California Corrections Realignment: Opportunities and Challenges in the Public Policy Institute of California's Multi-county Study. Ryken Grattet March 31 st, 2015
The Data Problem How can researchers (and others who value data) engage with governmental entities to help them generate the kind of data that are necessary for evaluating performance and planning in corrections? 2
3
Challenges and Opportunities Opportunities Dimensions Challenges Prison Downsizing Political Tolerance for bad news Evidence-Based Practice Professional Unseating BAU Accessibility and Power Technological Outdated Systems 4
Outline PPIC Public Safety Realignment The BSCC-PPIC Multi-county Study (MCS) Project 5
6
Postrelease Community Supervision Act of 2011 (AB 109) "Evidence-based practices refers to supervision policies, procedures, programs, and practices demonstrated by scientific research to reduce recidivism among individuals under probation, parole, or postrelease supervision. Cal Penal Code 3450 (b)(7) 7
California State Prison and Parole Populations have declined 8
Control of Correctional Populations Has Shifted to Counties 800000 Number of offenders under control 700000 600000 500000 400000 300000 200000 100000 341584 331270 311692 310809 333786 339894 123597 109026 107667 101143 58718 47717 171085 168830 162821 147578 132935 134339 Probation Parole Prison Jail 0 80011 76128 70649 72131 78878 81262 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12 Dec-13 9
Realignment s new (and some old) tools Post-release Community Supervision (by county probation, instead of state parole) County Jail Felons Flash Incarceration Split Sentencing Encouragement to experiment with programming and enforcement strategies (DRCs, EM, specialized caseloads, specialty courts) 10
If we had to do it over again, we probably would have included a research component to AB109. --Former Secretary of CDCR & current Executive Director of CSAC, Matt Cate We must not only collect data about each new population, but also connect the data to programming types and supervision levels, and determine whether or not an offender has recidivated. --San Diego Deputy District Attorney Lisa Rodriguez The state does not currently have access to reliable and meaningful realignment data to ensure its ability to effectively monitor progress toward achieving intended realignment goals. --California State Auditor 11
BSCC-PPIC Multi-County Study (MCS) Engagement: California State Association of Counties County Administrative Officers Association of California California State Sheriff s Association Chief Probation Officers of California CDCR and DOJ Twelve California Counties Partially Funded by: National Institute of Justice 12
What types of data are needed? Recidivism Arrests, Violations Convictions Returns CI&I Unique ID Services & Sanctions Alternative Sanctions Treatment Background Risk & Needs Offending history
Finding interventions that work ID Controls Intervention Outcome Offender County Demographics Risk Needs Service Recidivism Andre X 32, M, White High SA Y Y Sebastian Y 22, M, Asian High SA Y Y Juan X 45, M, Black High SA N N Steve Z 34, M, White Low Educ N N Erica X 27, F, Latino Moderate MH Y N
15
What questions could be answered with such data? Are recidivism rates (however best defined) going up or down? Do the services we refer people to decrease their recidivism? Is flash incarceration leading to behavior change? Do offenders given split sentences do better, worse, or the same as offenders given straight sentences? Do offenders placed on electronic monitoring do better, worse, or the same as offenders given straight or split sentences? Do we have the right set of service and program options in place? Are their promising evidence based practices being used elsewhere that could benefit our county? 16
Possible research designs Wide range of policy impact, program outcome evaluations, compositional changes, forecasting Within and Across County Variation Lots of controls for matching or regression Quasi-experimental designs (propensity score matching, difference-in-differences, fixed effects) 17
Key Project Phases January 2014- Present Establishing the Pipeline February 2015- June 2015 Expanding the Scope June 2015- December 2016 Maintenance and Transfer 18
Establishing the Pipeline Establish capacity at PPIC to receive and secure a subset of the county probation and sheriff data Standardize and clean data Link data to state sources Produce a report on recidivism, including 1170h recidivism and returns to jail custody 19
2000 PRCS Releases, October 2011-June 2012 1800 1600 1400 1200 1000 CPOC/BSCC CDCR PPIC MCS 800 600 400 200 0 Contra Costa Fresno Humboldt Kern Los Angeles Orange 20
2000 PRCS Releases, October 2011-June 2012 1800 1600 1400 1200 1000 CPOC/BSCC CDCR PPIC MCS 800 600 400 200 0 Sacramento San Bernardino San Francisco Shasta Stanislaus 21
1 0.9 Next Steps 1-Year PRCS Recidivism Rates, October 2011 - June 2012 0.8 0.7 0.6 0.5 57.4% Arrested Convicted Return to Prison 0.4 0.3 0.2 22.9% 0.1 6.5% 0 Contra Costa Fresno Humboldt Kern Los Angeles Orange 22
1 1- Year PRCS Recidivism Rates, October 2011 - June 2012 0.9 0.8 0.7 0.6 57.4% 0.5 Arrested Convicted Return to Prison 0.4 0.3 0.2 22.9% 0.1 6.5% 0 Sacramento San Bernardino San Francisco Shasta Stanislaus 23
Data collection challenges Challenges Example(s) Solutions Incomplete data Services data Risk and needs data Identify necessary steps to capture data electronically and integrate into CMS Linking data Common identifiers Data silos Improved integration of data systems across criminal justice partners (sheriff, probation, jails, courts) Definitional ambiguity Key terms may be defined differently across agencies or counties (e.g., a program, recidivism) Provide standardized definitions and employ the building block approach Aging technology Venders no longer in business Older programming languages Technological patches Funding for technology upgrades 24
State of the Data Report Reasons for collecting data Types of data needed Obstacles to collecting Ways of overcoming those obstacles 25
Next Steps Preparing for Expanding the Scope Phase Working with CDCR and DOJ on how county data will be linked to state data Developing a publication on recidivism (encompassing returns to jail custody and arrest, reconviction, and return to custody of the 1170h) 26
The Data Problem How can researchers (and others who value data) engage with governmental entities to help them generate the kind of data that are necessary for evaluating performance and planning in corrections? Building political support Providing focus to data collection efforts Training locals on how to prepare data Doing the design and testing for them Brokering data flows that leverage existing sources 27
Contact Sonya Tafoya Research Associate Public Policy Institute of California tafoya@ppic.org (415) 291-4470 Ryken Grattet Research Fellow Public Policy Institute of California grattet@ppic.org (916) 440-1123 Mia Bird Research Fellow Public Policy Institute of California bird@ppic.org (415) 291-4471 28