As of 2022, Black people were more likely than those of other races to be imprisoned in the United States. In that year, the rate of imprisonment for Black men stood at ***** per 100,000 of the population. For Black women, this rate stood at ** per 100,000 of the population.

These data assess the effects of the risk of local jail incarceration and of police aggressiveness in patrol style on rates of violent offending. The collection includes arrest rates for public order offenses, size of county jail populations, and numbers of new prison admissions as they relate to arrest rates for index (serious) crimes. Data were collected from seven sources for each city. CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILE 1A (ICPSR 7941), provided county-level data on number of persons by race, age, and age by race, number of persons in households, and types of households within each county. CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: SUMMARY TAPE FILE 3A (ICPSR 8071), measured at the city level, provided data on total population, race, age, marital status by sex, persons in household, number of households, housing, children, and families above and below the poverty level by race, employment by race, and income by race within each city. The Federal Bureau of Investigation (FBI) 1980 data provided variables on total offenses and offense rates per 100,000 persons for homicides, rapes, robbery, aggravated assault, burglary, larceny, motor vehicle offenses, and arson. Data from the FBI for 1980-1982, averaged per 100,000, provided variables for the above offenses by sex, age, and race, and the Uniform Crime Report arrest rates for index crimes within each city. The NATIONAL JAIL CENSUS for 1978 and 1983 (ICPSR 7737 and ICPSR 8203), aggregated to the county level, provided variables on jail capacity, number of inmates being held by sex, race, and status of inmate's case (awaiting trial, awaiting sentence, serving sentence, and technical violations), average daily jail populations, number of staff by full-time and part-time, number of volunteers, and number of correctional officers. The JUVENILE DETENTION AND CORRECTIONAL FACILITY CENSUS for 1979 and 1982-1983 (ICPSR 7846 and 8205), aggregated to the county level, provided data on the number of individuals being held by type of crime and sex, as well as age of juvenile offenders by sex, average daily prison population, and payroll and other expenditures for the institutions.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.The data were obtained from one state prison system that was characterized by a diverse and rising prison population. This prison system housed more than 30,000 inmates across 15 institutions (14 men's facilities; 1 women's facility). The data contain information on inmates' placements into different housing units across all 15 state prison complexes, including designated maximum security, restrictive housing units. Inmates placed in restrictive housing were in lockdown the majority of the day, had limited work opportunities, and were closely monitored. These inmates were also escorted in full restraints within the institution. They experienced little recreational time, visitation and phone privileges, and few interactions with other inmates. The data contain information on inmates' housing placements, institutional misconduct, risk factors, demographic characteristics, criminal history, and offense information. These data provide information on every housing placement for each inmate, including the time spent in each placement, and the reasons documented by correctional staff for placing inmates in each housing unit. Demographic information includes inmate sex, race/ethnicity, and age. The collection contains 1 Stata data file "Inmate-Housing-Placements-Data.dta" with 16 variables and 124,942 cases.

The purpose of this study was to examine the crime of identity theft from the offenders' perspectives. The study employed a purposive sampling strategy. Researchers identified potential interview subjects by examining newspapers (using Lexis-Nexis), legal documents (using Lexis-Nexis and Westlaw), and United States Attorneys' Web sites for individuals charged with, indicted, and/or sentenced to prison for identity theft. Once this list was generated, researchers used the Federal Bureau of Prisons (BOP) Inmate Locator to determine if the individuals were currently housed in federal facilities. Researchers visited the facilities that housed the largest number of inmates on the list in each of the six regions in the United States as defined by the BOP (Western, North Central, South Central, North Eastern, Mid-Atlantic, and South Eastern) and solicited the inmates housed in these prisons. A total of 14 correctional facilities were visited and 65 individuals incarcerated for identity theft or identity theft related crimes were interviewed between March 2006 and February 2007. Researchers used semi-structured interviews to explore the offenders' decision-making processes. When possible, interviews were audio recorded and then transcribed verbatim. Part 1 (Quantitative Data) includes the demographic variables age, race, gender, number of children, highest level of education, and socioeconomic class while growing up. Other variables include prior arrests or convictions and offense type, prior drug use and if drug use contributed to identity theft, if employment facilitated identity theft, if they went to trial or plead to charges, and sentence length. Part 2 (Qualitative Data), includes demographic questions such as family situation while growing up, highest level of education, marital status, number of children, and employment status while committing identity theft crimes. Subjects were asked about prior criminal activity and drug use. Questions specific to identity theft include the age at which the person became involved in identity theft, how many identities he or she had stolen, if they had worked with other people to steal identities, why they had become involved in identity theft, the skills necessary to steal identities, and the perceived risks involved in identity theft.

