From the project page: https://github.com/jkbren/incarcerated-populations-data/

The United States has the highest incarceration rate in the world. Through combinations of structural biases in the criminal justice and police systems, we see even higher incarceration rates among Black and Hispanic people. During the first year of the COVID-19 pandemic, the number of incarcerated people in the United States decreased by at least 17%---the largest, fastest reduction in prison population in American history. Using an original dataset curated from public sources on prison demographics across all 50 states and the District of Columbia, we show that incarcerated white people benefited disproportionately from this decrease in the U.S. prison population, and the fraction of incarcerated Black and Latino people sharply increased. This pattern persists across prison systems in nearly every state and deviates from a decade-long trend before 2020 and the onset of COVID-19, when the proportion of incarcerated white people was increasing amid declining numbers of Black people in prison. While a variety of mechanisms underlie these alarming trends, we explore why racial inequities in average sentence length are a likely major contributor. Ultimately, this study reveals how disruptions caused by COVID-19 exacerbated racial inequalities in the criminal legal system, and highlights key forces that drive mass incarceration.

Released under MIT license

In 2011, a historic Supreme Court decision mandated that the state of California substantially reduce its prison population to alleviate overcrowding, which was deemed so severe as to preclude the provision of adequate healthcare. To comply, California passed the Public Safety Realignment Act (Assembly Bill [AB] 109), representing the largest ever court-ordered reduction of a prison population in U.S. history. AB109 was successful in reducing the state prison population; however, although the policy was precipitated by inadequate healthcare in state prisons, no studies have examined its effects on prisoner health. As other states grapple with overcrowded prisons and look to California’s experience with this landmark policy, understanding how it may have impacted prisoner health is critical. We sought to evaluate the effects of AB109 on prison mortality and assess the extent to which policy-induced changes in the age distribution of prisoners may have contributed to these effects. To do so, we used prison mortality data from the Bureau of Justice Statistics and the California Deaths in Custody reporting program and prison population data from the National Corrections Reporting Program to examine changes in overall prison mortality, the age distribution of prisoners, and age-adjusted prison mortality in California relative to other states before and after the implementation of AB109. Following AB109, California prisons experienced an increase in overall mortality relative to other states that attenuated within three years. Over the same period, California experienced a greater upward shift in the age distribution of its prisoners relative to other states, suggesting that the state’s increase in overall mortality may have been driven by this change in age distribution. Indeed, when accounting for this differential change in age distribution, mortality among California prisoners exhibited a greater reduction relative to other states in the third year after implementation. As other states seek to reduce their prison populations to address overcrowding, assessments of California’s experience with AB109 should consider this potential improvement in age-adjusted mortality.

The Washington legislature has established a comprehensive system of corrections for convicted law violators within the state of Washington to accomplish a primary objective of ensuring public safety. The system is designed and managed to provide the maximum feasible safety for the persons and property of the general public, the staff, and the inmates (RCW 72.09.010).

Archived as of 9/25/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset is the underlying data for the Public Safety portion of the Equity Data Portal displaying Indiana's prison population by demographics. A snapshot of the incarcerated population sentenced to the Indiana Department of Correction, including race, age, felony type, and most serious offense category. All data reflects December 31st of the selected year. This dataset contains the underlying data for the 'Population' tab of the 'Prison Incarceration' dashboard within the Public Safety domain.

This measure reports the percentage of offenders who are currently serving terms in Iowa correctional institutions who have a high school diploma or an equivalent. It includes offenders where the highest level of education completed includes: High School Diploma, HiSET/GED or Special Education Diploma.

Currently incarcerated inmate population with relevant demographic, offense, and parole information.

The purpose of the Survey of Jails in Indian Country is an enumeration of all known adult and juvenile facilities -- jails, confinement facilities, detention centers, and other correctional facilities operated by tribal authorities or by the Bureau of Indian Affairs (BIA)in the United States Department of the Interior. For the purpose of this collection, Indian country includes reservations, pueblos, rancherias, and other Native American and Alaska Native communities throughout the United States. The survey collects data on the number of adults and juveniles held on the last weekday in June 2009, type of offense, average daily population in June, most crowded day in June, admissions and releases in June, number of inmate deaths and suicide attempts, rated capacity, and jail staffing.

