The purpose of the study was to facilitate an understanding of the sanctioning of parolees in California. The central databases used in the study were the Offender Based Information System (OBIS), the Revocation Scheduling and Tracking System (RSTS), and the Statewide Parolee Database (SPDB). These three central databases provided information for the outcome variables of the study as well as information about parolees' personal characteristics, aspects of their supervision, and criminal histories. For the Parole Violations Data (Part 1), these data were combined with data extracted from several California Department of Corrections and Rehabilitation (CDCR) data systems and connected to other pieces of data using administrative and geographic identifiers to construct measures of parole agent and community characteristics. Parole agent and parole policy measures were drawn from the California State Personnel Board Parole Agent Database (PACD) and California parole policies. Measures of community conditions were drawn from the 2000 United States Census, the United States Substance Abuse and Mental Health Services Administration (SAMHSA), the California Secretary of State, and the Religious Congregations and Membership Study, 2000. A total of 13,070 parolees were observed for a maximum of 106 weeks during 2003-2004, yielding a total of 1,376,820 parolee-week observations for Part 1. The Parole Revocations Data (Part 2) include every parole violation case that went through a county court or a parole board hearing in 2003 and 2004 -- a total of 151,586 cases. Individual, organizational, and community-level data were merged into the Part 2 dataset using administrative and geographic identifiers. Information about each parolee was extracted from several CDCR data systems. Similar to Part 1, the central databases used in Part 2 of the study were the OBIS and the RSTS. Organizational measures were drawn from CDCR Annual Population Reports, California Corrections Standards Authority Jail Profile Surveys, and Judicial Council of California Court Statistics Reports. Measures of community conditions were drawn from the 2000 United States Census, the SAMHSA, and the California Secretary of State. The Parole Violations Data (Part 1) contain a total of 50 variables including past and present offense history variables, parolee characteristics, supervision characteristics, and community environment variables. The Parole Revocations Data (Part 2) contain a total of 42 variables including case characteristics, individual characteristics, organizational factors, and community factors.

This study was divided into two phases. The first assessed the effects of different sanctions on separate criminal populations, focusing on probation as a sentencing alternative for felons. The second phase used a quasi-experimental design to address how imprisonment affects criminal behavior when criminals are released. Specific issues included: (a) the effect that imprisonment (vs. probation) and length of time served have on recidivism, (b) the amount of crime prevented by imprisoning offenders rather than placing them on probation, and (c) costs to the system for achieving that reduction in crime.

This study was undertaken to examine the ways in which different felony sanctions impact the future behavior of felony offenders. The study sought to determine whether the following made a difference in subsequent criminal behavior: (1) sentences of confinement, (2) the length of sentence (both the sentence imposed and that which was actually served), and (3) sentences of probation combined with jail ("split" sentences), or combined with fines, restitution, or other alternative sanctions. Data were collected from questionnaires completed by 18 judges of the Essex County, New Jersey, courts and by probation staff. Follow-up data were collected from official records provided by probation, jail, prison, and parole case files. Follow-up data were also collected from the following official records: (1) the New Jersey Offender-Based Transaction System Computerized Criminal History, (2) the New Jersey Department of Corrections Offender-Based Correctional Information System, (3) the United States Department of Justice Interstate Identification Index, (4) the National Crime Information Center Wanted Persons File, (5) the New Jersey PROMIS/GAVEL Prosecutors Case Tracking System, and (6) administrative record files of the New Jersey Department of Corrections. Variables in the data file include the most serious offense charge, most serious offense of conviction, dimension of conviction, offense type (person, property, social order, fraud, or drug offense), number of prior probations, number of probation revocations, number of prior jail and prison terms, mitigating and aggravating factors affecting the sentence, type of sentence, special conditions of probation, fines and restitutions imposed, minimum and maximum incarceration terms (in months), history of drug offenses, type of drugs used, probation and parole violations, total number of prior arrests and prior convictions, and longest arrest-free period after first arrest. The type of post-sentence offense, dimension, disposition charge, sentence, and date of arrest are provided for arresting events and charge episodes 1 through 108 for any offender. For up to 43 arrest events (for any offender), the date of lockup and date of exit from confinement are provided. The file also includes recommendations made by prosecutors and probation officers, and judges' ratings (on a scale of one to nine) with respect to the likelihood of an offender committing future property crimes, crimes against persons, or any crime. Judges also rated the arrest record length, conviction record length, and social stability of each offender. Retribution points, incapacitation points, and specific deterrence points assigned by the judges complete the file. Demographic variables include the race and sex of each convicted offender, and the age of the offender at first conviction.