At the beginning of 2025, the United States had the highest number of incarcerated individuals worldwide, with around 1.8 million people in prison. China followed with around 100,000 fewer prisoners. Brazil followed in third. The incarceration problem in the U.S. The United States has an incredibly high number of incarcerated individuals. Therefore, the incarceration problem has become a widely contested issue, because it impacts disadvantaged people and minorities the most. Additionally, the prison system has become capitalized by outside corporations that fund prisons, but there is still a high cost to taxpayers. Furthermore, there has been an increase in the amount of private prisons that have been created. For-profit prison companies have come under scrutiny because of their lack of satisfactory staff and widespread lobbying. Violent offenses are the most common type of offense among prisoners in the U.S. Incarceration rates worldwide El Salvador had the highest rate of incarceration worldwide, at 1,659 prisoners per 100,000 residents as of February 2025. Cuba followed in second with 794 prisoners per 100,000 inhabitants. The incarceration rate is a better measure to use when comparing countries than the total prison populations, which will naturally have the most populous countries topping the list.

ObjectiveThere is currently inconclusive evidence regarding the relationship between recidivism and mental illness. This retrospective study aimed to use rigorous machine learning methods to understand the unique predictive utility of mental illness for recidivism in a general population (i.e.; not only those with mental illness) prison sample in the United States.MethodParticipants were adult men (n = 322) and women (n = 72) who were recruited from three prisons in the Midwest region of the United States. Three model comparisons using Bayesian correlated t-tests were conducted to understand the incremental predictive utility of mental illness, substance use, and crime and demographic variables for recidivism prediction. Three classification statistical algorithms were considered while evaluating model configurations for the t-tests: elastic net logistic regression (GLMnet), k-nearest neighbors (KNN), and random forests (RF).ResultsRates of substance use disorders were particularly high in our sample (86.29%). Mental illness variables and substance use variables did not add predictive utility for recidivism prediction over and above crime and demographic variables. Exploratory analyses comparing the crime and demographic, substance use, and mental illness feature sets to null models found that only the crime and demographics model had an increased likelihood of improving recidivism prediction accuracy.ConclusionsDespite not finding a direct relationship between mental illness and recidivism, treatment of mental illness in incarcerated populations is still essential due to the high rates of mental illnesses, the legal imperative, the possibility of decreasing institutional disciplinary burden, the opportunity to increase the effectiveness of rehabilitation programs in prison, and the potential to improve meaningful outcomes beyond recidivism following release.

This project sought to investigate a possible relationship between sentencing guidelines and family structure in the United States. The research team developed three research modules that employed a variety of data sources and approaches to understand family destabilization and community distress, which cannot be observed directly. These three research modules were used to discover causal relationships between male withdrawal from productive spheres of the economy and resulting changes in the community and families. The research modules approached the issue of sentencing guidelines and family structure by studying: (1) the flow of inmates into prison (Module A), (2) the role of and issues related to sentencing reform (Module B), and family disruption in a single state (Module C). Module A utilized the Uniform Crime Reporting (UCR) Program data for 1984 and 1993 (Parts 1 and 2), the 1984 and 1993 National Correctional Reporting Program (NCRP) data (Parts 3-6), the Urban Institute's 1980 and 1990 Underclass Database (UDB) (Part 7), the 1985 and 1994 National Longitudinal Survey on Youth (NLSY) (Parts 8 and 9), and county population, social, and economic data from the Current Population Survey, County Business Patterns, and United States Vital Statistics (Parts 10-12). The focus of this module was the relationship between family instability, as measured by female-headed families, and three societal characteristics, namely underclass measures in county of residence, individual characteristics, and flows of inmates. Module B examined the effects of statewide incarceration and sentencing changes on marriage markets and family structure. Module B utilized data from the Current Population Survey for 1985 and 1994 (Part 12) and the United States Statistical Abstracts (Part 13), as well as state-level data (Parts 14 and 15) to measure the Darity-Myers sex ratio and expected welfare income. The relationship between these two factors and family structure, sentencing guidelines, and minimum sentences for drug-related crimes was then measured. Module C used data collected from inmates entering the Minnesota prison system in 1997 and 1998 (Part 16), information from the 1990 Census (Part 17), and the Minnesota Crime Survey (Part 18) to assess any connections between incarceration and family structure. Module C focused on a single state with sentencing guidelines with the goal of understanding how sentencing reforms and the impacts of the local community factors affect inmate family structure. The researchers wanted to know if the aspects of locations that lose marriageable males to prison were more important than individual inmate characteristics with respect to the probability that someone will be imprisoned and leave behind dependent children. Variables in Parts 1 and 2 document arrests by race for arson, assault, auto theft, burglary, drugs, homicide, larceny, manslaughter, rape, robbery, sexual assault, and weapons. Variables in Parts 3 and 4 document prison admissions, while variables in Parts 5 and 6 document prison releases. Variables in Part 7 include the number of households on public assistance, education and income levels of residents by race, labor force participation by race, unemployment by race, percentage of population of different races, poverty rate by race, men in the military by race, and marriage pool by race. Variables in Parts 8 and 9 include age, county, education, employment status, family income, marital status, race, residence type, sex, and state. Part 10 provides county population data. Part 11 contains two different state identifiers. Variables in Part 12 describe mortality data and welfare data. Part 13 contains data from the United States Statistical Abstracts, including welfare and poverty variables. Variables in Parts 14 and 15 include number of children, age, education, family type, gender, head of household, marital status, race, religion, and state. Variables in Part 16 cover admission date, admission type, age, county, education, language, length of sentence, marital status, military status, sentence, sex, state, and ZIP code. Part 17 contains demographic data by Minnesota ZIP code, such as age categories, race, divorces, number of children, home ownership, and unemployment. Part 18 includes Minnesota crime data as well as some demographic variables, such as race, education, and poverty ratio.

