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.

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.

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.

In 2024, there were 87,869 men and 3,635 women in prisons in England and Wales. Compared with the previous year, this represented an increase for both men and women. This represented a peak in the number of prisoners during this provided time period, and was also the peak for the United Kingdom as a whole.
Demographics of prisoners There were 29,339 prisoners in their 30s in England and Wales in 2024, the most of any age group. In this year, there were also 3,354 prisoners who were aged between 15 and 20, with a further 21,381 prisoners who were in their 20s. In terms of the ethnicity of prisoners in England and Wales, 63,103 people in jail were White, 10,624 were Black, and 7,067were Asian. As of the same year, the most common religious faith of prisoners was Christianity, at 39,068 inmates, followed by 27,122 who identified as having no religion, with a further 15,909 who were Muslims. Increase in prison officers since 2017 The 23,614 prison officers working in England and Wales in 2024 was almost as high as 2011 when there were 24,369 officers. From 2010 onwards, the number of prison officers fell from 24,830 to 18,251 by 2014, and stayed at comparably low levels until 2018. Low government expenditure on Prisons during the same time period suggests this was a result of the austerity policies implemented by the UK government at that time. The government has steadily increased spending on prisons since 2019/20, with spending on prisons reaching 6.09 billion in 2022/23. This has however not been enough to avert a possible overcrowding crisis in England and Wales, which had just 768 spare prison places in September 2023.

A. SUMMARY Please note that the "Data Last Updated" date on this page denotes the most recent DataSF update and does not reflect the most recent update to this dataset. To confirm the completeness of this dataset please contact the Sheriff's Office at sheriff.tech.services@sfgov.org The dataset provides summary information on individuals booked into the San Francisco City and County Jail since 2012, categorized by ethnicity. The table provides a breakdown of the total number of bookings by month and ethnicity. The unit of measure is the jail booking number. The data is collected by the Sheriff's Office and includes self-report and assigned data. However, some ethnicity categories with small sample sizes are grouped together to reduce the risk of re-identification and protect the privacy of individuals booked into jail. The booking process refers to the procedure that occurs after an individual has been arrested and is taken into custody. The process begins with the arrest of an individual by law enforcement officers. The arrest can take place on the scene or at a later time if a warrant is issued. Once the individual has been arrested, and statutory law requires incarceration, they would be transported to the jail for booking. The arresting officer will record the reason for the arrest, along with any other relevant information. The sheriff’s deputies will then book the individual into jail, which involves taking their fingerprints, photograph, and recording personal information. The jail will assign a booking number, which is used to identify the individual throughout their time in custody. Once the booking process is complete, the individual will be incarcerated and will remain in custody until they are released per court order. Disclaimer: The San Francisco Sheriff's Office does not guarantee the accuracy, completeness, or timeliness of the information as the data is subject to change as modifications and updates are completed. B. HOW THE DATASET IS CREATED When an arrest is presented to the Sheriff’s Office, relevant data is manually entered into the Sheriff Office's jail management system. Data reports are pulled from this system on a semi-regular basis, and added to Open Data. C. UPDATE PROCESS This dataset is scheduled to update monthly. D. HOW TO USE THIS DATASET This data can be used to identify trends and patterns in the jail population over time. The date in this dataset is based on the date the suspect was booked into county jail for the arresting incident. The unit of measurement for this dataset is the booking number. A jail booking number is a unique identifier assigned to each individual who is booked into a jail facility. E. RELATED DATASETS • Booking by Age • Bookings by Race • Booking by Male/Female

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.

A. SUMMARY To confirm the completeness of this dataset please contact the Sheriff's Office at sheriff.tech.services@sfgov.org

The dataset provides summary information on individuals booked into the San Francisco City and County Jail since 2012, categorized by race. The table provides a breakdown of the total number of bookings by month and race. The unit of measure is the jail booking number. The data is collected by the Sheriff's Office and includes self-report and assigned data. However, some race categories with small sample sizes are grouped together to reduce the risk of re-identification and protect the privacy of individuals booked into jail.

The booking process refers to the procedure that occurs after an individual has been arrested and is taken into custody. The process begins with the arrest of an individual by law enforcement officers. The arrest can take place on the scene or at a later time if a warrant is issued. Once the individual has been arrested, and statutory law requires incarceration, they would be transported to the jail for booking. The arresting officer will record the reason for the arrest, along with any other relevant information. The sheriff’s deputies will then book the individual into jail, which involves taking their fingerprints, photograph, and recording personal information. The jail will assign a booking number, which is used to identify the individual throughout their time in custody. Once the booking process is complete, the individual will be incarcerated and will remain in custody until they are released per court order.

