46 datasets found
  1. d

    The Marshall Project: COVID Cases in Prisons

    • data.world
    csv, zip
    Updated Apr 6, 2023
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    The Associated Press (2023). The Marshall Project: COVID Cases in Prisons [Dataset]. https://data.world/associatedpress/marshall-project-covid-cases-in-prisons
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    csv, zipAvailable download formats
    Dataset updated
    Apr 6, 2023
    Authors
    The Associated Press
    Time period covered
    Jul 31, 2019 - Aug 1, 2021
    Description

    Overview

    The Marshall Project, the nonprofit investigative newsroom dedicated to the U.S. criminal justice system, has partnered with The Associated Press to compile data on the prevalence of COVID-19 infection in prisons across the country. The Associated Press is sharing this data as the most comprehensive current national source of COVID-19 outbreaks in state and federal prisons.

    Lawyers, criminal justice reform advocates and families of the incarcerated have worried about what was happening in prisons across the nation as coronavirus began to take hold in the communities outside. Data collected by The Marshall Project and AP shows that hundreds of thousands of prisoners, workers, correctional officers and staff have caught the illness as prisons became the center of some of the country’s largest outbreaks. And thousands of people — most of them incarcerated — have died.

    In December, as COVID-19 cases spiked across the U.S., the news organizations also shared cumulative rates of infection among prison populations, to better gauge the total effects of the pandemic on prison populations. The analysis found that by mid-December, one in five state and federal prisoners in the United States had tested positive for the coronavirus -- a rate more than four times higher than the general population.

    This data, which is updated weekly, is an effort to track how those people have been affected and where the crisis has hit the hardest.

    Methodology and Caveats

    The data tracks the number of COVID-19 tests administered to people incarcerated in all state and federal prisons, as well as the staff in those facilities. It is collected on a weekly basis by Marshall Project and AP reporters who contact each prison agency directly and verify published figures with officials.

    Each week, the reporters ask every prison agency for the total number of coronavirus tests administered to its staff members and prisoners, the cumulative number who tested positive among staff and prisoners, and the numbers of deaths for each group.

    The time series data is aggregated to the system level; there is one record for each prison agency on each date of collection. Not all departments could provide data for the exact date requested, and the data indicates the date for the figures.

    To estimate the rate of infection among prisoners, we collected population data for each prison system before the pandemic, roughly in mid-March, in April, June, July, August, September and October. Beginning the week of July 28, we updated all prisoner population numbers, reflecting the number of incarcerated adults in state or federal prisons. Prior to that, population figures may have included additional populations, such as prisoners housed in other facilities, which were not captured in our COVID-19 data. In states with unified prison and jail systems, we include both detainees awaiting trial and sentenced prisoners.

    To estimate the rate of infection among prison employees, we collected staffing numbers for each system. Where current data was not publicly available, we acquired other numbers through our reporting, including calling agencies or from state budget documents. In six states, we were unable to find recent staffing figures: Alaska, Hawaii, Kentucky, Maryland, Montana, Utah.

    To calculate the cumulative COVID-19 impact on prisoner and prison worker populations, we aggregated prisoner and staff COVID case and death data up through Dec. 15. Because population snapshots do not account for movement in and out of prisons since March, and because many systems have significantly slowed the number of new people being sent to prison, it’s difficult to estimate the total number of people who have been held in a state system since March. To be conservative, we calculated our rates of infection using the largest prisoner population snapshots we had during this time period.

    As with all COVID-19 data, our understanding of the spread and impact of the virus is limited by the availability of testing. Epidemiology and public health experts say that aside from a few states that have recently begun aggressively testing in prisons, it is likely that there are more cases of COVID-19 circulating undetected in facilities. Sixteen prison systems, including the Federal Bureau of Prisons, would not release information about how many prisoners they are testing.

    Corrections departments in Indiana, Kansas, Montana, North Dakota and Wisconsin report coronavirus testing and case data for juvenile facilities; West Virginia reports figures for juvenile facilities and jails. For consistency of comparison with other state prison systems, we removed those facilities from our data that had been included prior to July 28. For these states we have also removed staff data. Similarly, Pennsylvania’s coronavirus data includes testing and cases for those who have been released on parole. We removed these tests and cases for prisoners from the data prior to July 28. The staff cases remain.

    About the Data

    There are four tables in this data:

    • covid_prison_cases.csv contains weekly time series data on tests, infections and deaths in prisons. The first dates in the table are on March 26. Any questions that a prison agency could not or would not answer are left blank.

    • prison_populations.csv contains snapshots of the population of people incarcerated in each of these prison systems for whom data on COVID testing and cases are available. This varies by state and may not always be the entire number of people incarcerated in each system. In some states, it may include other populations, such as those on parole or held in state-run jails. This data is primarily for use in calculating rates of testing and infection, and we would not recommend using these numbers to compare the change in how many people are being held in each prison system.

    • staff_populations.csv contains a one-time, recent snapshot of the headcount of workers for each prison agency, collected as close to April 15 as possible.

    • covid_prison_rates.csv contains the rates of cases and deaths for prisoners. There is one row for every state and federal prison system and an additional row with the National totals.