Human Trafficking Statistics: Human trafficking remains a pervasive global issue, with millions of individuals subjected to exploitation and abuse each year. According to recent statistics, an estimated 25 million people worldwide are victims of human trafficking, with the majority being women and children. This lucrative criminal industry generates profits of over $150 billion annually, making it one of the most profitable illegal trades globally. As market research analysts, it's imperative to understand the scale and impact of human trafficking to develop effective strategies for prevention and intervention. Efforts to combat human trafficking have intensified in recent years, driven by increased awareness and advocacy. However, despite these efforts, the problem persists, with trafficking networks adapting to evade law enforcement and exploit vulnerabilities in communities. Through comprehensive data analysis and research, we can uncover trends, identify high-risk areas, and develop targeted interventions to disrupt trafficking networks and support survivors. In this context, understanding human trafficking statistics is crucial for informing policy decisions, resource allocation, and collaborative efforts to combat this grave violation of human rights. Editor’s Choice Every year, approximately 4.5 billion people become victims of forced sex trafficking. Two out of three immigrants become victims of human trafficking, regardless of their international travel method. There are 5.4 victims of modern slavery for every 1000 people worldwide. An estimated 40.3 million individuals are trapped in modern-day slavery, with 24.9 million in forced labor and 15.4 million in forced marriage. Around 16.55 million reported human trafficking cases have occurred in the Asia Pacific region. Out of 40 million human trafficking victims worldwide, 25% are children. The highest proportion of forced labor trafficking cases occurs in domestic work, accounting for 30%. The illicit earnings from human trafficking amount to approximately USD 150 billion annually. The sex trafficking industry globally exceeds the size of the worldwide cocaine market. Only 0.4% of survivors of human trafficking cases are detected. Currently, there are 49.6 million people in modern slavery worldwide, with 35% being children. Sex trafficking is the most common type of trafficking in the U.S. In 2022, there were 88 million child sexual abuse material (CSAM) files reported to the National Center for Missing and Exploited Children (NCMEC) tip line. Child sex trafficking has been reported in all 50 U.S. states. Human trafficking is a USD 150 billion industry globally. It ranks as the second most profitable illegal industry in the United States. 25 million people worldwide are denied their fundamental right to freedom. 30% of global human trafficking victims are children. Women constitute 49% of all victims of global trafficking. In 2019, 62% of victims in the US were identified as sex trafficking victims. In the same year, US Department of Health and Human Services (HHS) grantees reported that 68% of clients served were victims of labor trafficking. Human traffickers in the US face a maximum statutory penalty of 20 years in prison. In France, 74% of exploited victims in 2018 were victims of sex trafficking. You May Also Like To Read Domestic Violence Statistics Sexual Assault Statistics Crime Statistics FBI Crime Statistics Referral Marketing Statistics Prison Statistics GDPR Statistics Piracy Statistics Notable Ransomware Statistics DDoS Statistics Divorce Statistics