Description

This dataset contains information about the prisoners in India in 2020. A criminal is a person who is guilty of a crime, notably breaking the law. A prisoner is a person incarcerated in a prison, while on trial or serving a sentence

Description

• It has 87 columns and 39 rows. The columns include the state or union territory, the educational standard, the domicile, the religion, the gender, the age group, the type of prison, and the type of offense.
• The rows include the total for each state or union territory and the total for all of India.
• The dataset is based on the Prison Statistics India (PSI) report published by the National Crime Records Bureau (NCRB).
• The dataset can be used for analysis and visualization of the prisoner's statistics

Features

Here is a list of first 10 column names and their descriptions: 1. Sl. No.: Serial number of the row. 2. State/UT: The state or union territory where the prison is located. 3. Educational Standard - Illiterate: The number of prisoners who are illiterate 4. Educational Standard - Below Class X: The number of prisoners who have completed less than 10 years of education. 5. Educational Standard - Class X & above but below Graduation: The number of prisoners who have completed 10 years of education or more but less than graduation 6. Educational Standard - Graduate: The number of prisoners who have completed graduation or higher education. 7. Educational Standard - Holding Tech. Degree/ Diploma: The number of prisoners who hold a technical degree or diploma 8. Educational Standard - Post Graduate: The number of prisoners who have completed post-graduation or higher education. 9. Educational Standard - Total: The total number of prisoners by educational standard. 10. Domicile - Belongs to State: The number of prisoners who belong to the state where the prison is located

ObjectiveWe aimed to systematically review recidivism rates in individuals given community sentences internationally. We sought to explore sources of variation between these rates and how reporting practices may limit their comparability across jurisdictions. Finally, we aimed to adapt previously published guidelines on recidivism reporting to include community sentenced populations.MethodsWe searched MEDLINE, PsycINFO, SAGE and Google Scholar for reports and studies of recidivism rates using non-specific and targeted searches for the 20 countries with the largest prison populations worldwide. We identified 28 studies with data from 19 countries. Of the 20 countries with the largest prison populations, only 2 reported recidivism rates for individuals given community sentences.ResultsThe most commonly reported recidivism information between countries was for 2-year reconviction, which ranged widely from 14% to 43% in men, and 9% to 35% in women. Explanations for recidivism rate variations between countries include when the follow-up period started and whether technical violations were taken into account.ConclusionRecidivism rates in individuals receiving community sentences are typically lower in comparison to those reported in released prisoners, although these two populations differ in terms of their baseline characteristics. Direct comparisons of the recidivism rates in community sentenced cohorts across jurisdictions are currently not possible, but simple changes to existing reporting practices can facilitate these. We propose recommendations to improve reporting practices.

This report documents and examines the process of de congestion of prisons across India by assessing the functioning of High Powered Committees (HPC), Undertrial Review Committees (UTRC) and legal aid functionaries. It has vital data on prison population rates as well as a comparative on both pre and post COVID-19 induced lockdown. This data helps in understanding the impact on prison overcrowding as well as predicting future overcrowding rates with High Courts cancelling interim bail and paroles of prisoners across the country. As such this information would be vital for journalists, grassroots organizations as well as other stakeholders to highlight related concerns in their states/region of work.

ObjectivesTo systematically review recidivism rates internationally, report whether they are comparable and, on the basis of this, develop best reporting guidelines for recidivism.MethodsWe searched MEDLINE, Google Web, and Google Scholar search engines for recidivism rates around the world, using both non-country-specific searches as well as targeted searches for the 20 countries with the largest total prison populations worldwide.ResultsWe identified recidivism data for 18 countries. Of the 20 countries with the largest prison populations, only 2 reported repeat offending rates. The most commonly reported outcome was 2-year reconviction rates in prisoners. Sample selection and definitions of recidivism varied widely, and few countries were comparable.ConclusionsRecidivism data are currently not valid for international comparisons. Justice Departments should consider using the reporting guidelines developed in this paper to report their data.

Abstract: Mortality in prisons, a basic indicator of the right to health for incarcerated persons, has never been studied extensively in Brazil. An assessment of all-cause and cause-specific mortality in prison inmates was conducted in 2016-2017 in the state of Rio de Janeiro, based on data from the Mortality Information System and Prison Administration. Mortality rates were compared between prison population and general population after standardization. The leading causes of death in inmates were infectious diseases (30%), cardiovascular diseases (22%), and external causes (12%). Infectious causes featured HIV/AIDS (43%) and TB (52%, considering all deaths with mention of TB). Only 0.7% of inmates who died had access to extramural health services. All-cause mortality rate was higher among prison inmates than in the state’s general population. Among inmates, mortality from infectious diseases was 5 times higher, from TB 15 times higher, and from endocrine diseases (especially diabetes) and cardiovascular diseases 1.5 and 1.3 times higher, respectively, while deaths from external causes were less frequent in prison inmates. The study revealed important potentially avoidable excess deaths in prisons, reflecting lack of care and exclusion of this population from the Brazilian Unified National Health System. This further highlights the need for a precise and sustainable real-time monitoring system for deaths, in addition to restructuring of the prison staff through implementation of the Brazilian National Policy for Comprehensive Healthcare for Persons Deprived of Freedom in the Prison System in order for inmates to fully access their constitutional right to health with the same quality and timeliness as the general population.