    Queries

    The Associated Press and The Marshall Project have created several queries to help you use this data:

    Get your state's prison COVID data: Provides each week's data from just your state and calculates a cases-per-100000-prisoners rate, a deaths-per-100000-prisoners rate, a cases-per-100000-workers rate and a deaths-per-100000-workers rate here

    Rank all systems' most recent data by cases per 100,000 prisoners here

    Find what percentage of your state's total cases and deaths -- as reported by Johns Hopkins University -- occurred within the prison system here

    Attribution

    In stories, attribute this data to: “According to an analysis of state prison cases by The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system, and The Associated Press.”

    Contributors

    Many reporters and editors at The Marshall Project and The Associated Press contributed to this data, including: Katie Park, Tom Meagher, Weihua Li, Gabe Isman, Cary Aspinwall, Keri Blakinger, Jake Bleiberg, Andrew R. Calderón, Maurice Chammah, Andrew DeMillo, Eli Hager, Jamiles Lartey, Claudia Lauer, Nicole Lewis, Humera Lodhi, Colleen Long, Joseph Neff, Michelle Pitcher, Alysia Santo, Beth Schwartzapfel, Damini Sharma, Colleen Slevin, Christie Thompson, Abbie VanSickle, Adria Watson, Andrew Welsh-Huggins.

    Questions

    If you have questions about the data, please email The Marshall Project at info+covidtracker@themarshallproject.org or file a Github issue.

    To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

  2. National Prisoner Statistics, [United States], 1978-2022

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated Jan 10, 2024
    + more versions
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    United States. Bureau of Justice Statistics (2024). National Prisoner Statistics, [United States], 1978-2022 [Dataset]. http://doi.org/10.3886/ICPSR38871.v1
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    r, delimited, spss, sas, stata, asciiAvailable download formats
    Dataset updated
    Jan 10, 2024
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Justice Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38871/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38871/terms

    Time period covered
    1978 - 2022
    Area covered
    United States
    Description

    The National Prisoner Statistics (NPS) data collection began in 1926 in response to a congressional mandate to gather information on persons incarcerated in state and federal prisons. Originally under the auspices of the U.S. Census Bureau, the collection moved to the Bureau of Prisons in 1950, and then in 1971 to the National Criminal Justice Information and Statistics Service, the precursor to the Bureau of Justice Statistics (BJS) which was established in 1979. From 1979 to 2013, the Census Bureau was the NPS data collection agent. In 2014, the collection was competitively bid in conjunction with the National Corrections Reporting Program (NCRP), since many of the respondents for NPS and NCRP are the same. The contract was awarded to Abt Associates, Inc. The NPS is administered to 51 respondents. Before 2001, the District of Columbia was also a respondent, but responsibility for housing the District of Columbia's sentenced prisoners was transferred to the Federal Bureau of Prisons, and by yearend 2001 the District of Columbia no longer operated a prison system. The NPS provides an enumeration of persons in state and federal prisons and collects data on key characteristics of the nation's prison population. NPS has been adapted over time to keep pace with the changing information needs of the public, researchers, and federal, state, and local governments.

  3. Indian Prison Statistics

    • kaggle.com
    Updated Sep 5, 2017
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    Rajanand Ilangovan (2017). Indian Prison Statistics [Dataset]. https://www.kaggle.com/rajanand/prison-in-india/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 5, 2017
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Rajanand Ilangovan
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    India
    Description
    "https://link.rajanand.org/sql-challenges" target="_blank"> https://link.rajanand.org/banner-01" alt="SQL Data Challenges" style="width: 700px; height: 120px">
    --- ### 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). ---
    "https://link.rajanand.org/sql-challenges" target="_blank"> https://link.rajanand.org/banner-02" alt="SQL Data Challenges" style="width: 700px; height: 120px">
  4. Mortality in Correctional Institutions: State Prisons, 2001-2017

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Mortality in Correctional Institutions: State Prisons, 2001-2017 [Dataset]. https://catalog.data.gov/dataset/mortality-in-correctional-institutions-state-prisons-2001-2017-5868a
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    Mortality in Correctional Institutions (MCI) (formerly, the Deaths in Custody Reporting Program (DCRP)), is an annual data collection conducted by the Bureau of Justice Statistics (BJS). The MCI collection began in 2000 under the Death in Custody Reporting Act of 2000 (P.L. 106-297). It is the only national statistical collection that obtains detailed information about deaths in adult correctional facilities. MCI collects data on persons dying in state prisons, local jails and in the process of arrest. Each collection is a separate subcollection, but each is under the umbrella of the MCI collection. This deals with the prison subcollection, which has a prison death file. The prison portion of Mortality in Correctional Institutions began in 2001 after the passage of the Deaths in Custody Reporting Act of 2000 in October of 2000. The prison component of MCI collects data on inmate deaths occurring in the 50 state departments of corrections while inmates are in the physical custody of prison officials.

  5. Z

    Mapping environmental injustices within the U.S. prison system: a nationwide...

    • data.niaid.nih.gov
    Updated Sep 2, 2023
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    Caitlin Mothes (2023). Mapping environmental injustices within the U.S. prison system: a nationwide dataset [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8306891
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    Dataset updated
    Sep 2, 2023
    Dataset provided by
    Carrie Chennault
    Caitlin Mothes
    Devin Hunt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This open-access geospatial dataset (downloadable in csv or shapefile format) contains a total of 11 environmental indicators calculated for 1865 U.S. prisons. This consists of all active state- and federally-operated prisons according to the Homeland Infrastructure Foundation-Level Data (HIFLD), last updated June 2022. This dataset includes both raw values and percentiles for each indicator. Percentiles denote a way to rank prisons among each other, where the number represents the percentage of prisons that are equal to or have a lower ranking than that prison. Higher percentile values indicate higher vulnerability to that specific environmental burden compared to all the other prisons. Full descriptions of how each indicator was calculated and the datasets used can be found here: https://github.com/GeospatialCentroid/NASA-prison-EJ/blob/main/doc/indicator_metadata.md.

