--- ### Context This dataset contains the complete detail about the Prison and various characteristics of inmates. This will help to understand better about prison system in India. ### Content 1. Details of Jail wise population of prison inmates 1. Details about the list of jails in India at the end of year 2015. 1. Jail category wise population of inmates. 1. Capacity of jails by inmate population. 1. Age group, nationality and gender wise population of inmates. 1. Religion and gender wise population of inmates. 1. Caste and gender wise population of inmates. 1. Education standards of inmates. 1. Domicile of inmates. 1. Incidence of recidivism. 1. Rehabilitation of prisoners. 1. Distribution of sentence periods of convicts in various jails by sex and age-groups. 1. Details of under trial prisoners by the type of IPC (Indian Penal Code) offences. 1. Details of convicts by the type of IPC (Indian Penal Code) offences. 1. Details of SLL (special & local law) Crime headwise distribution of inmates who convicted 1. Details of SLL (special & local law) Crime head wise distribution of inmates under trial 1. Details of educational facilities provided to prisoners. 1. Details of Jail breaks, group clashes and firing in jail (Tranquility). 1. Details of wages per day to convicts. 1. Details of Prison inmates trained under different vocational training. 1. Details of capital punishment (death sentence) and life imprisonment. 1. Details of prison inmates escaped. 1. Details of prison inmates released. 1. Details of Strength of officials 1. Details of Total Budget and Actual Expenditure during the year 2015-16. 1. Details of Budget 1. Details of Expenditure 1. Details of Expenditure on inmates 1. Details of Inmates suffering from mental ilness 1. Details of Period of detention of undertrials 1. Details of Number of women prisoners with children 1. Details of Details of inmates parole during the year 1. Details of Value of goods produced by inmates 1. Details of Number of vehicles available 1. Details of Training of Jail Officers 1. Details of Movements outside jail premises 1. Details of Details of electronic equipment used in prison ### Inspiration There are many questions about Indian prison with this dataset. Some of the interesting questions are 1. Percentage of jails over crowded. Is there any change in percentage over time? 1. How many percentage of inmates re-arrested? 1. Which state/u.t pay more wages to the inmates? 1. Which state/u.t has more capital punishment/life imprisonment inmates? 1. Inmates gender ratio per state ### Acknowledgements National Crime Records Bureau (NCRB), Govt of India has shared this [dataset](https://data.gov.in/dataset-group-name/prison-statistics) under [Govt. Open Data License - India](https://data.gov.in/government-open-data-license-india). NCRB has also shared prison data on their [website](http://ncrb.nic.in/StatPublications/PSI/PrevPublications.htm). ---

This census provides information on county and municipal jails facilities in the United States and their administration. For all jails, the data include number of prisoners and their reason for being held, age and sex of prisoners, maximum sentence that could be served in the facility, facility capacity and age, types of security available, and operating expenditures. For jails in counties and municipalities with populations of 25,000 or more, data are supplied on quarterly jail population, age of cells, and availability of service facilities and programs for inmates.

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 1999 Census of Jails is the seventh in a series of data collection efforts aimed at studying the nation's locally administered jails. Previous censuses were conducted in 1970, 1972, 1978, 1983, 1988, and 1993. The 1999 census enumerated 3,365 locally administered confinement facilities that held inmates beyond arraignment and were staffed by municipal or county employees. Among these were 47 privately operated jails under contract for local governments and 42 regional jails that were operated for two or more jail authorities. In addition, the census identified 11 facilities maintained by the Federal Bureau of Prisons that functioned as jails. The nationwide total of the number of jails in operation on June 30, 1999, was 3,376. For purposes of this data collection, a local jail was defined as a locally operated adult detention facility that receives individuals pending arraignment and holds them awaiting trial, conviction, or sentencing, readmits probation, parole, and bail-bond violators and absconders, temporarily detains juveniles pending transfer to juvenile authorities, holds mentally ill persons pending their movement to appropriate health facilities, holds individuals for the military, for protective custody, for contempt, and for the courts as witnesses, releases convicted inmates to the community upon completion of sentence, transfers inmates to federal, state, or other authorities, houses inmates for federal, state, or other authorities because of crowding of their facilities, relinquishes custody of temporary detainees to juvenile and medical authorities, operates community-based programs with day-reporting, home detention, electronic monitoring, or other types of supervision, and holds inmates sentenced to short terms. Variables include information on jail population by legal status, age and sex of prisoners, maximum sentence, admissions and releases, available services and programs, structure and capacity, facility age and use of space, expenditure, employment, staff information, and health issues, which include statistics on drugs, AIDS, and tuberculosis.