BackgroundIt has been hypothesized that prisons serve as amplifiers of general tuberculosis (TB) epidemics, but there is a paucity of data on this phenomenon and the potential population-level effects of prison-focused interventions. This study (1) quantifies the TB risk for prisoners as they traverse incarceration and release, (2) mathematically models the impact of prison-based interventions on TB burden in the general population, and (3) generalizes this model to a wide range of epidemiological contexts.Methods and findingsWe obtained individual-level incarceration data for all inmates (n = 42,925) and all reported TB cases (n = 5,643) in the Brazilian state of Mato Grosso do Sul from 2007 through 2013. We matched individuals between prisoner and TB databases and estimated the incidence of TB from the time of incarceration and the time of prison release using Cox proportional hazards models. We identified 130 new TB cases diagnosed during incarceration and 170 among individuals released from prison. During imprisonment, TB rates increased from 111 cases per 100,000 person-years at entry to a maximum of 1,303 per 100,000 person-years at 5.2 years. At release, TB incidence was 229 per 100,000 person-years, which declined to 42 per 100,000 person-years (the average TB incidence in Brazil) after 7 years. We used these data to populate a compartmental model of TB transmission and incarceration to evaluate the effects of various prison-based interventions on the incidence of TB among prisoners and the general population. Annual mass TB screening within Brazilian prisons would reduce TB incidence in prisons by 47.4% (95% Bayesian credible interval [BCI], 44.4%–52.5%) and in the general population by 19.4% (95% BCI 17.9%–24.2%). A generalized model demonstrates that prison-based interventions would have maximum effectiveness in reducing community incidence in populations with a high concentration of TB in prisons and greater degrees of mixing between ex-prisoners and community members. Study limitations include our focus on a single Brazilian state and our retrospective use of administrative databases.ConclusionsOur findings suggest that the prison environment, more so than the prison population itself, drives TB incidence, and targeted interventions within prisons could have a substantial effect on the broader TB epidemic.

Context

Predicting parole violators In many criminal justice systems around the world, inmates deemed not to be a threat to society are released from prison under the parole system prior to completing their sentence. They are still considered to be serving their sentence while on parole, and they can be returned to prison if they violate the terms of their parole.

Parole boards are charged with identifying which inmates are good candidates for release on parole. They seek to release inmates who will not commit additional crimes after release. In this problem, we will build and validate a model that predicts if an inmate will violate the terms of his or her parole. Such a model could be useful to a parole board when deciding to approve or deny an application for parole.

For this prediction task, we will use data from the United States 2004 National Corrections Reporting Program, a nationwide census of parole releases that occurred during 2004. We limited our focus to parolees who served no more than 6 months in prison and whose maximum sentence for all charges did not exceed 18 months. The dataset contains all such parolees who either successfully completed their term of parole during 2004 or those who violated the terms of their parole during that year. The dataset contains the following variables:

Content

male: 1 if the parolee is male, 0 if female race: 1 if the parolee is white, 2 otherwise age: the parolee's age (in years) when he or she was released from prison state: a code for the parolee's state. 2 is Kentucky, 3 is Louisiana, 4 is Virginia, and 1 is any other state. The three states were selected due to having a high representation in the dataset. time.served: the number of months the parolee served in prison (limited by the inclusion criteria to not exceed 6 months). max.sentence: the maximum sentence length for all charges, in months (limited by the inclusion criteria to not exceed 18 months). multiple.offenses: 1 if the parolee was incarcerated for multiple offenses, 0 otherwise. crime: a code for the parolee's main crime leading to incarceration. 2 is larceny, 3 is drug-related crime, 4 is driving-related crime, and 1 is any other crime. violator: 1 if the parolee violated the parole, and 0 if the parolee completed the parole without violation.