    From these raw indicator values and percentiles, we also developed three individual component scores to summarize similar indicators, and to then create a single vulnerability index (methods based on other EJ screening tools such as Colorado Enviroscreen, CalEnviroScreen and EPA’s EJ Screen). The three component scores include climate vulnerability, environmental exposures and environmental effects. Climate vulnerability factors reflect climate change risks that have been associated with health impacts and includes flood risk, wildfire risk, heat exposure and canopy cover indicators. Environmental exposures reflect variables of different types of pollution people may come into contact with (but not a real-time exposure to pollution) and includes ozone, particulate matter (PM 2.5), traffic proximity and pesticide use. Environmental effects indicators are based on the proximity of toxic chemical facilities and includes proximity to risk management plan (RMP) facilities, National Priority List (NPL)/Superfund facilities, and hazardous waste facilities. Component scores were calculated by taking the geometric mean of the indicator percentiles. Using the geometric mean was most appropriate for our dataset since many values may be related (e.g., canopy cover and temperature are known to be correlated).

    To calculate a final, standardized vulnerability score to compare overall environmental burdens at prisons across the U.S., we took the average of each component score and then converted those values to a percentile rank. While this index only compares environmental burdens among prisons and is not comparable to non-prison sites/communities, it will be able to heighten awareness of prisons most vulnerable to negative environmental impacts at county, state and national scales. As an open-access dataset it also provides new opportunities for other researchers, journalists, activists, government officials and others to further analyze the data for their needs and make comparisons between prisons and other communities. This is made even easier as we produced the methodology for this project as an open-source code base so that others can apply the code to calculate individual indicators for any spatial boundaries of interest. The codebase can be found on GitHub (https://github.com/GeospatialCentroid/NASA-prison-EJ) and is also published via Zenodo (https://zenodo.org/record/8306856).

  6. d

    Correctional Institutions

    • catalog.data.gov
    • nconemap.gov
    • +3more
    Updated Jan 31, 2025
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    TechniGraphics, Inc. (2025). Correctional Institutions [Dataset]. https://catalog.data.gov/dataset/correctional-institutions
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    TechniGraphics, Inc.
    Description

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; Bureau of Alcohol, Tobacco, Firearms and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by sin

  7. r

    Correctional Institutions

    • rigis.org
    • hub.arcgis.com
    Updated Mar 15, 2010
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    Environmental Data Center (2010). Correctional Institutions [Dataset]. https://www.rigis.org/datasets/correctional-institutions/api
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    Dataset updated
    Mar 15, 2010
    Dataset authored and provided by
    Environmental Data Center
    Area covered
    Description

    The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; Bureau of Alcohol, Tobacco, Firearms and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 05/03/2006 and the newest record dates from 10/19/2009.

    Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. A threat to cause the mass release of prisoners by an outside terrorist group has been identified. Steps need to be taken to provide extra security at the targeted prisons. 2. Massive civil unrest has resulted in a large number of arrests. Appropriate space is needed outside of the immediate area to house the arrested individuals. 3. Massive civil unrest has resulted in a large number of arrests. A "holding camp" has been established to hold those arrested. Trained security guards are needed to staff the holding camp. 4. A disaster has caused the need for an emergency labor force (e.g., sandbagging during a flood) and prisoners may fill that need. 5. Inmates may need to be evacuated, or appropriate steps may need to be taken at a prison to protect the inmates and to ensure that a disaster does not present an opportunity for escape.

  8. d

    People Released to Philadelphia from Prison & Jail

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Mar 31, 2025
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    City of Philadelphia (2025). People Released to Philadelphia from Prison & Jail [Dataset]. https://catalog.data.gov/dataset/people-released-to-philadelphia-from-prison-jail-0cd84
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    Dataset updated
    Mar 31, 2025
    Dataset provided by
    City of Philadelphia
    Area covered
    Philadelphia
    Description

    This dataset includes people released to Philadelphia from the Philadelphia Department of Prisons (PDP) and the Pennsylvania Department of Correction (PA DOC). Individual-level data for releases from Federal (BOP) incarceration was not available, and makes up less than 2% of people released to Philadelphia in the year analyzed. The dataset also only includes people released to Philadelphia who have been charged with a criminal non-summary type offense in the Philadelphia adult criminal justice system.

  9. Data on Inmates in Ontario

    • open.canada.ca
    • datasets.ai
    • +2more
    csv, docx, html, xlsx
    Updated Jul 23, 2025
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    Government of Ontario (2025). Data on Inmates in Ontario [Dataset]. https://open.canada.ca/data/dataset/09f7fc65-d3bb-4ca8-8b84-1cdc3ef73c36
    Explore at:
    csv, html, docx, xlsxAvailable download formats
    Dataset updated
    Jul 23, 2025
    Dataset provided by
    Government of Ontariohttps://www.ontario.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Time period covered
    Jan 1, 2022 - Mar 31, 2024
    Area covered
    Ontario
    Description

    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.