Disclaimer: The San Francisco Sheriff's Office does not guarantee the accuracy, completeness, or timeliness of the information as the data is subject to change as modifications and updates are completed.

B. HOW THE DATASET IS CREATED When an arrest is presented to the Sheriff’s Office, relevant data is manually entered into the Sheriff Office's jail management system. Data reports are pulled from this system on a semi-regular basis, and added to Open Data.

C. UPDATE PROCESS This dataset is scheduled to update monthly

D. HOW TO USE THIS DATASET This data can be used to identify trends and patterns in the jail population over time. The date in this dataset is based on the date the suspect was booked into county jail for the arresting incident. The unit of measurement for this dataset is the booking number. A jail booking number is a unique identifier assigned to each individual who is booked into a jail facility. It is used to track the individual throughout their time in custody and to link their records to other relevant information, such as court appearances and medical records.

Note that this dataset should be used with the Jail Bookings by Ethnicity dataset for an accurate characterization of the Hispanic or Latin populations.

E. RELATED DATASETS • Bookings by Age • Bookings by Male/Female • Bookings by Ethnicity

Despite the renewed bipartisan policy support for post-secondary correctional education (PSCE) as a pathway to reduce post-release labor market barriers, extant studies often find mixed and inconsistent economic returns, with limited attention to how PSCE interacts with persistent racial discrimination to shape job prospects. Drawing on signaling and social status theories, this study examines whether PSCE credentials, particularly vocational certificates, improve post-release employment outcomes and whether race moderates signaling effects. Through a matched correspondence audit study of 1,502 employers seeking heating, ventilation, and air conditioning (HVAC) workers, this article advances understandings of the signaling value of PSCE in skilled trade labor markets. Results indicate that HVAC credentials improved callback chances for applicants regardless of prison record status, yet this advantage was not adequate for completely overcoming stigma. While HVAC credentials earned during incarceration operated similarly for Black and White men, the additive effects of racial discrimination and prison record stigma created compounded disadvantages for Black formerly incarcerated men. These findings demonstrate both the promise and limitations of PSCE vocational credentials for improving job opportunities and highlight the need for integrated policy solutions that address both the mark of a prison record and racial discrimination in skilled trade labor markets.

These data focus on rates of criminal offending obtained through the use of self-report surveys. Specifically, the study investigates whether two different types of self-report surveys produce different estimates of lambda, an individual's frequency of criminal offending. The surveys, which were administered during personal interviews with inmates in Nebraska prisons, differed in how respondents were asked about their frequency of criminal offending. The more detailed survey asked respondents to indicate their offenses on a month-by-month basis for the reporting period. The less detailed survey only asked respondents to indicate their offending for the entire reporting period. These data also provide information on the relationship between race and offending frequencies, the rates of offending over time and by crime category, and the individual's subjective probability of punishment and offending frequency. The specific crimes targeted in this collection include burglary, business robbery, personal robbery, assault, theft, forgery, fraud, drug dealing, and rape. All respondents were asked questions on criminal history, substance abuse, attitudes about crime and the judicial system, predictions of future criminal behavior, and demographic information, including age, race, education, and marital status.

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.

As of October 2024, the operational capacity of Italian prisons was about 51,100 inmates. However, there were roughly 62,100 prisoners incarcerated in all Italian penal institutions, over 11,000 more than the regulatory capacity. Indeed, most Italian regions were affected by the overpopulation of jails. Prison population in Italy Since the beginning of the twenty-first century, the number of inmates in Italian jails remained rather stable. In the period between 2000 and 2019, the lowest prison population was registered in 2006, whereas the highest number of inmates in custody was reported in 2010. However, the number of detainees in 2020 experienced a decrease. During the coronavirus emergency, certain prisoners were released under supervision in order to reduce overcrowding. Perception of prison overpopulation Italians are aware that the number of inmates in the country’s prisons exceeds the operational capacity. However, in 2018 Italian respondents believed that the penal institutions in their country were more overcrowded than they actually were.

Abstract (en): The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2008. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute. 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.. Offenders in the custody of the United States Bureau of Prisons at year-end of fiscal year 2008. 2014-03-11 AGE variable has been relabeled based on when age was computed.2011-03-08 All parts are being moved to restricted access and will be available only using the restricted access procedures. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics.

