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Prior to 2003, the State of Alabama had no formal methodology to forecast prison populations, including a simulation model or statistical time-series and forecasting methods. Instead, the Alabama Department of Corrections relied on percent growth models, using the existing prison population to forecast future statewide prison populations. As Alabama moved toward a structured sentencing system, more precision was needed to investigate the impact statewide sentencing reform would have on the prison population. Adding to the need for more precise forecast methods, the Alabama Sentencing Commission intended to incorporate Virginia worksheet-style sentencing guidelines into its sentencing reform efforts. The Virginia sentencing guidelines uses offender and offense factors identified with statistical models and weights to guide sentence recommendations. Alabama require an analytical tool to guide the Commission during development of such a complicated sentencing system. To shepherd this process, the simulation model development project was undertaken which consisted of three phases;

• The development of a baseline projection of current practices for later comparison with projections made following implementation of the sentencing standards;
• Incorporating the initial sentencing standards into the simulation model; and
• Integrating disparate modules together into a user-friendly model interface.

The study examined the first five years of operation of Kansas senate bill 123 (November 2003-November 2008) examining individual-level and system-level outcomes over time and across community corrections districts and judicial actors. The study also assesses the impact of SB 123 on the work routines of criminal justice system actors, examining changes in sentencing and supervision practices and interactions across agencies following the implementation of SB 123.

Individual-level impacts of SB 123 on recidivism rates are assessed using sentencing and revocation data collected by the Kansas Sentencing Commission for drug possessors sentenced in Kansas between November 1, 2001 and October 31, 2008 (Dataset 1). Propensity score matching was used to compare the revocation and reconviction rates of drug possessors sentenced to SB 123 with the recidivism rates of similar individuals sentenced to regular probation (standard supervision by community corrections or court services) (Dataset 2). Supervision and program participation data provided by the Kansas Department of Corrections were used to assess the use of drug treatment services, education and employment services, and sanctions for individuals sentenced to SB 123 or standard community corrections (Dataset 3). These quantitative data were complemented by a set qualitative data derived from interviews with SB 123-eligible offenders (Dataset 4), community corrections managers, and courtroom actors (judges, prosecutors, public defenders) (Dataset 5).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

This study examined the extent to which contextual factors influenced variation in sex offender sentencing decisions.

By law, Pennsylvania trial courts were required to submit all felony and misdemeanor convictions under the Pennsylvania Sentencing Guidelines to the Pennsylvania Commission on Sentencing on a yearly basis.

These data were supplemented with county-level data from the American Community Survey, Administrative Office of Pennsylvania Courts' Annual Caseload Statistics of the Unified Judicial System of Pennsylvania, Associated Religion Data Archives, and Pennsylvania Department of State, Voter Registration Statistics Archives.

The collection contains 1 SPSS data file (Cleaned-Data-2015-R2-CX-0039.sav (n=318048; 31 variables)).

Demographic variables include gender, race, and defendant's age at sentencing.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

This study utilized data from the Bureau of Justice Statistics on federal criminal case processing to study jurisdictional variations in prosecutorial decision-making outcomes. It linked information across multiple federal agencies in order to track individual offenders across the various stages of the federal justice system. Specifically, it combined arrest information from the United States Marshall's Service with charging information from the Executive and Administrative Offices of the United States Attorney and with sentencing information from the United States Sentencing Commission. These individual data were subsequently augmented with additional information on federal courts to examine contextual variations in charging decisions across federal jurisdictions.

There are three data files. Dataset 1 (Executive Office for United States Attorneys (EOUSA) and United States Marshals Service (USMS) Data) contains 88 variables and 284,869 cases. Dataset 2 (Administrative Office of the United States Courts (AOUSC) and United States Sentencing Commission (USSC) Data) contains 717 variables and 256,598 cases. Dataset 3 (United States District Court Characteristics Data) contains 6 variables and 89 cases.

Only Dataset 3 is being released as part of the available study materials. Datasets 1 and 2 can be re-created using the syntax files which are included in the study materials.