  10. c

    HSIP Correctional Institutions in New Mexico

    • s.cnmilf.com
    • gstore.unm.edu
    • +1more
    Updated Dec 2, 2020
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    (Point of Contact) (2020). HSIP Correctional Institutions in New Mexico [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/hsip-correctional-institutions-in-new-mexico
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    Dataset updated
    Dec 2, 2020
    Dataset provided by
    (Point of Contact)
    Area covered
    New Mexico
    Description

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or _location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; Bureau of Alcohol, Tobacco, Firearms and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 12/27/2004 and the newest record dates from 09/08/2009

  11. Data from: THE RELEVANCY OF MASSIVE HEALTH EDUCATION IN THE BRAZILIAN PRISON...

    • zenodo.org
    csv, pdf
    Updated Jul 16, 2024
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    Janaína L. R. da S. Valentim; Janaína L. R. da S. Valentim; Sara Dias-Trindade; Sara Dias-Trindade; Eloiza da S. G. Oliveira; Eloiza da S. G. Oliveira; José A. M. Moreira; José A. M. Moreira; Felipe Fernandes; Felipe Fernandes; Manoel Honorio Romão; Manoel Honorio Romão; Philippi S. G. de Morais; Philippi S. G. de Morais; Alexandre R. Caitano; Alexandre R. Caitano; Aline P. Dias; Aline P. Dias; Carlos A. P. Oliveira; Carlos A. P. Oliveira; Karilany D. Coutinho; Karilany D. Coutinho; Ricardo B. Ceccim; Ricardo B. Ceccim; Ricardo A. de M. Valentim; Ricardo A. de M. Valentim (2024). THE RELEVANCY OF MASSIVE HEALTH EDUCATION IN THE BRAZILIAN PRISON SYSTEM: THE COURSE "HEALTH CARE FOR PEOPLE DEPRIVED OF FREEDOM" AND ITS IMPACTS [Dataset]. http://doi.org/10.5281/zenodo.6499752
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    csv, pdfAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Janaína L. R. da S. Valentim; Janaína L. R. da S. Valentim; Sara Dias-Trindade; Sara Dias-Trindade; Eloiza da S. G. Oliveira; Eloiza da S. G. Oliveira; José A. M. Moreira; José A. M. Moreira; Felipe Fernandes; Felipe Fernandes; Manoel Honorio Romão; Manoel Honorio Romão; Philippi S. G. de Morais; Philippi S. G. de Morais; Alexandre R. Caitano; Alexandre R. Caitano; Aline P. Dias; Aline P. Dias; Carlos A. P. Oliveira; Carlos A. P. Oliveira; Karilany D. Coutinho; Karilany D. Coutinho; Ricardo B. Ceccim; Ricardo B. Ceccim; Ricardo A. de M. Valentim; Ricardo A. de M. Valentim
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dataset name: asppl_dataset_v2.csv

    Version: 2.0

    Dataset period: 06/07/2018 - 01/14/2022

    Dataset Characteristics: Multivalued

    Number of Instances: 8118

    Number of Attributes: 9

    Missing Values: Yes

    Area(s): Health and education

    Sources:

    • Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2022a);

    • Brazilian Occupational Classification (CBO) (Brasil, 2022b);

    • National Registry of Health Establishments (CNES) (Brasil, 2022c);

    • Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2022e).

    Description: The data contained in the asppl_dataset_v2.csv dataset (see Table 1) originates from participants of the technology-based educational course “Health Care for People Deprived of Freedom.” The course is available on the AVASUS (Brasil, 2022a). This dataset provides elementary data for analyzing the course’s impact and reach and the profile of its participants. In addition, it brings an update of the data presented in work by Valentim et al. (2021).

    Table 1: Description of AVASUS dataset features.

    Attributes

    Description

    datatype

    Value

    gender

    Gender of the course participant.

    Categorical.

    Feminino / Masculino / Não Informado. (In English, Female, Male or Uninformed)

    course_progress

    Percentage of completion of the course.

    Numerical.

    Range from 0 to 100.

    course_evaluation

    A score given to the course by the participant.

    Numerical.

    0, 1, 2, 3, 4, 5 or NaN.

    evaluation_commentary

    Comment made by the participant about the course.

    Categorical.

    Free text or NaN.

    region

    Brazilian region in which the participant resides.

    Categorical.

    Brazilian region according to IBGE: Norte, Nordeste, Centro-Oeste, Sudeste or Sul (In English North, Northeast, Midwest, Southeast or South).

    CNES

    The CNES code refers to the health establishment where the participant works.

    Numerical.

    CNES Code or NaN.

    health_care_level

    Identification of the health care network level for which the course participant works.

    Categorical.

    “ATENCAO PRIMARIA”,

    “MEDIA COMPLEXIDADE”,

    “ALTA COMPLEXIDADE”,

    and their possible combinations.

    (In English "PRIMARY HEALTH CARE", "SECONDARY HEALTH CARE" AND "TERTIARY HEALTH CARE")

    year_enrollment

    Year in which the course participant registered.

    Numerical.

    Year (YYYY).

    CBO

    Participant occupation.

    Categorical.

    Text coded according to the Brazilian Classification of Occupations or “Indivíduo sem afiliação formal.” (In English “Individual without formal affiliation.”)

