Description of original award (Fiscal Year 2005, $282,835)
California leads the nation in sending people on parole back to prison, and parole violators now represent 67% of all admissions to California prisons. This research will examine how parolee behavior, parole unit activities, the characteristics of parole staff, and community conditions affect the failure rates of parolees. This knowledge will inform policy in terms of the length and degree of supervision required for parolees of different risk levels and the characteristics of parole officers and the units in which they work that produce the best results during parole supervision. Specific objectives of the study include: 1) What proportions of parolees are violated by their parole officers, have revocations, and commit new crimes; what types of offenders are more or less likely to fail; and within what time frame are they more or less likely to fail; 2) How the characteristics of parolees who technically violate their supervision differ from those who commit a new crime; 3) The characteristics of parolees who survive their first 13 months of supervision and are then eligible for release; 4) The relationship between technical violations and the commission of new crimes; 5) At what point the risk of failure while on parole diminishes for what types of offenders; and 6) The individual and contextual factors of the parole office and community that affect failure on parole.
The grantees will continue to assemble a dataset from the California Department of Corrections' administrative records of parolee behavior, as well as data on parole units, parole officers, and the communities within which parolees are released. These data track violations, revocations, and arrests for the roughly 120,000 parolees in California from 2003-2004. A descriptive analysis will identify the basic patterns of violations, revocations, and new arrests for selected types of offenders. A hierarchical hazard model will reveal the parolee background, unit, and community factors that affect each of these outcomes. Together these analyses will show how unit and community factors contribute to the probability a parolee will violate parole, have their parole revoked, and/or commit new crimes; whether technical violations are predictive of new criminal acts; and whether parole agents and units recommend revocation under similar conditions.
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