In 1980, the National Institute of Justice awarded a grant to the Cornell University College of Human Ecology for the establishment of the Center for the Study of Race, Crime, and Social Policy in Oakland, California. This center mounted a long-term research project that sought to explain the wide variation in crime statistics by race and ethnicity. Using information from eight ethnic communities in Oakland, California, representing working- and middle-class Black, White, Chinese, and Hispanic groups, as well as additional data from Oakland's justice systems and local organizations, the center conducted empirical research to describe the criminalization process and to explore the relationship between race and crime. The differences in observed patterns and levels of crime were analyzed in terms of: (1) the abilities of local ethnic communities to contribute to, resist, neutralize, or otherwise affect the criminalization of its members, (2) the impacts of criminal justice policies on ethnic communities and their members, and (3) the cumulative impacts of criminal justice agency decisions on the processing of individuals in the system. Administrative records data were gathered from two sources, the Alameda County Criminal Oriented Records Production System (CORPUS) (Part 1) and the Oakland District Attorney Legal Information System (DALITE) (Part 2). In addition to collecting administrative data, the researchers also surveyed residents (Part 3), police officers (Part 4), and public defenders and district attorneys (Part 5). The eight study areas included a middle- and low-income pair of census tracts for each of the four racial/ethnic groups: white, Black, Hispanic, and Asian. Part 1, Criminal Oriented Records Production System (CORPUS) Data, contains information on offenders' most serious felony and misdemeanor arrests, dispositions, offense codes, bail arrangements, fines, jail terms, and pleas for both current and prior arrests in Alameda County. Demographic variables include age, sex, race, and marital status. Variables in Part 2, District Attorney Legal Information System (DALITE) Data, include current and prior charges, days from offense to charge, disposition, and arrest, plea agreement conditions, final results from both municipal court and superior court, sentence outcomes, date and outcome of arraignment, disposition, and sentence, number and type of enhancements, numbers of convictions, mistrials, acquittals, insanity pleas, and dismissals, and factors that determined the prison term. For Part 3, Oakland Community Crime Survey Data, researchers interviewed 1,930 Oakland residents from eight communities. Information was gathered from community residents on the quality of schools, shopping, and transportation in their neighborhoods, the neighborhood's racial composition, neighborhood problems, such as noise, abandoned buildings, and drugs, level of crime in the neighborhood, chances of being victimized, how respondents would describe certain types of criminals in terms of age, race, education, and work history, community involvement, crime prevention measures, the performance of the police, judges, and attorneys, victimization experiences, and fear of certain types of crimes. Demographic variables include age, sex, race, and family status. For Part 4, Oakland Police Department Survey Data, Oakland County police officers were asked about why they joined the police force, how they perceived their role, aspects of a good and a bad police officer, why they believed crime was down, and how they would describe certain beats in terms of drug availability, crime rates, socioeconomic status, number of juveniles, potential for violence, residential versus commercial, and degree of danger. Officers were also asked about problems particular neighborhoods were experiencing, strategies for reducing crime, difficulties in doing police work well, and work conditions. Demographic variables include age, sex, race, marital status, level of education, and years on the force. In Part 5, Public Defender/District Attorney Survey Data, public defenders and district attorneys were queried regarding which offenses were increasing most rapidly in Oakland, and they were asked to rank certain offenses in terms of seriousness. Respondents were also asked about the public's influence on criminal justice agencies and on the performance of certain criminal justice agencies. Respondents were presented with a list of crimes and asked how typical these offenses were and what factors influenced their decisions about such cases (e.g., intent, motive, evidence, behavior, prior history, injury or loss, substance abuse, emotional trauma). Other variables measured how often and under what circumstances the public defender and client and the public defender and the district attorney agreed on the case, defendant characteristics in terms of who should not be put on the stand, the effects of Proposition 8, public defender and district attorney plea guidelines, attorney discretion, and advantageous and disadvantageous characteristics of a defendant. Demographic variables include age, sex, race, marital status, religion, years of experience, and area of responsibility.