    Dataset name: prison_syphilis_and_population_brazil.csv

    Dataset period: 2017 - 2020

    Dataset Characteristics: Multivalued

    Number of Instances: 6

    Number of Attributes: 13

    Missing Values: No

    Source:

    • National Penitentiary Department (DEPEN) (Brasil, 2022d);

    Description: The data contained in the prison_syphilis_and_population_brazil.csv dataset (see Table 2) originate from the National Penitentiary Department Information System (SISDEPEN) (Brasil, 2022d). This dataset provides data on the population and prevalence of syphilis in the Brazilian prison system. In addition, it brings a rate that represents the normalized data for purposes of comparison between the populations of each region and Brazil.

    Table 2: Description of DEPEN dataset Features.

    Attributes

    Description

    datatype

    Value

    Region

    Brazilian region in which the participant resides. In addition, the sum of the regions, which refers to Brazil.

    Categorical.

    Brazil and Brazilian region according to IBGE: North, Northeast, Midwest, Southeast or South.

    syphilis_2017

    Number of syphilis cases in the prison system in 2017.

    Numerical.

    Number of syphilis cases.

    syphilis_rate_2017

    Normalized rate of syphilis cases in 2017.

    Numerical.

    Syphilis case rate.

    syphilis_2018

    Number of syphilis cases in the prison system in 2018.

    Numerical.

    Number of syphilis cases.

    syphilis_rate_2018

    Normalized rate of syphilis cases in 2018.

    Numerical.

    Syphilis case rate.

    syphilis_2019

    Number of syphilis cases in the prison system in 2019.

    Numerical.

    Number of syphilis cases.

    syphilis_rate_2019

    Normalized rate of syphilis cases in 2019.

    Numerical.

    Syphilis case rate.

    syphilis_2020

    Number of syphilis cases in the prison system in 2020.

    Numerical.

    Number of syphilis cases.

    syphilis_rate_2020

    Normalized rate of syphilis cases in 2020.

    Numerical.

    Syphilis case rate.

    pop_2017

    Prison population in 2017.

    Numerical.

    Population number.

    pop_2018

    Prison population in 2018.

    Numerical.

    Population number.

    pop_2019

    Prison population in 2019.

    Numerical.

    Population number.

    pop_2020

    Prison population in 2020.

    Numerical.

    Population number.

    Dataset name: students_cumulative_sum.csv

    Dataset period: 2018 - 2020

    Dataset Characteristics: Multivalued

    Number of Instances: 6

    Number of Attributes: 7

    Missing Values: No

    Source:

    • Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2022a);

    • Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2022e).

    Description: The data contained in the students_cumulative_sum.csv dataset (see Table 3) originate mainly from AVASUS (Brasil, 2022a). This dataset provides data on the number of students by region and year. In addition, it brings a rate that represents the normalized data for purposes of comparison between the populations of each region and Brazil. We used population data estimated by the IBGE (Brasil, 2022e) to calculate the rate.

    Table 3: Description of Students dataset Features.

  12. o

    Coronavirus (COVID-19) in Prisons in the United States, April - June 2020

    • openicpsr.org
    delimited, spss +1
    Updated Jun 14, 2020
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    Jacob Kaplan; Sebastian Hoyos-Torres; Oren Gur; Connor Concannon; Nick Jones (2020). Coronavirus (COVID-19) in Prisons in the United States, April - June 2020 [Dataset]. http://doi.org/10.3886/E119901V1
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    stata, delimited, spssAvailable download formats
    Dataset updated
    Jun 14, 2020
    Dataset provided by
    University of Pennsylvania
    City University of New York. John Jay College of Criminal Justice
    Philadelphia District Attorney's Office
    Authors
    Jacob Kaplan; Sebastian Hoyos-Torres; Oren Gur; Connor Concannon; Nick Jones
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 14, 2020 - Jun 24, 2020
    Area covered
    United States
    Description

    Summary: This is a collection of publicly reported data relevant to the COVID-19 pandemic scraped from state and federal prisons in the United States. Data are collected each night from every state and federal correctional agency’s site that has data available. Data from Massachusetts come directly from the ACLU Massachusetts COVID-19 website (https://data.aclum.org/sjc-12926-tracker/), not the Massachusetts DOC website. Data from a small number of states come from Recidiviz (https://www.recidiviz.org/) whose team manually collects data from these states. Not all dates are available for some states due to websites being down or changes to the website that cause some data to be missed by the scraper.The data primarily cover the number of people incarcerated in these facilities who have tested positive, negative, recovered, and have died from COVID-19. Many - but not all - states also provide this information for staff members. This dataset includes every variable that any state makes available. While there are dozens of variables in the data, most apply to only a small number of states or a single state.The data is primarily at the facility-date unit, meaning that each row represents a single prison facility on a single date. The date is the date we scraped the data (we do so each night between 9pm-3am EST) and not necessarily the date the data was updated. While many states update daily, some do so less frequently. As such, you may see some dates for certain states contain the same values. A small number of states do not provide facility-level data, or do so for only a subset of all the variables they make available. In these cases we have also collected state-level data and made that available separately. Please note: When facility data is available, the state-level file combines the aggregated facility-level data with any state-level data that is available. You should therefore use this file when doing a state-level analysis instead of aggregating the facility-level data, as some states report values only at the state level (these states may still have some data at the facility-level), and some states report cumulative numbers at the state level but do not report them at the facility level. As a result, when we identify this, we typically add the cumulative information to the state level file. The state level file is still undergoing quality checks and will be released soon.These data were scraped from nearly all state and federal prison websites that make their data available each night for several months, and we continue to collect data. Over time some states have changed what variables are available, both adding and removing some variables, as well as the definition of variables. For all states and time periods you are using this data for, please carefully examine the data to detect these kinds of issues. We have spent extensive time doing a careful check of the data to remove any issues we find, primarily ones that could be caused by a scraper not working properly. However, please check all data for issues before using it. Contact us at covidprisondata@gmail.com to let us know if you find any issues, have questions, or if you would like to collaborate on research.

