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string(57320) "Do Local Realignment Policies Affect Recidivism in California ? August 2014 Mia Bird and Ryken Grattet with research support from Daniel Krimm, Brandon Martin , and Alexander Becker Summary California is now completing the third year of one of the most ambitious correctional reforms it has ever carried out , A ssembly Bill 109, known as “p ublic safety realignment .” When the state legislature approved this sweeping overhaul in 2011, which transferred authority over lower- level felons from the state prison and parole system to the count y jail and probation systems, it had few alternatives . A federal court had ordered California to sharply cut back priso n overcrowding because of the state’s failure to provide inmates adequate health care . Lawmakers were also under pressure to reduce skyrocketing prison costs and California’s historically high recidivism rate . In other words, California had to fundamentally redesign its correctional system under urgent and pressing circumstances that left little time for study and deliberation . In the months between the passage of realignment and its implementation, counties had to quickly develop strategies to manage the new population of offenders that would now be held and supervised locally. Realignment was motivated , in part, by the idea that “locals c an do it better ”—that counties would be able to reduce the recidivism rates of lower -level offenders more ef fectively than the state prison and parole system. This report examines this issue in two ways. First, it looks at whether realignment reduced recidivism among a particular group of offenders —the Post-Release Community Supervision (PRCS) population , a segm ent of the released prisoner population with current sentences for offenses that are neither serious nor violent. Before realignment, these types of offenders were under the state parole system and now they are supervised by county probation authorities . We find that the post -realignment period has not seen dramatic changes in rearrests or reconvictions among this population, a finding in line with recent research focused more broadly on this topic ( CDCR 2013; Lofstrom, Raphael, and Grattet 2014 ). For the PRCS population, we estimate that felony rearrest s increased 4.7 percentage point s and felony reconvictions increased 1.9 percentage points following realignment. However, these increases are likely due to the elimination of the option to use parole revoc ation to return offenders to prison . Second, the report examines variation across counties in realignment implementation policies . Under realignment, the state provided counties with $400 million dollars to help cover their increased workload. C ounties were required to submit plans describ ing how they would implement realignment, but they had wide dis cretion in which programs to adopt and how to allocate these funds . These choices appear to have mattered. When we examine the relationship between the polici es counties chose to implement and changes in recidivism under realignment, we find that offenders did better in counties that emphasized reentry services . We find that recidivism increased over the realignment period for PRCS offenders released to counties with implementation policies that prioritized enforcement relative to those released to counties with policies that prioritized reentry services. We estim ate the change in the felony rearrest rate under realignment was 3.7 percentage points greater for offenders released to counties with enforcement -focused plans than for those released to counties with reentry -focused plans . The felony reconviction rate followed a similar pattern. We find the change in the felony reconviction rate was 1.7 percentage points greater for offenders released to counties with enforcement -focused plans. It is important to interpret these findings with caution . The available data limits our analysis to only one segment of the realigned offender population, t hose released from state prison and supervised by county probation. In addition, o ur analysis focuses on the first year of realignment, during which c ounties faced a momentous change and had limited time to design and implement realignment plans. We also relied on realignment plans and budget allocations submitted to the s tate, which may not provide a complete view of http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism in California? 2 county strategic approaches. Nonetheless, these plans and budget allocations represent important policy levers available to county leaders. Finally , we deliver these findings with caution because there may be factors at work that we were unable to observe in this study and that explain, in part, differences across counties in recidivism outcomes. While this study offers a first look into the r elationship between county imp lementation policies and recidivism, w e expect to be able to learn a great deal more as better data become available . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism in California? 