Abstract (en): RECIDIVISM OF PRISONERS RELEASED IN 1994 is a database containing information on each of 38,624 sampled prisoners released from prisons in 15 states in 1994 and tracked for three years following their release. The majority of the database consists of information on each released prisoner's entire officially recorded criminal history (before and after the 1994 release). Sources for criminal history information are state and FBI automated RAP ("Records of Arrests and Prosecutions") sheets, which contain records of arrests, adjudications, and sentences. The study is the second major recidivism study conducted by the Bureau of Justice Statistics. The first study, RECIDIVISM AMONG RELEASED PRISONERS, 1983: UNITED STATES, tracked over 16,000 prisoners released in 11 states in 1983 for three years. These two studies are the closest approximation to "national" recidivism studies in the United States. They are distinguished by their large sample size (over 16,000 released prisoners in the first study, 38,624 in the second), geographic breadth of coverage (11 states in the first study, 15 in the second), length of prospective tracking (three years from date of release in both studies), ability to track the movement of released prisoners across state boundaries (both studies), and multiple measures of recidivism (both studies). Demographic data include race, ethnicity, sex, and date of birth. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Prisoners released during 1994 in the 15 states that the study covered. The 15 states account for about two-thirds of releases in the United States in a given year. Smallest Geographic Unit: state The following 15 state Departments of Corrections participated in the study: Arizona, California, Delaware, Florida, Illinois, Maryland, Michigan, Minnesota, New Jersey, New York, North Carolina, Ohio, Oregon, Texas, and Virginia. These departments supplied Bureau of Justice Statistics (BJS) with information on each person released from prison in the state in 1994 (Note: Illinois releases are for fiscal year 1994 rather than calendar year 1994). These 15 states were chosen as a purposive sample, based on willingness to participate, the state's relative contribution to the overall national prison population, and the state's inclusion in the earlier study of recidivism conducted by BJS in 1983 (see ICPSR 8875). The 15 states supplied BJS with release records on 302,309 prisoners released in 1994, approximately two-thirds of all prisoners released in the nation. Using these records, the researchers drew a representative sample from each state, totaling 38,624 out of the 302,309 released prisoners, stratified by most serious conviction offense. More detailed information regarding sampling procedures can be found in the codebook that accompanies this data collection. 2014-12-05 A minor change is made to the codebook.2012-01-12 For variable POTST, values for the state of New York were adjusted per the principal investigator.2011-03-08 All parts are being moved to restricted access and will be available only using the restricted access procedures.2009-02-09 Missing value codes were edited to correct for rounding and data entry errors.2007-03-02 The principal investigator revised the data so that there are 4,834 cases instead of 4,824 for values that are less than or equal to 90 for variable DCDV.2006-12-01 The principal investigator revised the description for variables RPRSD and RPRSITV in the codebook.2003-08-27 The principal investigator recoded some values in variables DCDV, RPRSD, RPRSITV, and RELTYP.2002-10-04 The principal investigator recoded some values (child victim age) in variable DCDV for 89 releases in the state of Virginia. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics.

In 2022, about 194,164 perpetrators of child abuse in the United States were white. In that same year, about 83,314 perpetrators of child abuse were Hispanic, and 25,092 were of unknown ethnic origin.

Abstract (en): This study was conducted to provide a consistent and comprehensive description of convicted persons' entrance into and departure from correctional custody and correctional supervision. To accomplish this goal, data were gathered from official state prison records on topics such as race, sex, and age of inmates, length of time in jail, length of time in prison, and type of offense committed. The data were collected from the state prison systems of 38 states, as well as the Federal Prison System, the California Youth Authority, and the District of Columbia. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. All persons incarcerated in prisons in the United States. All people incarcerated in 38 state prisons (plus federal prisons, the California Youth Authority, and the District of Columbia) in 1992. 2010-04-23 The entire NCRP series is being re-released in restricted format.2006-01-12 All files were removed from dataset 6 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 5 and flagged as study-level files, so that they will accompany all downloads.2006-01-12 All files were removed from dataset 4 and flagged as study-level files, so that they will accompany all downloads.1997-08-01 The data have been checked for wild or invalid codes, and the codebook and SAS and SPSS data definition statements now document these codes. In addition, the codebook is now available as a PDF file only, and the variable and value labels have been expanded. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Conducted by the United States Department of Commerce, Bureau of the Census.

Mental health disorders and symptoms by recidivism status.

In 2023, the unemployment rate of African Americans in the United States stood at 5.5 percent. This was over the national average of 3.6 percent.