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ACKNOWLEGMENT

MITx ANALYTIX

This is an Annotation for Transparent Inquiry (ATI) data project. The annotated article can be viewed on the publisher's website here. Project Summary Scholarship on human rights diplomacy (HRD)—efforts by government officials to engage publicly and privately with their foreign counterparts—often focuses on actions taken to “name and shame” target countries, because private diplomatic activities are unobservable. To understand how HRD works in practice, we explore a campaign coordinated by the US government to free twenty female political prisoners. We compare release rates of the featured women to two comparable groups: a longer list of women considered by the State Department for the campaign; and other women imprisoned simultaneously in countries targeted by the campaign. Both approaches suggest that the campaign was highly effective. We consider two possible mechanisms through which expressive public HRD works: by imposing reputational costs and by mobilizing foreign actors. However, in-depth interviews with US officials and an analysis of media coverage find little evidence of these mechanisms. Instead, we argue that public pressure resolved deadlock within the foreign policy bureaucracy, enabling private diplomacy and specific inducements to secure the release of political prisoners. Entrepreneurial bureaucrats leveraged the spotlight on human rights abuses to overcome competing equities that prevent government-led coercive diplomacy on these issues. Our research highlights the importance of understanding the intersection of public and private diplomacy before drawing inferences about the effectiveness of HRD. Data Generation We generated four sources of data for this project: 1. A dataset of political prisoners from 13 countries based on Amnesty International Urgent Action reports between 2000 and 2015. 2. Arrest and release information for a dataset of female political prisoners 3. A dataset on media attention based on both news articles from LexisNexis and online search trends from Google Trends 4. Interviews conducted with U.S. government officials and other human rights advocates involved in the #Freethe20 campaign to free political prisoners launched in September 2015 We used two sources of data for each of our two research questions. Our first research question was: Did the #Freethe20 campaign have an impact on the release rate of political prisoners? In an ideal world, we would have a comprehensive set of female political prisoners to compare with #Freethe20 prisoners. However, as we explain in the manuscript, in countries with more dire human rights situations, arrests often go unreported. In some cases, the sheer volume of political prisoners makes chronicling information about them challenging, if not impossible. Therefore, in order to construct a comparable set of cases, one strategy we used was to collect information from Amnesty International’s “Urgent Action” campaigns. To our knowledge, Amnesty International has the most comprehensive, publicly available list of contemporary political prisoners globally. Their records are public and searchable, which allowed us to construct a population of political prisoners from the countries targeted by the #Freethe20 campaign. We began our data collection with a base set of Urgent Actions metadata generated by Judith Kelley and Dan Nielson via webscraping from the Amnesty International website. Using a list of URLs that linked to each Urgent Action Report, we coded the name and sex of individuals featured in each Urgent Action Report from 2000 through September 2015 (the start of the #Freethe20 campaign) in the 13 countries featured in the campaign (Azerbaijan, Burma, China, Egypt, Ethiopia, Eritrea, Iran, North Korea, Russia, Syria, Uzbekistan, Venezuela, and Vietnam). Instructions about how we coded this information and sample documents are available in the QDR repository (QDR: MyrickWeinstein_codebook_urgentaction.pdf). After compiling a base dataset of individuals featured in Urgent Action reports, we identified the women in the dataset (~17% of entries) and conducted additional research about (1) whether these women could be classified as political prisoners, and (2) whether and when these women were released from prison, detention, or house arrest. Here, we relied on both follow-up reporting from Amnesty International as well as a variety of online news sources. We deposited the coding instructions for this process (MyrickWeinstein_codebook_releaseinfo.pdf) and also include documentation on additional online news sources that we used to make a judgment on a particular case. Our second question was: How and under what conditions did #Freethe20 affect the release rate of female political prisoners? To answer this question, we look at strategies of both public pressure and private, coercive diplomacy. For the former, we collected data on media attention and online search trends. We searched for newspapers and news articles that featured...

ABSTRACT Tuberculosis (TB) is a serious infectious disease, and its control is considered a challenge, especially among vulnerable populations such as prisoners. The occurrence of TB in prisons is an alarming public health problem in many countries. This integrative review aims to describe the epidemiology of TB and control strategies for this disease in countries with the largest prison populations. Studies have shown that it is essential to know the prevalence of TB in prisons of each country. This is because it can serve as an indication of the need for action in prisons to reduce TB rates, including improving the structure of prison environments, rapidly and accurately diagnosing new cases, identifying drug-resistant strains, and implementing effective and directly observed treatment for TB.