3 Contents Summary 2 Figures 5 Tables 5 Abbreviations 6 Introduction 7 Recidivism under Realignment 9 Defining and Measuring Recidivism 9 Early Research on Realignment and Recidivism 10 Defining the Realignment Population 10 Recidivism Varies Over Time and Across Counties 11 Statewide Effects of Realignment on Re cidivism 14 Realignment Implementation Plans and Budgets 16 First-Year Realignment Implementation Plans 16 First-Year Realignment Budget Allocations 17 Categorizing Implementation Policies Based on Plans and Budgets 19 Effects of Realignment Policies on Recidivism 20 Conclusions 21 References 22 About the Authors 23 Acknowledgments 23 A technical appendi x to this paper is available on the PPIC website: www.ppic.org/content/pubs/other/814MBR_appendix.pdf Figures 1. Felony rearrest rates varied widely across counties after realignment 12 2. Felony reconviction rates varied widely across counties after realignment 13 3. Implementation plans varied widely in the types of reentry services emphasized 17 4. Implementation plans varied widely in their resource allocations 18 Tables 1. Implementation plans cluster into two categories 19 http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 5 Abbreviations 1170(h) The penal code designation for felons convicted of non-violent, non-serious, or non- sexual crimes who u nder realignment serve sentences in county jails rather than state prison. BSCC Board of State and Community Corrections CDCR California Department of Corrections and Rehabilitation PRCS Post-Release Community Supervision, county-based supervision of offenders released from state prison . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 6 Introduction October 1, 2011 marked the beginni ng of a new era for corrections and rehabilitation in California . State correctional authorities and their counterparts in 58 count ies began carrying out a fundamental realignment of responsibilities for managing tens of thousands of lower-level felons. This change , known as p ublic safety realignment, represented one of the most far -reaching correctional policy reforms in recent U.S. history. Federal courts had ruled that state prison overcrowding had made it impossible for California to provide inmates a level of health care required by the U.S. Constitution. The state was ordered to cut the prison population to 137.5 percent of design capacity. At the same time, California was facing an acute budget crisis and could no longer afford rapidly rising prison costs. Governor Brown proposed a series of changes that became the basis for Assembly Bill 109, which authorized realignment. T he changes this law ushered in have been described as “revolutionary and sudden” (Weisberg 2011), “the most significant correcti onal reform in decades” (Misczynski 2012), and “the biggest penal experiment in modern history” (Santos 2013). Realignment shifted authority over most non- serious, non-violent, non- sexual offenders from the state to counties and granted counties discretio n over how to manage these offenders. The idea behind realignment was that local governments have better information about what their communities need than the state, and that offenders would do better when held at the local level. Under realignment , state prison and parole populations have dropped dramatically , while county jail and probation caseloads have increased s ubstantially (Lofstrom and Raphael 2013; Petersilia and Snyder 2013). The net result has been lower overall levels of incarceration in California. A key question is w hether realignment can reduce California’s historically high rates of recidivism. Before realignment, California was among the states with the highest parolee rearrest rates (Fischer 2005; Langan and Levin 2002). In the years immediately before the change, some 60 percent of offenders paroled from state prison were arrested in the first year of release. By three year s after release, the re arrest rate reached over 80 percent (CDCR 2012). Even more striking was the proportion of released offenders returned to prison through parole revocations and reconvictions (Grattet, Petersilia, and Lin 2008) , precisely the revolving door t hat realignment sought to stop . Now the majority of offenders who violate terms of release go to county jails or community -based alternative form s of incarceration. T he state provided counties $400 million to help pay their increased correctional costs , but did not dictate how the money sh ould be spent. However, c ounties were required to create implementation plan s that de scribed their realignment strategies and explained how they would use funds provided by the state. These documents provide a unique research opportunity. V ariations across the counties in implementation strategies and spending priorities allow us to see how local correctional policies affected recidivism. T his report consider s two broad policy questions . First, we assess how realignment affected the recidivism rates of the P ost -Release Community Supervision (P RCS) population, the group of lower- level felons released from prison to county probation supervision under realignment . 1 And second , we examine how 1 PRCS is a designation created by AB 109. It refers to offenders whose current commitment offense is not serious or violent and who are not high -risk sex offenders or mentally disordered offender s Prior to realignment this group was not treated as distinct from other prison releases who were sent into the state parole system. Therefore, strictly speaking, PRCS did not exist as a recognized category of offe nders before http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 7 local policy choices affected the recidivism outcomes of this population . We start by reviewing the conceptual and measurement issues surrounding recidivism , as well as the existing literature on realignment and recidivism . Then we analyze the recidivism outcomes of the PRCS population compared with the recidiv ism of their pre- realignment counterparts. Finally, we examine how county realignment plans and budgets varied in how much they emphasize d reentry services versus enforcement , and how those implementation strategies affect ed PRCS recidivism outcomes . realignment. After realignmen t, PRCS are released to county probation departments. This group of offenders is uniquely affected by realignment and thus provides an opportunity to examine the consequences of shifting community supervision from state parole to county pr obation. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 8 Recidivism under Realignment Defining and Measuring Recidivism Among researchers there is widespread agreement about how recidivism should be defined—as a concept. In his book Recidivism, Michael Maltz defines recidivism as “the reversion of an individual to criminal behavior after he or she has been convicted of a prior offense, sentenced, and (presumably) corrected” (2001). This definition closely resembles th at used in The PEW Charitable Trusts’ State of Recidivism repo rt, which regards it as “the act of reengaging in criminal offending despite having been punished” (20 11). The contestation over recidivism emerges not because of lack of agreement about definition, but in terms of how it should be measured. T hree routinel y tracked points in the criminal justice process provide way s to measure recidivism —rearrest, reconviction, and return to custody —and each has its advocates. Rearrest can be subdivided into rearrest for a misdemeanor or felony , or for a supervision violat ion. Criminal rearrest is the most relevant for gauging how a released offender ’s behavior affects public safety . However, rearrest for a crime only happens when that crim e comes to light, the offender is identified as the perpetrator, and is apprehended. To the extent that this leaves out undetected or unreported crimes, it under states the true extent of recidivism. Conversely , to the degree that individuals are arrested for crimes they did not commit, rearrest over states recidivism. Reconviction sets a higher bar. When a released offender is reconvict ed, criminal justice authorities have found enough evidence of a crim e to prosecute or plea bargain . This measure of recidivism is conservative because it omits crim es for which there is insufficient eviden ce or other reasons for not prosecuting. Moreover, r econviction only measures result s of formal criminal prosecution s and does not include administrative parole revocations . Despite these flaws , advocates for us ing conviction as a recidivism measure argue that it covers “validated” criminal activity and better captures recidivism’s impact on local criminal justice resources . Return to custody includes only those released inmates sent back to prison or jail following criminal reconviction or revocation . Offenders may be revoked if they are arrested for a new crime or if they commit a technical violation of supervision rules , such as failure to report to a supervising officer or travel outside of a restricted area . For many years, the California Department of Corrections and Rehabilitation ’s (CDCR) official recidivism statistic was return to the department’s custody. For any given year, CDCR wanted to know how many felons released from its custody came back and occupied a bed with in one, two, or three years . For this purpose, it was not relevant whether the return reflected a new criminal conviction or a parole revocation. By this measure, California had an exceptionally high three- year recidivism rate of more than 65 percent before realignment . The return -to -prison -custody measure had many critics because it included large number s of technical parole violators. Still, it made sense to CDCR because it measured the impact of parole failure on the department’s r esources. Now , under realignment, offenders released from prison can only be revoked to county jail . Revocations generally cannot result in returns to prison and the problem s of return to custody as a recidivism measure have become more apparent . http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 9 Early Research on Realignment and Recidivism In the past fifteen months , the first studies have appeared of the effect s of realignment on recidivism. A CDCR report compar es offenders released from prison in realignment’s first year with those released in the year before realignment. CDCR found that one -year post -realignment returns to prison have dropped from 32 percent to 7 percent (CDCR 2013) , a his torical low. 2 T his is not surprising. Realignment was intended to end the revolving door of parole violators and low -level offenders in to a nd out of prison . CDCR also found that one -year rearrest rates dropped from 59 to 56 percent after realignment , although the proportion of felony rearrests rose from 37 to 43 percent . The average number of rearrests for each offender also rose. Rec onvictions were unchanged , although the proportion of felony reconvictions rose from 57 to 58 percent . PPIC researchers analyz ing CDCR’s data found that offenders released from prison pre - and post - realignment differed in several ways (Lofstrom, Raphael, and Grattet 2014). M ost important was the declining proportion of re turns to prison resulting from parole revocations , which was one of the main goals of realignment . Therefore, release d prisoners were less likely to be “frequent flyers” who cycled in a nd out of prison on parole revocations. After adjusting for these differences in the characteristics of pre- and post - realignment prison releases, t he PPIC study l argely corroborat ed CDCR findings of slight declines in arrests and slight increases in convi ctions, particularly for felonies. Taken together, t he PPIC and CDCR studies suggest: 1) released offenders now return to prison at a historically low rate ; 2) overall rearrests appear to be declining, although the composition and frequency of rearrests is changing; and 3) without parole revocation to send released offenders back to prison, reconvictions are increasing , driven by rising felony re convictions. These changes must be set against a larger context in which reductions to the prison popul ation have saved the state a considerable amount of money . Finally , total incarceration levels have fallen , with a big drop in the state prison population more than offsetting rising numbers in county jails . Lower overall incarceration levels suggest relea sed offenders may be spending more time in the community where they are at risk of committing new crimes. O ur work takes a somewhat different approach. We focus specifically on the PRCS population because they are much more likely, when compared with offenders released from prison to parole, to be affected by county policy choices under realignment . Also, f or the methodological reasons we describe below, we use a six -month observation period rather than a one -year period. As a result, estimates generated from the present work are not directly comparable to the investigations described above. Defining the Realignment Population Realignment delineated three populations of offenders: PRCS . Offenders convicted of non- violent, non- serious, and non- sexual crimes, released from state prison to county supervision instead of state parole . 