Since 2001, Vermont Department of Corrections (DOC) sex offender treatment providers and probation and parole officers have scored every adult male sex offender under community supervision on three measures of static (unchangeable) risk at intake (i.e., Static-99, RRASOR-Rapid Risk Assessment for Sex Offence Recidivism, and VASOR-Vermont Assessment of Sex Offender Risk) and one measure of dynamic (changeable) risk (i.e, SOTNPS) at intake and then every six months thereafter. This project conducted record reviews to verify the accuracy of the risk assessment scores and examined how scores on the Sex Offender Treatment Needs and Progress Scale (SOTNPS) and one or more of these static risk instruments can be combined into an overall model of risk assessment. An empirically derived decision-making model was created to assist correctional administrators, probation and parole officers, and treatment providers in allocating and delivering supervision and treatment services based on an individual's treatment needs and risk to sexually re-offend. Three hypotheses were tested. First, it was expected that one or more static risk measures (Static-99R, Static-2002R and VASOR) would predict sexual recidivism with moderate accuracy in the sample. Second, a dynamic risk measure, Sex Offender Treatment Needs and Progress Scale (SOTNPS), or a subset of risk factors contained in this measure would also predict sexual recidivism with moderate accuracy and be sensitive to the changes in dynamic risk over time. Third, a combined static and dynamic risk measure would predict sexual recidivism more accurate than either measure alone.

The aim of the study was to evaluate and to improve the decision-making algorithms that have been generated to assess risk in sexual offenders. More specifically, it was the task of this research project to evaluate the extant actuarials in a sample of sexual offenders on whom long-term follow-up data were available. Researchers attempted to assess the comparative accuracy of the major risk instruments over time and over subsamples, explore their underlying factor structure, examine the accuracy of a new assessment protocol, and explore the potential for generating improved predictive instruments. The sample was drawn from an earlier study in which researchers had followed 599 offenders who had been referred to the Massachusetts Treatment Center (MTC) for evaluation between 1959 and 1984. Of these, 266 (the Bridgewater Treatment [BT] sample) had been committed to MTC as "sexually dangerous" and subsequently released, and 333 (the Bridgewater Observation [BO] sample) had been determined not to be sexually dangerous and returned to finish their sentences. There were two sources of data for the study. The first source was the offender's MTC clinical and criminal archival records. The second comprised four record sources that were accessed to obtain comprehensive follow-up data. In this study, researchers coded these records both on modern empirically-derived, mechanical actuarials that have been developed since 1997 for predicting sexual recidivism, and on a new experimental measure. Two coding teams were created. In general Team A was responsible for (a) purifying, redacting, and scanning detailed copies of offenders' files, (b) classifying all BO sample using both the MTC typologies and the DSM-IV Conduct Disorder and Antisocial Personality Disorder categories, and (c) classifying a subset of the BT sample using the DSM-IV Conduct Disorder and Antisocial Personality Disorder categories. Team B was responsible for coding all actuarials and the Psychopathy Checklist-Revised on all offenders in the study, and for classifying all BT sample using the DSM-IV Conduct Disorder and Antisocial Personality Disorder categories.

The NLSY97 standalone data files are intended to be used by crime researchers for analyses without requiring supplementation from the main NLSY97 data set. The data contain age-based calendar year variables on arrests and incarcerations, self-reported criminal activity, substance use, demographic variables and relevant variables from other domains which are created using the NLSY97 data. The main NLSY97 data are available for public use and can be accessed online at the NLS Investigator Web site and at the NACJD Web site (as ICPSR 3959). Questionnaires, user guides and other documentation are available at the same links. The National Longitudinal Survey of Youth 1997 (NLSY97) was designed by the United States Department of Labor, comprising the National Longitudinal Survey (NLS) Series. Created to be representative of United States residents in 1997 who were born between the years of 1980 and 1984, the NLSY97 documents the transition from school to work experienced by today's youths through data collection from 1997. The majority of the oldest cohort members (age 16 as of December 31, 1996) were still in school during the first survey round and the youngest respondents (age 12) had not yet entered the labor market.

