This dataset displays the inmate populations for all the Federal Prisons throughout the United States on 7.2.08. This weekly Population Report can be found on the Bureau of Prisons website at bop.gov. These facilities are positioned by their lat/lon and this dataset is updated on a weekly basis.

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.

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...

The objective of the Survey of Jails in Indian Country is to gather data on all adult and juvenile jail facilities and detention centers in Indian country, which is defined for purposes of this collection as reservations, pueblos, rancherias, and other Native American and Alaska Native communities throughout the United States. The survey, a complete enumeration of all 69 confinement facilities operated by tribal authorities or by the Bureau of Indian Affairs (BIA), provides data on number of inmates, staffing, and facility characteristics and needs. Variables describe each facility, including who operated it, facility age, facility function, rated capacity, authority to house juveniles, number of juveniles held, number of admission and discharges in last 30 days, number of inmate deaths, peak population during June, number of inmates held by sex and conviction status on June 30, number of facility staff by sex and function, facility crowding, renovation and building plans, types of programs available to inmates, and overview of facility and staffing needs.

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 database seeks to capture the rise and extent of quantification as a tool of government by tracing the development of performance indicators used for regulatory purposes between 1985 and 2015 across different public service sectors (health/hospitals; higher education/universities; criminal justice/prisons) in the UK (with a specific focus on England). The cross-sectoral comparison intends to capture the diffusion of indicators across domains, and to compare temporal dynamics in the adoption of similar or different new public management instruments: Do indicators develop in a similar pace across sectors? What are their focus, audience and goals? And how did these change over time?Numbers increasingly govern public services. Both policymaking activities and administrative control are increasingly structured around calculations such as cost-benefit analyses, estimates of social and financial returns, measurements of performance and risk, benchmarking, quantified impact assessments, ratings and rankings, all of which provide information in the form of a numerical representation. Through quantification, public services have experienced a fundamental transformation from government by rules to governance by numbers, with fundamental implications not just for our understanding of the nature of public service itself, but also for wider debates about the nature of citizenship and democracy. This project scrutinizes the relationships between quantification, administrative capacity and democracy across three policy sectors (health/hospitals, higher education/universities, criminal justice/prisons) and four countries (France, Germany, Netherlands, UK). It offers a cross-national and cross-sectoral study of how managerialist ideas and instruments of quantification have been adopted and how they mattered. More specifically, it examines (i) how quantification has travelled across sectors and states; (ii) relations between quantification and administrative capacity; and (iii) how quantification has redefined relations between public service and liberal democratic understandings of public welfare, notions of citizenship, equity, accountability and legitimacy. The database aims to provide a comprehensive overview of different indicators used by regulators to measure the performance of universities, hospitals and prisons in England at different points of time (1985, 1995, 2005, 2015). It intends to be exhaustive. However, we cannot lay claim to completeness, given the growing extent and scope of indicators which makes 100% completeness a difficult goal to attain. The chosen sectors (higher education/universities, healthcare/hospitals and criminal justice/prisons) constitute three public sectors where performance measurement took hold, and where issues of quality, economy, and democracy have been publicly discussed. All three sectors have been particularly exposed to managerialist thinking over the past three decades and present ideal cases to explore tensions between “government by rules” and “governance by numbers”. The database starts in 1985 as it aims to assess the impact of new public management reforms that began in the 1980s on the development of performance indicators. Indicators were then re-assessed every ten years to capture their development over time (1995, 2005, 2015). One challenge we faced was to identify empirically what counts as an indicator. Indicators are often based on a compilation of different data assessing performance. They often involve multiple sources of data and various ways of data aggregation, which complicates the task of identifying what counts as an indicator (or its sub-component). In addition, some indicators are more easily accessible than others. For the purpose of compiling this database, we identified and selected indicators through two main methods. First, we reviewed different primary sources where indicators are published (official reports, websites, etc.). Second, we complemented our search with a review of secondary sources (academic articles, books, etc.) to check for completeness and gain information about indicators that was otherwise not available. As highlighted above, the database is aimed at being as comprehensive as possible, however, it does not (and cannot) provide a complete overview of all indicators that may have existed at the time.

This dataset shows the number of people that are in prison by state in 2006 and 2007. These numbers are then compared to show the difference between the two years and a percentage of change is given as well. This data was brought to our attention by the Pew Charitable Trusts in their report titled, One in 100: Behind Bars in America 2008."" The main emphasis of the article emphasizes the point that in 2007 1 in every 100 Americans were in prison. To note: Many states have not completed their data verification process. Final published figures may differ slightly. The District of Columbia is not included. D.C. prisoners were transferred to federal custody in 2001

This dataset shows the total amount of State Prison Expenditures for Medical Care, Food expenses, and Utilities in the year 2001. Over a quarter of prison operating costs are for basic living expenses. Prisoner medical care, food service, utilities, and contract housing totaled $7.3 billion, or about 26% of State prison current operating expenses. Inmate medical care totaled $3.3 billion, or about 12% of operating expenditures. Supplies and services of government staff and full-time and part-time managed care and fee-for service providers averaged $2,625 per inmate, or $7.19 per day. By comparison, the average annual health care expenditure of U.S. residents, including all sources in FY 2001, was $4,370, or $11.97 per day. Factors beyond the scope of this report contributed to the variation in spending levels for prisoner medical care. Lacking economies of scale, some States had significantly higher than average medical costs for everyone, and some had higher proportions of inmates whose abuse of drugs or alcohol had led to disease. Also influencing variations in expenditures were staffing and funding of prisoner health care and distribution of specialized medical equipment for prisoner treatment. Food service in FY 2001 cost $1.2 billion, or approximately 4% of State prison operating expenditures. On average nationwide, State departments of correction spent $2.62 to feed inmates each day. Utility services for electricity, natural gas, heating oil, water, sewerage, trash removal, and telephone in State prisons totaled $996 million in FY 2001. Utilities accounted for about 3.5% of State prison operating expenditure. For more information see the url source of this dataset.

This dataset shows the total amount of expenditures and operating costs that states spent on inmates in the fiscal year of 2001. Correctional authorities spent $38.2 billion to maintain the Nation's State correctional systems in fiscal year 2001, including $29.5 billion specifically for adult correctional facilities. Day-today operating expenses totaled $28.4 billion, and capital outlays for land, new building, and renovations, $1.1 billion. The average annual operating cost per State inmate in 2001 was $22,650, or $62.05 per day. Among facilities operated by the Federal Bureau of Prisons, it was $22,632 per inmate, or $62.01 per day. In a followup to a study based on FY 1996 data, this report presents unique statistics on the cost of operating State prisons in FY 2001. Information was obtained by extracting corrections data from each State's responses to the U.S. Census Bureau's annual Survey of Government Finances. Item categories were standardized across jurisdictions, and reported figures were verified with State budget officials. For more information please see source url.

This dataset displays the locations of all the Adult Correctional Facilities in the state of New York as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Rhode Island as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of North Carolina as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of West Virginia as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Hawaii as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Montana as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Wisconsin as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Wyoming as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Louisiana as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Arkansas as of 3.2008. This includes both female and male institutions.

This dataset displays the locations of all the Adult Correctional Facilities in the state of Arizona as of 3.2008. This includes both female and male institutions.