: (1) to extract data from two transaction management information systems, which could then be used by researchers to describe and analyze the workforce that administers justice in Florida, (2) to pilot test the concept of developing a new research information source from existing data systems, (3) to forge partnerships with diverse criminal justice agencies having a mutual need to understand their respective workforces, (4) to design research files to enable internal and external researchers to utilize the data for analytical purposes, and (5) to describe the methodology used to create the workforce information system in sufficient detail to enable other states to replicate the process and develop their own criminal justice workforce research databases. The project was jointly conceived, designed, and completed by two state-level criminal justice agencies with diverse missions and responsibilities: the Florida Department of Law Enforcement (FDLE) and the Florida Department of Corrections (FDC). Data were extracted from two personnel management systems: the Automated Transaction Management System (ATMS) operated by the Florida Department of Law Enforcement, which contains data on all certified law enforcement, correctional, and correctional probation officers in Florida (Part 1), and the Cooperative Personnel Employment System (COPES) operated by the Department of Management Services, which contains data on all state employees (Part 2). Parts 3-5 consist of data extracted from Parts 1 and 2 regarding certification status (Part 3), education (Part 4), and training (Part 5). Two demographic variables, race and sex, are found in all parts. Parts 1 and 2 also contain variables on employment event type, employer type, position type, salary plan, job class, appointment status, and supervisor indicator. Part 3 variables are certification event type and certificate type. Part 4 variables include degree earned and area of degree. Part 5 includes a variable for passing or failing training certification.

This study analyzes shock incarceration (boot camp) programs in Florida, Georgia, Illinois, Louisiana, Oklahoma, South Carolina, and Texas. In each state, offenders who participated in boot camps were compared with demographically similar offenders who were sentenced to prison, probation, or parole. The impact of shock incarceration on offenders was assessed in two major areas: (1) changes in offenders' attitudes, expectations, and outlook during incarceration (self-report/attitude data), and (2) performance during and adjustment to community supervision after incarceration (community supervision data). The self-report/attitude data include variables measuring criminal history, drinking and drug abuse, and attitudes toward the shock incarceration program, as well as demographic variables, such as age, race, employment, income, education, and military experience. The community supervision data contain information on offenders' behaviors during community supervision, such as arrests, absconding incidents, jail time, drug use, education and employment experiences, financial and residential stability, and contacts with community supervision officers, along with demographic variables, such as age and race. In addition to these key areas, more detailed data were collected in Louisiana, including a psychological assessment, a risk and needs assessment, and a community supervision follow-up at two different time periods (Parts 11-18). For most states, the subjects sampled in the self-report/attitude survey were different from those who were surveyed in the community supervision phase of data collection. Data collection practices and sample structures differed by state, and therefore the data files are organized to explore the impact of shock incarceration at the state level. For each state, the unit of analysis is the offender.

This study was undertaken to investigate the relationship, if any, between drug treatment and success or failure of drug-involved offenders on probation/community supervision. Further, the researchers sought to evaluate the outcomes of drug-involved offenders admitted to (1) secure residential substance abuse treatment (RSAT) programs, (2) non-secure residential drug treatment programs, (3) non-residential drug treatment programs, and (4) no drug treatment programs. Data were collected from administrative records provided by the Florida Department of Corrections, specifically case history records of offenders admitted to supervision in the community from July 1, 1991, through June 30, 1997. Part 1 is comprised of all cases admitted to community supervision between July 1, 1991, and June 30, 1993 (fiscal years 1991 and 1992) and treated in a secure residential drug treatment program. Part 2 is comprised of all cases admitted to community supervision from July 1, 1991, through June 30, 1995, receiving treatment in a non-secure residential drug treatment program. Part 3 contains data on offenders admitted to non-residential drug treatment programs, whose community supervision admissions were between July 1, 1991, and June 30, 1993. Part 4 contains data on offenders admitted to non-residential drug treatment programs, whose community supervision admissions were between July 1, 1993, and June 30, 1995 (fiscal years 1993 and 1994). Part 5 contains data on cases admitted to community supervision between July 1, 1991, and June 30, 1993, who did not receive drug treatment of any kind. Cases admitted to community supervision between July 1, 1993, and June 20, 1995, receiving no drug treatment are contained in Part 6. Each supervision admission record contains a history of subsequent court actions that were complete through December 31, 1997. Variables for all parts include population estimates, unemployment rates, population by age-specific categories, violent and nonviolent index offenses, per capita personal income, clearance rates, split sentence flag, primary offense disposition, primary offense felony level, current commitment years supervised, supervision type, whether current offense included a drug charge, number of prior supervision terms, number of prior commitments, reasons for failure, treatment facility code, number of drug sale/traffic offenses, outcome of supervision period, and reasons for prison intake. Demographic variables include race and gender.