This study was undertaken to investigate the relationship, if any, between drug treatment and success or failure of drug-involved offenders on probation/community supervision. Further, the researchers sought to evaluate the outcomes of drug-involved offenders admitted to (1) secure residential substance abuse treatment (RSAT) programs, (2) non-secure residential drug treatment programs, (3) non-residential drug treatment programs, and (4) no drug treatment programs. Data were collected from administrative records provided by the Florida Department of Corrections, specifically case history records of offenders admitted to supervision in the community from July 1, 1991, through June 30, 1997. Part 1 is comprised of all cases admitted to community supervision between July 1, 1991, and June 30, 1993 (fiscal years 1991 and 1992) and treated in a secure residential drug treatment program. Part 2 is comprised of all cases admitted to community supervision from July 1, 1991, through June 30, 1995, receiving treatment in a non-secure residential drug treatment program. Part 3 contains data on offenders admitted to non-residential drug treatment programs, whose community supervision admissions were between July 1, 1991, and June 30, 1993. Part 4 contains data on offenders admitted to non-residential drug treatment programs, whose community supervision admissions were between July 1, 1993, and June 30, 1995 (fiscal years 1993 and 1994). Part 5 contains data on cases admitted to community supervision between July 1, 1991, and June 30, 1993, who did not receive drug treatment of any kind. Cases admitted to community supervision between July 1, 1993, and June 20, 1995, receiving no drug treatment are contained in Part 6. Each supervision admission record contains a history of subsequent court actions that were complete through December 31, 1997. Variables for all parts include population estimates, unemployment rates, population by age-specific categories, violent and nonviolent index offenses, per capita personal income, clearance rates, split sentence flag, primary offense disposition, primary offense felony level, current commitment years supervised, supervision type, whether current offense included a drug charge, number of prior supervision terms, number of prior commitments, reasons for failure, treatment facility code, number of drug sale/traffic offenses, outcome of supervision period, and reasons for prison intake. Demographic variables include race and gender.

The purpose of this data collection was to measure the validity or accuracy of four recidivism prediction instruments: the INSLAW, RAND, SFS81, and CGR scales. These scales estimate the probability that criminals will commit subsequent crimes quickly, that individuals will commit crime frequently, that inmates who are eligible for release on parole will commit subsequent crimes, and that defendants awaiting trial will commit crimes while on pretrial arrest or detention. The investigators used longitudinal data from five existing independent studies to assess the validity of the four predictive measures in question. The first data file was originally collected by the Vera Institute of Justice in New York City and was derived from an experimental evaluation of a jobs training program called the Alternative Youth Employment Strategies Project implemented in Albuquerque, New Mexico, Miami, Florida, and New York City, New York. The second file contains data from a RAND Corporation study, EFFECTS OF PRISON VERSUS PROBATION IN CALIFORNIA, 1980-1982 (ICPSR 8700), from offenders in Alameda and Los Angeles counties, California. Parts 3 through 5 pertain to serious juvenile offenders who were incarcerated during the 1960s and 1970s in three institutions of the California Youth Authority. A portion of the original data for these parts was taken from EARLY IDENTIFICATION OF THE CHRONIC OFFENDER, [1978-1980: CALIFORNIA] (ICPSR 8226). All files present demographic and socioeconomic variables such as birth information, race and ethnicity, education background, work and military experience, and criminal history, including involvement in criminal activities, drug addiction, and incarceration episodes. From the variables in each data file, standard variables across all data files were constructed. Constructed variables included those on background (such as drug use, arrest, conviction, employment, and education history), which were used to construct the four predictive scales, and follow-up variables concerning arrest and incarceration history. Scores on the four predictive scales were estimated.

The current study focused on 479 men and women from South Carolina who were enrolled as participants in the Serious and Violent Offender Reentry Initiative (SVORI) multi-site program evaluation shortly before prison release in 2004 or 2005. The original SVORI data suggested that the South Carolina respondents were similar to the multi-site sample with "committed to not going back to prison" as the most common reason for desisting and using drugs or alcohol as the most common reason for persisting. The goals of the current study were to (1) update information on the current status of these individuals across multiple domains (e.g., housing, employment, substance use); (2) gather additional administrative recidivism data to examine long-term offending; and (3) acquire information about the factors individuals associated with their decisions to desist from criminal activity, as well as circumstances associated with renewed criminal activity or desistence. Interviews were conducted with those that the study team were able to locate and additional administrative arrest and incarceration data were acquired for the full sample, providing recidivism follow-up over at least a 10-year period. Official administrative data were obtained from the South Carolina Law Enforcement Division (rearrests) and South Carolina Department of Corrections (reincarcerations). Arrest data span the entire arrest history (from first arrest through December 2015); reincarceration data span the period between the SVORI study prison release in 2005 and 2006 through June 2014. These data were obtained for the full sample of 479 South Carolina SVORI participants. Three components of interview data were collected. Desistance study interview data: 1 wave of in-person interviews was conducted with 208 study subjects who consented to participate in an interview. The research team used computer-assisted personal interviewing (CAPI) to administer the survey, and interviews were conducted from September 2016 through March 2017. Life event data: The Life Events Calendar (LEC) is a tool used in qualitative and quantitative research to gather retrospective information about a person's life, experiences, and history. The approach is based on autobiographical memory and how entering events on a calendar or page help facilitate memory recall. LECs typically encompass periods of 5 years or less; this study's LEC covered a 10- to 12-year span to allow analysis since last contact with the study cohort. Data were collected from the 208 subjects who consented to be interviewed. SVORI interview data: This inventory includes files with select baseline and outcome data (e.g., self-reported employment, drug use, criminal behavior) for desistance study subjects who responded to follow-up interviews at Wave 2 (3-month), Wave 3 (9-month), and Wave 4 (15-month). This collection of administrative and interview data is organized into 14 data parts. Demographic data includes information on age, gender, race, and education.