  13. e

    The costs of imprisonment: A longitudinal study - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Dec 19, 2023
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    (2023). The costs of imprisonment: A longitudinal study - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/4967baf0-21ae-5a2c-bb17-c9330391e0b3
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    Dataset updated
    Dec 19, 2023
    Description

    The 1922 Prison System Enquiry Committee Report said that: 'In order to judge our Prison system rightly it is necessary to know what kind of people become prisoners... How many go to prison? For what length of sentence?' These questions persist, and are especially relevant for today's prison crisis. This project will assess nearly 100 years of historical data to explore, for the first time, how prison numbers were largely dictated by the repeat incarceration of recidivist's offenders with short sentences. It questions how the prison authorities attempted to manage increasing numbers of offenders by using early release schemes (licenses) in the nineteenth and twentieth centuries (licenses have only recently become available, generous access granted by The National Archives). This project will explore whether short sentences contributed to repeat offending, and whether early release schemes accelerated or inhibited recidivism. It investigates the financial costs of imprisonment to the country (and the human costs to those imprisoned) and does this over a significant period of time (allowing an examination of how repeated incarcerations affected the whole of an offender's criminal career). It concludes by asking what lessons can be learnt for today's debates about sentencing offenders and managing the prison population? Data was derived from the following sources: PCOM 3 (1853-1887, 1902-08, 1912-42) – these files contained 45,000 licenses and also the registers of license holders. They listed the prisoner’s name, sentence, where/when convicted, dates and conditions of the current license; previous convictions, age, previous occupation, when and from where the prisoner was released; and most had photographs of the prisoner. The National Archives granted us access to these records pre public release (they are now available on Find-My-Past and Ancestry). Criminal Registers 1853-1892 (contained offenders tried for indictable crimes, whether they were found guilty, details of the offence, and sentence imposed). Where possible we traced these offences in the Quarter Sessions Calendars in order to trace the antecedent criminal history. From these main sources, we were then able to trace prisoners released on license using a wide variety of other extant sources. These sources provided us with a considerable amount of additional information on offenders who were released on license: Census returns from 1841-1911 censuses (which gave details of the residence, family status, and occupation, of each person we will be searching for). Online Birth, Marriage and Death indices (which detailed if and when our offender was married, and had children; and, of course, when they died). Military records (mainly referring to World War One; these included service records - which in turn included disciplinary breaches - medal indices and pensions details. Metropolitan Police records including Habitual Criminal Registers (MEPO 6) which contain details of criminals as defined by sections 5-8 of the Prevention of Crimes Act 1871. From the sources above we constructed approximately 650 life grids. These were divided into an early (1853-55 n=62), middle (1871-73 n=201), and late (1885-1887 n=184) tranche, for 356 men and 288 women. Each life-grid charted offending/life histories for each offender. Studies funded by Leverhulme Trust (F/00130/H)) and ESRC (RES-062-23-0416) used life grids and `whole-life’ research methods and the method is now well-tested. The life-grid data was then entered into excel and SPSS in order to produce quantifiable data on - the progress of their criminal careers, their periods of incarceration, their employment careers, life events such as marriage, death of parents, and other significant life events. We had over two hundred thousand fields of data at the conclusion of our data collection/analysis. By analysing each of the life grids we were able to see the relationships and connections between life events and offending post-imprisonment (both short and long periods of custody, whilst on licence, and after license had expired.

  14. T

    Utah Correctional Facilities

    • opendata.utah.gov
    • esri-denver-office.hub.arcgis.com
    application/rdfxml +5
    Updated Mar 20, 2020
    + more versions
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    (2020). Utah Correctional Facilities [Dataset]. https://opendata.utah.gov/dataset/Utah-Correctional-Facilities/4zfr-z4af
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    tsv, json, csv, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Mar 20, 2020
    Area covered
    Utah
    Description

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. AGRC has made a concerted effort to include all correctional institutions.

    This dataset is comprised completely of license free data.

    Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries.

    "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields.

    Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results.

    All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics.

    Last Update: June, 2013

  15. a

    New Hampshire Correctional Institutions

    • hub.arcgis.com
    Updated Aug 9, 2018
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    The citation is currently not available for this dataset.
    Explore at:
    Dataset updated
    Aug 9, 2018
    Dataset authored and provided by
    New Hampshire GRANIT GIS Clearinghouse
    Area covered
    Description

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; Bureau of Alcohol, Tobacco, Firearms and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 04/26/2006 and the newest record dates from 10/19/2009

  16. k

    Correctional Institutions 2008

    • archivehub.kansasgis.org
    Updated Apr 7, 2008
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    Kansas State Government GIS (2008). Correctional Institutions 2008 [Dataset]. https://archivehub.kansasgis.org/datasets/correctional-institutions-2008
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    Dataset updated
    Apr 7, 2008
    Dataset authored and provided by
    Kansas State Government GIS
    Area covered
    Description