The high rate of unemployment

There are many reasons why the unemployment rate among minorities is different than the national average. When it comes to African Americans, a large part of this is due to historical events, such as slavery and the struggle for civil rights, as well as the number of Black families living below the poverty level. Additionally, in 2019, for every 100,000 of the population, there were 2,203 Black men in prison. This high rate of imprisonment can contribute to the unemployment rate for African Americans, since having been in prison can reduce one’s chances of finding a job once released.

Earning differences

African Americans also make less money than other ethnicities in the United States. In 2020, the median weekly earnings of African Americans were 794 U.S. dollars, compared to Asians, who made 1,310 U.S. dollars per week, and whites, who made 1,003 U.S. dollars per week. While the African American unemployment rate may be low, it is clear that much has to change in order to achieve full equality.

Abstract (en): To reduce respondent burden for the 2013 collection, the Census of Jails was combined with the Deaths in Custody Reporting Program (DCRP). The census provides the sampling frame for the nationwide Survey of Inmates in Local Jails (SILJ) and the Annual Survey of Jails (ASJ). Previous jail enumerations were conducted in 1970 (ICPSR 7641), 1972 (ICPSR 7638), 1978 (ICPSR 7737), 1983 (ICPSR 8203), 1988 (ICPSR 9256), 1993 (ICPSR 6648), 1999 (ICPSR 3318), 2005 (ICPSR 20367), and 2006 (ICPSR 26602). The RTI International collected the data for the Bureau of Justice Statistics in 2013. The United States Census Bureau was the collection agent from 1970-2006. The 2013 Census of Jails gathered data from all jail detention facilities holding inmates beyond arraignment, a period normally exceeding 72 hours. Jail facilities were operated by cities and counties, by private entities under contract to correctional authorities, and by the Federal Bureau of Prisons (BOP). Excluded from the census were physically separate temporary holding facilities such as drunk tanks and police lockups that do not hold persons after being formally charged in court. Also excluded were state-operated facilities in Connecticut, Delaware, Hawaii, Rhode Island, Vermont, and Alaska, which have combined jail-prison systems. Fifteen independently operated jails in Alaska were included in the Census. The 2013 census collected facility-level information on the number of confined and nonconfined inmates, number of inmates participating in weekend programs, number of confined non-U.S. citizens, number of confined inmates by sex and adult or juvenile status, number of juveniles held as adults, conviction and sentencing status, offense type, number of inmates held by race or Hispanic origin, number of inmates held for other jurisdictions or authorities, average daily population, rated capacity, number of admissions and releases, program participation for nonconfined inmates, operating expenditures, and staff by occupational category. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Standardized missing values.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Datasets:DS1: Census of Jails, 2013 All locally, regionally, and federally administered jails in the United States. The respondent universe was derived from a facility list maintained by the Census Bureau for BJS, from correctional association directories, and from other secondary sources. Census forms were sent to each jail jurisdiction. In addition to a paper form, BJS offered respondents an electronic version via the internet, allowing them to complete and submit their completed questionnaires on-line. 2018-04-25 The dataset and the codebook have been updated2016-03-25 Two records needed to be updated. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. mail questionnaire web-based survey

This statistic shows the number of releases on day and full parole from federal prisons in Canada from the fiscal year of 2006 to the fiscal year of 2022. In the fiscal year of 2022, 62 prisoners were released on full parole from federal prisons in Canada. ParoleParole is the conditional release of an offender that allows them to serve the remainder of their sentence in the community under supervision. There are two type of parole in Canada: day parole, and full parole. The purpose of day parole is to prepare the inmate for full parole or statutory release. The inmate is allowed to participate in community-based activities but must return to either a correctional institution or community residence in the evening. An inmate is eligible for day parole six months before they are eligible for full parole. Full parole allows offenders to serve part of their sentence in the community under supervision. They are allowed to live in a private residence but must report regularly to a parole supervisor. An offender is eligible for full parole when they have served either one-third of their sentence or seven years, whichever is less. Those convicted of first degree murder are eligible after 25 years. Second degree murderers are eligible between 10 and 25 years into their sentences. Day parole is granted much more frequently than full parole. In the fiscal year of 2022, 715.8 percent of day paroles were granted, while only 30.4 percent of full paroles were granted. In general, non-aboriginal offenders have been more likely to be granted parole over the last decade. Aboriginal offenders also serve more of their sentence, on average, than their non-Aboriginal counter parts.

This statistic shows the percentage of eligible days and full paroles from federal prisons approved in Canada from the fiscal year of 2006 to the fiscal year of 2022. In the fiscal year of 2022, 30.4 percent of offenders eligible for full parole were granted release in Canada.