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 Probationers in Recovery (PIR) program, developed by the San Diego County Probation Department, targeted high-risk, drug-abusing offenders with the goal of controlling offender behavior without increasing risks to communities. This evaluation of PIR was based on a quasiexperimental design that compared program activities and outcomes for two matched groups of high-risk probationers receiving different levels of service and supervision. The assessment included both a process evaluation to discover if expected service levels were implemented as designed, and an impact evaluation to assess the effectiveness of drug treatment within an intensive community supervision program. The experimental group included 209 PIR participants who received intensive community supervision and drug treatment, and the control group consisted of 151 probationers who were assigned to regular high-risk probation caseloads and who met the PIR screening criteria. The samples were selected from probationers entering community supervision from February to December 1991. The length of the PIR program varied, but for purposes of analysis the minimum time in the program to represent the intervention period was set at eight months, including relapse prevention. A comparable period was used for the control group. The subsequent six-month period was used to measure the effects of PIR and regular high-risk probation after intervention. Intake interviews were conducted with a subsample of 96 probationers in PIR and 80 in the control group (Part 1). The interviews were conducted within the first two weeks after intake. Follow-up interviews were conducted with these probationers after they had completed eight months of PIR or regular high-risk probation to measure experiences on probation and changes in behavior and attitudes (Part 2). Follow-up interviews were completed with 47 probationers from the experimental group in the PIR program and 35 in the control group. The case tracking portion of the study involved the review of probation, treatment, and state and local criminal history files (Part 3). Data on technical violations and arrests for new crimes were compiled for the following time periods: (1) six months prior to the instant offense (the baseline), (2) the first eight months of community supervision (the in-program period), (3) the six months after intervention, and (4) the combined 14-month period. The initial interview (Part 1) included questions regarding sociodemographic characteristics, current offense, awareness of probation conditions ordered, perceived consequences for violations of probation, drug use and drug history, prior drug treatment and treatment needs, criminal history, expectations regarding the probation term, opinions regarding probation and treatment, daily activities prior to the current offense, current life satisfaction, and prospects for the future. Questions on the follow-up interview (Part 2) focused on changes in probationers' personal lives (e.g., employment, income, education, marital status, living situation, and relationships with family and friends), technical probation violations and new offenses committed during the eight-month period, sanctions imposed by probation staff, contacts with probation and treatment staff, changes in drug use and daily activities, expectations with regard to remaining crime- and drug-free in the future, attitudes regarding probation and treatment, treatment needs, and significant life changes over the eight-month period. Variables in the tracking data file (Part 3) include sociodemographic characteristics, current offense and sentence imposed, probation conditions ordered, drug use history, offense and probation violations occurring before, during, and after an eight-month probation period, custody time, changes in level of probation supervision, and program interventions such as drug tests, services delivered, and sanctions imposed.

This research was designed to determine whether the supervision of misdemeanant probationers was cost-effective for increasing the level of successful probation completions in Hamilton County, Ohio. The primary objective was to examine the relationships among these factors: supervision costs, the collection of court costs, fines, and restitution, types of supervision, risk assessment, and probationer conduct for the population of probationers. Probationers were initially classified according to risk assessment and then randomly assigned to a supervision category. The probationer's risk potential was a numerical score derived from demographic background variables, prior record, and history of substance use. The DSCP (Degree of Successful Completion of Probation) was developed specifically to measure probationer conduct and to compare trends and relationships. The variables examined in the study include: risk assessment at intake, supervision level assigned, number of times the probationer was assigned to probation, start and planned termination dates, date of last status change, status at termination, degree of successful completion of probation achieved, costs incurred in administering probation, and amounts collected from each probationer for court costs, restitution, and fines. Although data were collected on 7,072 misdemeanant probation experiences, there are only 2,756 probationers included in the study. The remaining 4,316 cases were excluded due to failure of the probationer to show up for screening or for other reasons that did not meet the research criteria.

These data were gathered to investigate the usefulness of statistical methods, particularly multiple-regression analysis, in predicting repeat criminal activity subsequent to an individual's release from prison. The data collection consists of follow-up information, collected in 1988, on a sample of males released from California prisons. The follow-up study identified criminal activity subsequent to individuals' release from prison through 1988. Predictor variables include age, prior periods of arrest, history of drug use, seriousness of original offense, and number of arrests for nuisance, person, property, and fraud offenses.

In 1996, the Los Angeles County Probation Department developed a set of six instruments to better assess offender risks and needs. Each instrument was intended to serve a specific purpose, with separate instruments used for adult and juvenile populations and release and placement decisions. The instruments were to be completed by probation staff. These instruments were tested in a pilot project by probation field staff in 1997. The probation department then asked RAND to re-examine the six instruments for instrument integrity, use of overrides, and relationship to long-term recidivism outcomes. The probation department's research staff had completed the instruments between April and December 1997 using available reports and case file information. RAND's involvement in the study began after all samples had been selected and instruments completed. The probation department gave RAND the data on instrument scores. Recidivism data were gathered at 6, 12, and 18 months after the instruments' administration. For juveniles data on the nature and date of arrest were available from the Juvenile Automated Information files. Data on adult re-arrests were unavailable, but the Adult Probation System provided the date, nature, and disposition of offenses referred to probation.

The purpose of this study was to evaluate the effectiveness of an Intensive Probation Supervision (IPS) program on high-risk offenders. The IPS program was characterized by four changes in usual procedures: (1) increased supervision, (2) risk/needs assessment for substance abuse, employment, and marital/family relationships, (3) stricter enforcement of probation, and (4) a four-stage revocation procedure for technical violations. The investigators also studied whether the additional caseload of the probation officers who implemented the IPS program reduced the number of supervision contacts with non-IPS probationers under normal minimum, moderate, and maximum supervision regimens. Offenders put on IPS probation in 1985 from 13 experimental courts were compared to high-risk offenders put on regular probation in the experimental courts in 1984, and to high-risk offenders on regular probation from 13 control courts for both 1984 and 1985. Data were derived from risk assessment forms, needs/strengths assessment forms, probation supervision records, and criminal history data obtained from the state's probation central field. For each offender, a full range of data were collected on (1) offender risk characteristics at initial, four-month, ten-month, and termination assessments, (2) offender needs characteristics at the same intervals, (3) probation officer/offender contact chronologies for the entire one-year follow-up period, and (4) offender prior criminal history and recidivism during a one-year follow-up period.

These data were collected to examine the practices and views of state trial court judges with respect to their use of fines as a criminal sanction. Respondents were asked about the composition of their caseloads, sentencing practices (including fines imposed for various circumstances), available information about the offender at time of sentencing, enforcement and collection procedures in their courts, and their attitudes toward the use of fines. In addition to questions concerning the judges' use of fines and other sanctions, the questionnaire presented the judges with hypothetical cases.