    Jails and Prisons (Correctional Institutions) in Kansas The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as ONENTITY at the entrance. If the facility's buildings are not enclosed, the locations were depicted as ONENTITY on the building or BLOCKFACE on the correct street segment. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to the fact that many constables work out of their home. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Descriptions were assigned based on the facility's main function, which were determined by the entity's name, facility type, web research and state supplied data. For records where the entity's name represents both datasets, the NAICS Description was assigned based on the specifications of the dataset the record is assigned to. text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06

  17. National Prisoner Statistics, [United States], 1978-2019

    • icpsr.umich.edu
    • catalog.data.gov
    ascii, delimited, r +3
    Updated Dec 16, 2021
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    United States. Bureau of Justice Statistics (2021). National Prisoner Statistics, [United States], 1978-2019 [Dataset]. http://doi.org/10.3886/ICPSR37986.v1
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    ascii, stata, spss, sas, delimited, rAvailable download formats
    Dataset updated
    Dec 16, 2021
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Justice Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37986/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37986/terms

    Time period covered
    1978 - 2019
    Area covered
    United States
    Description

    The National Prisoner Statistics (NPS) data collection began in 1926 in response to a congressional mandate to gather information on persons incarcerated in state and federal prisons. Originally under the auspices of the U.S. Census Bureau, the collection moved to the Bureau of Prisons in 1950, and then in 1971 to the National Criminal Justice Information and Statistics Service, the precursor to the Bureau of Justice Statistics (BJS) which was established in 1979. From 1979 to 2013, the Census Bureau was the NPS data collection agent. In 2014, the collection was competitively bid in conjunction with the National Corrections Reporting Program (NCRP), since many of the respondents for NPS and NCRP are the same. The contract was awarded to Abt Associates, Inc. The NPS is administered to 51 respondents. Before 2001, the District of Columbia was also a respondent, but responsibility for housing the District of Columbia's sentenced prisoners was transferred to the Federal Bureau of Prisons, and by yearend 2001 the District of Columbia no longer operated a prison system. The NPS provides an enumeration of persons in state and federal prisons and collects data on key characteristics of the nation's prison population. NPS has been adapted over time to keep pace with the changing information needs of the public, researchers, and federal, state, and local governments.

  18. Data from: In Custody Deaths

    • data.boston.gov
    csv
    Updated Aug 9, 2021
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    Boston Police Department (2021). In Custody Deaths [Dataset]. https://data.boston.gov/dataset/in-custody-deaths
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    csv(558), csv(435)Available download formats
    Dataset updated
    Aug 9, 2021
    Dataset authored and provided by
    Boston Police Departmenthttps://bpdnews.com/
    Description

    The Boston Police Department's Homicide Investigation Unit, in conjunction with the Suffolk County District Attorney’s Office, investigates deaths that occur while a prisoner is under police custody. This may include incidents that occur during arrest, transport, while in a holding cell, etc.

    The Suffolk County District Attorney’s Office has legal authority over all death investigations in Suffolk County. They investigate all in custody deaths in conjunction with BPD, and make a determination as to whether there is a violation of criminal law.

    Due to the infrequency of in-custody deaths, this dashboard will be updated as soon as possible following an incident, or a new medical examiner report is received. If there are no incidents in a year the dashboard will be updated annually to record a zero for the previous year.

  19. Average counts of offenders in federal programs, Canada and regions

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Mar 19, 2024
    + more versions
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    Government of Canada, Statistics Canada (2024). Average counts of offenders in federal programs, Canada and regions [Dataset]. http://doi.org/10.25318/3510015501-eng
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    Dataset updated
    Mar 19, 2024
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Adult correctional services, custodial and community supervision, average counts of offenders in federal programs, Canada and regions, five years of data.

  20. u

    New Hampshire Correctional Institutions

    • nhgeodata.unh.edu
    • granit.unh.edu
    Updated Dec 30, 2009
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    New Hampshire GRANIT GIS Clearinghouse (2009). New Hampshire Correctional Institutions [Dataset]. https://www.nhgeodata.unh.edu/maps/new-hampshire-correctional-institutions
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    Dataset updated
    Dec 30, 2009
    Dataset authored and provided by
    New Hampshire GRANIT GIS Clearinghouse
    Area covered
    Description

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; Bureau of Alcohol, Tobacco, Firearms and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 04/26/2006 and the newest record dates from 10/19/2009

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The Associated Press (2023). The Marshall Project: COVID Cases in Prisons [Dataset]. https://data.world/associatedpress/marshall-project-covid-cases-in-prisons

The Marshall Project: COVID Cases in Prisons

The Marshall Project is compiling data on the prevalence of COVID-19 infection in prisons across the country

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
csv, zipAvailable download formats
Dataset updated
Apr 6, 2023
Authors
The Associated Press
Time period covered
Jul 31, 2019 - Aug 1, 2021
Description

Overview

The Marshall Project, the nonprofit investigative newsroom dedicated to the U.S. criminal justice system, has partnered with The Associated Press to compile data on the prevalence of COVID-19 infection in prisons across the country. The Associated Press is sharing this data as the most comprehensive current national source of COVID-19 outbreaks in state and federal prisons.

Lawyers, criminal justice reform advocates and families of the incarcerated have worried about what was happening in prisons across the nation as coronavirus began to take hold in the communities outside. Data collected by The Marshall Project and AP shows that hundreds of thousands of prisoners, workers, correctional officers and staff have caught the illness as prisons became the center of some of the country’s largest outbreaks. And thousands of people — most of them incarcerated — have died.