The Ministry of the Solicitor General annually releases data on the segregation, restrictive confinement, and deaths in custody of inmates in Ontario’s adult correctional system. Data Source: Offender Tracking Information System (OTIS) Segregation is defined in Ontario Regulation 778 as any type of custody where an inmate is in highly restricted conditions for 22 to 24 hours or does not receive a minimum of two hours of meaningful social interaction each day, excluding circumstances of an unscheduled lockdown. A record is created each time an inmate meets the conditions of segregation and closed when the inmate no longer meets those conditions. A break in a segregation placement is defined as occurring when an individual is out of segregation conditions for 24 or more continuous hours. The Ministry of the Solicitor General defines restrictive confinement as any type of confinement that is more restrictive than the general population but less restrictive than segregation. As a result, the ministry is reporting on any case within the fiscal year reporting period where an individual was held in a unit regularly scheduled to be locked down for 17 hours or more per day. This timeframe is considered more restrictive than that of the general population based on an assessment of provincewide lockdown times. Regularly scheduled lockdowns are daily routine times where movement out of a cell is restricted, such as during meal times and overnight. The Ministry of the Solicitor General is committed to providing greater transparency by releasing data on all custodial-related deaths that occurred within the calendar year reporting period. The datasets in this category include information on gender, race, age, religion or spiritual affiliation, and alerts for mental health concerns and suicide risk. To simplify the provision of data, several data tables include information on both individuals in segregation conditions and individuals in restrictive confinement. Due to the differences in the way that the data on segregation conditions and restrictive confinement have been collected, and the differences in the definitions of these concepts, these numbers should not be compared to each other. Some individuals may have both placements in restrictive confinement and segregation conditions, within the reporting period. Therefore, these numbers should not be added together when calculating proportions out of the total. Please refer to https://www.ontario.ca/page/jahn-settlement-data-inmates-ontario for additional information on the data release, including written overviews of the data and disclosure on data collection methods.

Effective October 1, 1994, the state of North Carolina implemented a new structured sentencing law that applied to all felony and misdemeanor crimes (except for driving while impaired) committed on or after October 1, 1994. Under the new structured sentencing law parole was eliminated, and a sentencing commission developed recommended ranges of punishment for offense and offender categories, set priorities for the use of correctional resources, and developed a model to estimate correctional populations. This study sought to investigate sentencing reforms by looking at the effects of structured sentencing on multiple aspects of the adjudication process in North Carolina. A further objective was to determine whether there were differences in the commission of institutional infractions between inmates sentenced to North Carolina prisons under the pre-structured versus structured sentencing laws. Researchers hoped that the results of this study may help North Carolina and jurisdictions around the country (1) anticipate the likely effects of structured sentencing laws, (2) design new laws that might better achieve the jurisdictions' goals, and (3) improve the potential of sentencing legislation in order to enhance public safety in an effective and equitable way. Administrative records data were collected from two sources. First, in order to examine the effects of structured sentencing on the adjudication process in North Carolina, criminal case data were obtained from the North Carolina Administrative Office of the Courts (Parts 1 and 2). The pre-structured sentencing and structured sentencing samples were selected at the case level, and each record in Parts 1 and 2 represents a charged offense processed in either the North Carolina Superior or District Court. Second, inmate records data were collected from administrative records provided by the North Carolina Department of Correction (Part 3). These data were used to compare the involvement in infractions of inmates sentenced under both pre-structured and structured sentencing. The data for Part 3 focused on inmates entering the prison system between June 1, 1995, and January 31, 1998. Variables for Parts 1 and 2 include type of charge, charged offense date, method of disposition (e.g., dismissal, withdrawal, jury trial), defendant's plea, verdict for the offense, and whether the offense was processed through the North Carolina Superior or District Court. Structured sentencing offense class and modified Uniform Crime Reporting code for both charged and convicted offenses are presented for Parts 1 and 2. There are also county, prosecutorial district, and defendant episode identifiers in both parts. Variables related to defendant episodes include types of offenses within episode, total number of charges and convictions, whether all charges were dismissed, whether any felony charge resulted in a jury trial, and the adjudication time for all charges. Demographic variables for Parts 1 and 2 include the defendant's age, race, and gender. Part 3 variables include the date of prison admission, sentence type, number of prior incarcerations, number of years served during prior incarcerations, maximum sentence length for current incarceration, jail credit in years, count of all infractions during current and prior incarcerations, reason for incarceration, infraction rate, the risk for alcohol and drug dependency based on alcohol and chemical dependency screening scores, and the number of assault, drug/alcohol, profanity/disobedience, work absence, and money/property infractions during an inmate's current incarceration. Demographic variables for Part 3 include race, gender, and age at the time of each inmate's prison admission.