The purpose of this collection was to measure the extent to which the Prisoner Management Classification (PMC) system in Washington state improved overall operations of prison facilities and reduced safety risks to inmates and staff. Four primary issues were addressed: (1) To what extent the PMC reduces rates of assaults on staff and inmates, (2) To what extent the PMC reduces rates of other serious misconduct, (3) To what extent the PMC increases rates of inmate participation in work or vocational programs, and (4) To what extent the PMC enhances staff job satisfaction, morale, and staff performance. Information is included on outcome variables against which comparisons between the experimental and control groups can be made. For each correctional facility, figures were collected for the number of staff-inmate assaults, number of inmate-inmate assaults, number of suicides and suicide attempts, number of escapes and escape attempts, number of "serious" disciplinary incidents, number of total staff, number of inmates, number of security staff vacancies, rated capacity of the facility, number of staff transfers and reasons, and number of inmates involved in educational, vocational, and work programs. Demographic variables include date of birth, sex, and race. Additional information concerns the family structure of the inmates and conditions surrounding the inmates' lives prior to entering prison.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_1f0bc0a09aee736864d18d2e184b70eb/view

The National Jail Census was conducted by the United States Bureau of the Census for the Bureau of Justice Statistics. The census was taken of all locally administered county and municipal jails with the authority to hold prisoners for more than 48 hours. Data are presented for 3,338 jails in 45 states. Excluded are Connecticut, Delaware, Hawaii, Rhode Island, and Vermont. Information includes jail population by legal status, age and sex of prisoners, maximum sentence, admissions and releases, available services, structure and capacity, expenditure, and employment.

The National Jail Census was conducted in early 1978 by the United States Census Bureau for the Bureau of Justice Statistics. The census was taken of all locally administered county and municipal jails with the authority to hold prisoners for more than 48 hours. Data are presented for jails in 45 states. Excluded are Connecticut, Delaware, Hawaii, Rhode Island, and Vermont. Information includes jail population by legal status, age and sex of prisoners, maximum sentence, admissions and releases, available services, structure and capacity, expenditure, and employment.

Content

Represents inmates under custody in NYS Department of Corrections and Community Supervision as of March 31 of the snapshot year. Includes data about admission type, county, gender, age, race/ethnicity, crime, and facility.

Context

This is a dataset hosted by the State of New York. The state has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York State using Kaggle and all of the data sources available through the State of New York organization page!

• Update Frequency: This dataset is updated annually.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Mitch Lensink on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

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.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_08433c469bbe2768daf9e2b86217991d/view

Dataset from Central Narcotics Bureau. For more information, visit https://data.gov.sg/datasets/d_9ced8376868d18b9cd53a3a0a806d318/view