In December, as COVID-19 cases spiked across the U.S., the news organizations also shared cumulative rates of infection among prison populations, to better gauge the total effects of the pandemic on prison populations. The analysis found that by mid-December, one in five state and federal prisoners in the United States had tested positive for the coronavirus -- a rate more than four times higher than the general population.

This data, which is updated weekly, is an effort to track how those people have been affected and where the crisis has hit the hardest.

Methodology and Caveats

The data tracks the number of COVID-19 tests administered to people incarcerated in all state and federal prisons, as well as the staff in those facilities. It is collected on a weekly basis by Marshall Project and AP reporters who contact each prison agency directly and verify published figures with officials.

Each week, the reporters ask every prison agency for the total number of coronavirus tests administered to its staff members and prisoners, the cumulative number who tested positive among staff and prisoners, and the numbers of deaths for each group.

The time series data is aggregated to the system level; there is one record for each prison agency on each date of collection. Not all departments could provide data for the exact date requested, and the data indicates the date for the figures.

To estimate the rate of infection among prisoners, we collected population data for each prison system before the pandemic, roughly in mid-March, in April, June, July, August, September and October. Beginning the week of July 28, we updated all prisoner population numbers, reflecting the number of incarcerated adults in state or federal prisons. Prior to that, population figures may have included additional populations, such as prisoners housed in other facilities, which were not captured in our COVID-19 data. In states with unified prison and jail systems, we include both detainees awaiting trial and sentenced prisoners.

To estimate the rate of infection among prison employees, we collected staffing numbers for each system. Where current data was not publicly available, we acquired other numbers through our reporting, including calling agencies or from state budget documents. In six states, we were unable to find recent staffing figures: Alaska, Hawaii, Kentucky, Maryland, Montana, Utah.

To calculate the cumulative COVID-19 impact on prisoner and prison worker populations, we aggregated prisoner and staff COVID case and death data up through Dec. 15. Because population snapshots do not account for movement in and out of prisons since March, and because many systems have significantly slowed the number of new people being sent to prison, it’s difficult to estimate the total number of people who have been held in a state system since March. To be conservative, we calculated our rates of infection using the largest prisoner population snapshots we had during this time period.

As with all COVID-19 data, our understanding of the spread and impact of the virus is limited by the availability of testing. Epidemiology and public health experts say that aside from a few states that have recently begun aggressively testing in prisons, it is likely that there are more cases of COVID-19 circulating undetected in facilities. Sixteen prison systems, including the Federal Bureau of Prisons, would not release information about how many prisoners they are testing.

Corrections departments in Indiana, Kansas, Montana, North Dakota and Wisconsin report coronavirus testing and case data for juvenile facilities; West Virginia reports figures for juvenile facilities and jails. For consistency of comparison with other state prison systems, we removed those facilities from our data that had been included prior to July 28. For these states we have also removed staff data. Similarly, Pennsylvania’s coronavirus data includes testing and cases for those who have been released on parole. We removed these tests and cases for prisoners from the data prior to July 28. The staff cases remain.

About the Data

There are four tables in this data:

  • covid_prison_cases.csv contains weekly time series data on tests, infections and deaths in prisons. The first dates in the table are on March 26. Any questions that a prison agency could not or would not answer are left blank.

  • prison_populations.csv contains snapshots of the population of people incarcerated in each of these prison systems for whom data on COVID testing and cases are available. This varies by state and may not always be the entire number of people incarcerated in each system. In some states, it may include other populations, such as those on parole or held in state-run jails. This data is primarily for use in calculating rates of testing and infection, and we would not recommend using these numbers to compare the change in how many people are being held in each prison system.

  • staff_populations.csv contains a one-time, recent snapshot of the headcount of workers for each prison agency, collected as close to April 15 as possible.

  • covid_prison_rates.csv contains the rates of cases and deaths for prisoners. There is one row for every state and federal prison system and an additional row with the National totals.

Queries

The Associated Press and The Marshall Project have created several queries to help you use this data:

Get your state's prison COVID data: Provides each week's data from just your state and calculates a cases-per-100000-prisoners rate, a deaths-per-100000-prisoners rate, a cases-per-100000-workers rate and a deaths-per-100000-workers rate here

Rank all systems' most recent data by cases per 100,000 prisoners here

Find what percentage of your state's total cases and deaths -- as reported by Johns Hopkins University -- occurred within the prison system here

Attribution

In stories, attribute this data to: “According to an analysis of state prison cases by The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system, and The Associated Press.”

Contributors

Many reporters and editors at The Marshall Project and The Associated Press contributed to this data, including: Katie Park, Tom Meagher, Weihua Li, Gabe Isman, Cary Aspinwall, Keri Blakinger, Jake Bleiberg, Andrew R. Calderón, Maurice Chammah, Andrew DeMillo, Eli Hager, Jamiles Lartey, Claudia Lauer, Nicole Lewis, Humera Lodhi, Colleen Long, Joseph Neff, Michelle Pitcher, Alysia Santo, Beth Schwartzapfel, Damini Sharma, Colleen Slevin, Christie Thompson, Abbie VanSickle, Adria Watson, Andrew Welsh-Huggins.

Questions

If you have questions about the data, please email The Marshall Project at info+covidtracker@themarshallproject.org or file a Github issue.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

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