There were almost 700 thousand slaves in the US in 1790, which equated to approximately 18 percent of the total population, or roughly one in every six people. By 1860, the final census taken before the American Civil War, there were four million slaves in the South, compared with less than 0.5 million free African Americans in all of the US. Of the 4.4 million African Americans in the US before the war, almost four million of these people were held as slaves; meaning that for all African Americans living in the US in 1860, there was an 89 percent* chance that they lived in slavery. A brief history Trans-Atlantic slavery began in the early sixteenth century, when the Portuguese and Spanish forcefully brought captured African slaves to the New World, in order to work for them. The British Empire introduced slavery to North America on a large scale, and the economy of the British colonies there depended on slave labor, particularly regarding cotton, sugar and tobacco output. In the seventeenth and eighteenth century the number of slaves being brought to the Americas increased exponentially, and at the time of American independence it was legal in all thirteen colonies. Although slavery became increasingly prohibited in the north, the number of slaves remained high during this time as they were simply relocated or sold from the north to the south. It is also important to remember that the children of slaves were also viewed as property, and (apart from some very rare cases) were born into a life of slavery. Abolition and the American Civil War In the years that followed independence, the Northern States began gradually prohibiting slavery, and it was officially abolished there by 1805, and the importation of slave labor was prohibited nationwide from 1808 (although both still existed in practice after this). Business owners in the Southern States however depended on slave labor in order to meet the demand of their rapidly expanding industries, and the issue of slavery continued to polarize American society in the decades to come. This culminated in the election of President Abraham Lincoln in 1860, who promised to prohibit slavery in the newly acquired territories to the west, leading to the American Civil War from 1861 to 1865. Although the Confederacy (south) were victorious in much of the early stages of the war, the strength in numbers of the northern states (including many free, black men), eventually resulted in a victory for the Union (north), and the nationwide abolishment of slavery with the Thirteenth Amendment in 1865. Legacy In total, an estimated twelve to thirteen million Africans were transported to the Americas as slaves, and this does not include the high number who did not survive the journey (which was as high as 23 percent in some years). In the 150 years since the abolishment of slavery in the US, the African-American community have continuously campaigned for equal rights and opportunities that were not afforded to them along with freedom. The most prominent themes have been the Civil Rights Movement, voter suppression, mass incarceration and the relationship between the police and the African-American community has taken the spotlight in recent years.

The purpose of this data collection was to measure the validity or accuracy of four recidivism prediction instruments: the INSLAW, RAND, SFS81, and CGR scales. These scales estimate the probability that criminals will commit subsequent crimes quickly, that individuals will commit crime frequently, that inmates who are eligible for release on parole will commit subsequent crimes, and that defendants awaiting trial will commit crimes while on pretrial arrest or detention. The investigators used longitudinal data from five existing independent studies to assess the validity of the four predictive measures in question. The first data file was originally collected by the Vera Institute of Justice in New York City and was derived from an experimental evaluation of a jobs training program called the Alternative Youth Employment Strategies Project implemented in Albuquerque, New Mexico, Miami, Florida, and New York City, New York. The second file contains data from a RAND Corporation study, EFFECTS OF PRISON VERSUS PROBATION IN CALIFORNIA, 1980-1982 (ICPSR 8700), from offenders in Alameda and Los Angeles counties, California. Parts 3 through 5 pertain to serious juvenile offenders who were incarcerated during the 1960s and 1970s in three institutions of the California Youth Authority. A portion of the original data for these parts was taken from EARLY IDENTIFICATION OF THE CHRONIC OFFENDER, 1978-1980: CALIFORNIA. All files present demographic and socioeconomic variables such as birth information, race and ethnicity, education background, work and military experience, and criminal history, including involvement in criminal activities, drug addiction, and incarceration episodes. From the variables in each data file, standard variables across all data files were constructed. Constructed variables included those on background (such as drug use, arrest, conviction, employment, and education history), which were used to construct the four predictive scales, and follow-up variables concerning arrest and incarceration history. Scores on the four predictive scales were estimated.

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.

Abstract (en): This survey of inmates in five California prisons was conducted by the RAND Corporation with a grant from the National Institute of Justice. Researchers distributed an anonymous self-administered questionnaire to groups of 10-20 inmates at a time. Using the self-report technique, the survey obtained detailed information about the crimes committed by these prisoners prior to their incarceration. Variables were calculated to examine the characteristics of repeatedly arrested or convicted offenders (recidivists) as well as offenders reporting the greatest number of serious crimes (habitual criminals). The variables include crimes committed leading to incarceration, rates of criminal activity, and social-psychological scales for analyzing motivations to commit crimes, as well as self-reports of age, race, education, marital status, employment, income, and drug use. 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: Checked for undocumented or out-of-range codes.. Male prisoners who were incarcerated in five California state adult correctional institutions in July and August of 1976. 2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions. Funding insitution(s): United States Department of Justice. Office of Justice Programs. National Institute of Justice (83-IJ-CX-0006).