The 2019 Census of State and Federal Adult Correctional Facilities (CCF) was the ninth enumeration of state institutions and the sixth enumeration of federal institutions sponsored by the Bureau of Justice Statistics and its predecessors. Earlier censuses were completed in 1979 (ICPSR 7852), 1984 (ICPSR 8444), 1990 (ICPSR 9908), 1995 (ICPSR 6953), 2000 (ICPSR 4021), 2005 (ICPSR 24642), and 2012 (ICPSR 37294). The 2019 CCF consisted of two data collection instruments - one for confinement facilities and one for community-based facilities. For each facility, information was provided on facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, race/ethnicity, special populations, and holding authority; number of walkaways occurring over a one-year period; and educational and other special programs offered to prisoners. Additional information was collected from confinement facilities, including physical security level; housing for special populations; capacity; court orders for specific conditions; one-day count of correctional staff by payroll status and sex; one-day count of security staff by sex and race/ethnicity; assaults and incidents caused by prisoners; number of escapes occurring over a one-year period; and work assignments available to prisoners. Late in the data collection to avoid complete nonresponse from facilities, BJS offered the option of providing critical data elements from the two data collection instruments. These elements included facility operator; sex of prisoners authorized to be housed by facility; facility functions; percentage of prisoners authorized to leave the facility; one-day counts of prisoners by sex, and holding authority. Physical security level was an additional critical data element for confinement facilities. The census counted prisoners held in the facilities, a custody count. Some prisoners who are held in the custody of one jurisdiction may be under the authority of a different jurisdiction. The custody count is distinct from a count of prisoners under a correctional authority's jurisdiction, which includes all prisoners over whom a correctional authority exercises control, regardless of where the prisoner is housed. A jurisdictional count is more inclusive than a prison custody count and includes state and federal prisoners housed in local jails or other non-correctional facilities.

Dataset from Central Narcotics Bureau. For more information, visit https://data.gov.sg/datasets/d_44c6b6dabcde1025724cab86b7d1672e/view

Dataset from Singapore Prison Service. For more information, visit https://data.gov.sg/datasets/d_1d6394f2721fedcf0277e054c34e22be/view

Contains national information on prisoners who were in custody on 30 June each year. The statistics are derived from information collected by the ABS from corrective services agencies in each state and territory. Details are provided on the number of people in correctional institutions (including people on remand), imprisonment rates, most serious offence and sentence length. Information is also presented on prisoner characteristics (age, sex, Indigenous status) and on the type of prisoner (all prisoners, sentenced prisoners, and unsentenced prisoners (remandees).

The purpose of this study was to develop and validate a reliable and accurate method for measuring the effectiveness of offender classification systems to improve the management of correctional facilities. In the early 1980s, the state of Hawaii began classifying its prisoners with a newly developed Federal Bureau of Prisons classification instrument. This study was designed to develop a method to evaluate this form. Two prediction models were used. The first, initial classification, used the sum of four variables to arrive at a security score, which was taken to be predictive of violence. The second, reclassification, used the sum of seven different variables to obtain a custody total, which was then used as a major determinant of reclassification. Two groups of inmates were used: inmates who had committed infractions and inmates with no reported infractions. Research variables include (a) initial classification: offense (severity), expected length of incarceration (sentence), type of prior commitments, and history of violence, and (b) reclassification: percentage of time served, involvement with drugs/alcohol, mental/psychological stability, most serious disciplinary report, frequency of disciplinary reports, responsibility that the inmate demonstrated, and family/community ties. In addition, the collection supplies information on race and sex of inmates, sentence limitation, history of escapes or attempts, previous infractions, entry, reclassification, and termination dates (month and year), and custody level. There are demographic variables for sex and race. The unit of observation is the inmate.

Dataset from Singapore Prison Service. For more information, visit https://data.gov.sg/datasets/d_76b78d3f0b50ea8ba6c8c482e516d3b2/view

Dataset from Singapore Prison Service. For more information, visit https://data.gov.sg/datasets/d_bdd625091e115bd9c8d8d3128147a00b/view

The Iowa Sex Offender Registry became law on July 1, 1995 and is found in Chapter 692A Code of Iowa. On or after July 1, 1995, an individual who has been convicted or adjudicated of a criminal offense against a minor, sexual exploitation, or a sexually violent crime or who was on probation, parole, or work release status, or who was incarcerated on or after July 1, 1995 is required to register. Registration does include individuals that have received a deferred sentence or deferred judgments and can include convictions from other jurisdictions such as other states and/or federal convictions. The information on this website is provided from the Iowa Sex Offender Registry to the public pursuant to Iowa Code chapter 692A.