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

Summary Since 2017, GEO shares have fallen sharply from $30 to ~$8.50 per share, at one point below even the book value of $8.19 per share. President Biden recently signed an executive order that banned the renewal of Department of Justice contracts with private prisons, but the effect on GEO is way way less than the market thinks. The border crisis renders ICE dependent on GEO for capacity, making it near impossible for ICE to cut ties in the near future. With a market cap of just $1.02 Billion, GEO has the potential to increase 2-3x in the next 6-12 months. cropped image of african american prisoner reading book LightFieldStudios/iStock via Getty Images Thesis GEO Group (GEO) is a deeply mispriced provider of privately-owned prisons, falling from a price of $30+ in early 2017 to the current price of $8.50 per share. GEO has fallen primarily as a result of concerns about legislation regarding private prisons, a canceled dividend, the likely shift away from a REIT structure, and high levels of debt. These overblown concerns have created a pretty solid structural opportunity. kmosby1992@gmail.com password kmosby1992@gmail.com Subscribe Company overview GEO operates in several segments, such as GEO care, International services, and U.S. Secure Services. Source: Annual report 1 - U.S. Secure Services U.S. Secure services account for the majority of their revenue, 67%, and includes their correctional facilities and processing centers. Secure services manage 74,000 beds across 58 facilities as of the 2020 annual report. GEO transport is included in U.S. secure services, but we felt it warranted its own paragraph. GEO transport provides secure transportation services to government agencies. With 400 customized, U.S. Department of Transportation compliant vehicles, GEO transport drove more than 14 million miles in 2020. 2 - GEO Care GEO care is a series of programs designed to reintegrate inmates and troubled youth into society. They operate through reentry centers, non-residential reentry programs, and youth treatment programs. GEO care operates approximately 4-dozen reentry centers, which provide housing, employment assistance, rehabilitation, substance abuse counseling, and vocational and education programs to current and former inmates. Through their reentry segment, they operate more than 70 non-residential reentry programs that provide behavioral assessments, treatment, supervision, and education. GEO care made up 23% of total 2020 revenue. Geo monitoring is included in GEO care. Through a wholly-owned subsidiary, BI Inc., GEO offers monitoring technology for parolees, probationers, pretrial defendants, and individuals involved in the immigration process. As of the 2020 annual report, BI helps monitor ~155,000 individuals across all 50 states. 3 - International operations International operations made up only 10% of revenue in 2020, but it is showing signs of growth. GEO recently landed a 10-year contract with the United kingdom, which they expect to total $760 million in revenue over the course of the contract. They also landed an 8-year contract with the Scottish Prison Service, which grants an annualized revenue of $39 million and has a 4-year renewal period. Why is GEO Mispriced? While there are several reasons for the dramatic reduction in share price over the last 4 years, the main reason was the looming fear of legislation destroying privately owned prisons. To a degree, this fear materialized on January 26th, 2021, when President Biden signed an Executive Order ordering the Attorney General not to renew any Department of Justice contracts with "privately operated criminal detention facilities." At face value, this order seems as though it would have a devastating impact on GEO. However, only ~25% of total revenue is impacted in any form by this order. The executive order only concerns branches of the Department of Justice. Only 2 DOJ branches have business connections with GEO, the US Marshals (USMS), and the Bureau of Prisons (BOP). Source: Annual report It is imperative to note that Immigration and Customs Enforcement (ICE), is not a branch of the DOJ and is therefore unaffected by this order. Individual states, as well as other countries, are unaffected by this order Bureau of Prisons GEO currently holds several agreements with the BOP relating to operations of prisons across the country. As of year-end 2020, agreements involving the BOP accounted for 14% of total revenue. All revenue from the BOP will not disappear, as the executive order does not impact reentry facilities. In 2Q21, after the executive order was made, GEO renewed 5 BOP reentry contracts. GEO even scored a new contract with the BOP, regarding the construction and operation of a new facility in Tampa. United States Marshal Service The United States Marshal Service does not own o... Visit https://dataone.org/datasets/sha256%3A900514e651e0d2c774ad90f358c9db90884c2baf98c068f470b290b3c4b3103a for complete metadata about this dataset.

This survey of inmates in five California prisons was conducted by the RAND Corporation with a grant from the National Institute of Justice. Researchers distributed an anonymous self-administered questionnaire to groups of 10-20 inmates at a time. Using the self-report technique, the survey obtained detailed information about the crimes committed by these prisoners prior to their incarceration. Variables were calculated to examine the characteristics of repeatedly arrested or convicted offenders (recidivists) as well as offenders reporting the greatest number of serious crimes (habitual criminals). The variables include crimes committed leading to incarceration, rates of criminal activity, and social-psychological scales for analyzing motivations to commit crimes, as well as self-reports of age, race, education, marital status, employment, income, and drug use.

Adult correctional services, custodial and community supervision, average counts of adults in provincial and territorial programs, five years of data.