This study investigated the ways in which active offenders and their behavior patterns are related to individual characteristics. Data were collected to explore topics such as the nature of individual offending behavior, including offense mix and specialization, the frequency of offending, and the characterization of offender types. To address these issues, the post-release arrest patterns of two cohorts of male youths paroled by the California Youth Authority in 1981-1982 and 1986-1987 were examined. The project focused on modeling the frequency of recidivism and the correlates of arrest frequency. The frequency of arrest was measured during two periods: the first year following release and years two and three following release. Criminal justice variables in this collection provide information on county-level crime and clearance rates for violent and property crimes known to the police. Measures of parolees' criminal history include length of incarceration prior to current commitment, frequency of arrest, age at first arrest, and calculated criminal history scores. Personal and family characteristics include previous violent behavior, alcohol and drug abuse, family violence, neglect or abuse, degree of parental supervision, parental criminality, education, and school disciplinary problems. Demographic variables include age and race of the subjects.

The purpose of the project was to (1) determine whether the combined dynamic (SOTIPS) and static risk assessment (Static-99R) tools better predicted sexual recidivism than either alone, and (2) determine whether the tools could be implemented successfully in more representative populations. Previous research has established a "status quo" for risk assessments. This study was set within the context of the developing sexual offender risk prediction field, where investigators explored reliable and valid means to assess what have been termed "dynamic risk factors." Instruments that identify the specific psychological risk factors present in the individual offender ought to allow treatment for that individual to be tailored to these specific needs, thus increasing its effectiveness. Thus, instruments have been designed to: Assess psychological factors that are empirically related to sexual recidivism, thus creating a basis for selecting treatment targets Show robust incremental predictive validity relative to Static-99R or other measures of static risk factors Measure change in a way that is convincingly related to sexual recidivism Incorporate and point risk managers towards some of the factors identified in the desistance literature Improve the effectiveness of treatment in reducing sexual recidivism Enrollment of sex offenders in the evaluation study began in April 2013. To be included, offenders needed to be Static-99R eligible (an adult male convicted of a contact or non-contact sex offense with an identifiable victim), mentally cognizant, released to community supervision, and at least 18 years old in January 2013 in Maricopa County and April 2013 in New York City.

This study involved a survey of juvenile court judges, chief probation officers, prosecutors, and public defenders to measure their impressions of recent policy changes and the critical needs facing today's juvenile justice system. In addition the study garnered recommendations for improving the administration and effectiveness of this system. The study's primary objective was to provide policymakers, administrators, and practitioners with actionable information about how to improve the operations and effectiveness of the juvenile justice system, and to examine the role practitioners could play in constructing sound juvenile justice policy. A total of 534 juvenile court judges, chief probation officers, court administrators, prosecutors, and defense attorneys in 44 states and the District of Columbia participated in the Assessing the Policy Options (APO) national practitioner survey. The survey consisted of four major sections: demographics, critical needs, policies and practices, and practitioner recommendations. Critical needs facing the juvenile justice system were measured by asking respondents about the policy priority of 13 issues in their respective jurisdictions; topics ranged from staff training and development to effective juvenile defense counsel to information technology. Respondents were also asked to assess the effectiveness of 17 different policies and practices -- ranging from parental accountability laws to transfer and treatment -- in achieving 6 vital juvenile justice outcomes.

In nearly every state and in the vast majority of juvenile justice agencies, risk assessments are incorporated into diversion, case management, supervision, and placement practices. Despite two decades of use within the juvenile justice system, little research regarding the methods of risk assessment development is discussed or translated to the field and practitioners. Many of the contemporary tools used today are implemented off-the-shelf, meaning that tools were developed with a specific set of methods, selecting and weighting items used in the prediction of a specified sample of youth. What is not known is how the various designs, methods, and circumstances of tool development impact the predictive performance when adopted by a jurisdiction. This study seeks to provide input into this dilemma. Demographic information in this study includes age, race, and sex.