1170(h) . Felons with no current or prior serious, violent, or sexual convictions , previously subject to state prison sentences and state parole supervision , but now jailed and supervised at the county level . S tate parole . Mentally disordered, high- risk sex offenders , or felons most recent ly convicted of a serious or violent offense. 2 The changes in recidivism cited in this paper are rounded up from CDCR findings to ease readability. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 10 Under realignment, counties manage the PRCS and 1170(h ) populations, but have no responsibility for state parole es unless the y violate the terms of their supervision and are revoked to county jail. The PRCS offenders are of particular interest because, like the pre- realignment prison population , they served t heir sentences in state prison . However, PRCS offenders differ from their pre- realignment counterparts because they are supervised by county probation rather than by state parole. F ocusing on the PRCS population allows us to assess the statewide effect of realignment on PRCS recidivism. At the same time, because the PRCS population is exposed to county supervision strategies, evaluating outcomes for this population provides a window into the role of local policy choices in mitigating recidivism outcomes under realignment . While the 1170(h) population is also exposed to local implementation strategies, the kind of statewide data that would allow for analysis is not currently available for this population . 3 Recid ivism Varies Over Time and Across Counties CDCR data allow us to compare PRCS offenders with similar offenders who left prison before realignment. We selected a control population of prisoners released between October 2010 and March 2011. These offenders were sentenced to prison for crimes that would have put them under PRCS had they been released after realignment took effect. We then selected a PR CS population that left prison between October 2011 and March 2012, the first six months of realignment. We chose t he same release months for both populations to control for seasonal effects and we chose six -month observation periods because doing so allow ed us to conduct further analyses to ensure we account for any preexisting trends in reci divism outcomes. Although r esearch has demonstrated that the largest share of recidivism occurs within 180 days of release (Grattet, Petersilia, and Lin 2008) , we also conduct an analysis of one -year recidivism rates and discuss these findings in the Technical Appendix . Before realignment, we see wide variation in recidivism patterns across California’s counties. S ix-month felony rearrest rate s rang ed from 8 to 35 percent and f elony conviction rates from 1 to 15 percent. After realignment, we see even greater variation in these outcomes . S ix -month felony rearrest rates rang ed from 3 to 53 percent and felony reconviction rates from zero to 1 7 percent in the period that followed realignment . There are many underlying factors, such as local demographic and economic characteristics, that may drive differences in the level of recidivism across counties. Rather than analyze differences in the levels of recidivism, we focus on how recid ivism changed within counties over the time period of realignment. Figure 1 shows the six -month percentage point change in felony rearrest rates in the 39 California counties that supervised at least 30 PRCS offenders . Twelve counties experienced decreases and 27 experienced increases in felony rearrest rates . However, t hese changes might reflect a number of factors, including differences in the post - realignment offender population or variation across counties in realignment implementatio n policies. 3 PPIC is collecting data on 1170(h) offenders as part of a project with the Board of State and Community Corrections. These data should allow us to say m ore about 1170(h) recidivism in the future . http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 11 FIGURE 1 Felony rearrest rates varied widely across counties after realignment SOURCE: Author’s analysis of California Department of Corrections and Rehabilitation (CDCR) prison release data. NOTE: T his figure compares the rearrest outcomes of offenders released from prison to PRCS under realignment (between October 1, 2011 and March 31, 2012) to those of offenders with similar characteristics released from prison to parole before realignment (between October 1, 2010 and March 31, 2 011). -20%-10% 0% 20% Mendocino Humboldt San Luis Obispo San Francisco San Mateo SolanoLake Sonoma Santa Clara Santa Cruz ShastaPlacer Madera Kings Riverside Sacramento Napa San Bernardino Kern Contra Costa Alameda Monterey TulareYolo San Diego Los Angeles MercedSutterButte San Joaquin Yuba El Dorado Tehama Santa Barbara Orange Imperial Fresno Stanislaus Ventura Percentage point change in 6 month felony arrest rate http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 12 Figure 2 shows changes in felony reconviction s after realignment . The six -month felony reconviction rate fell in 14 counties and rose in 25. FIGURE 2 Felony reconviction rates varied widely across counties after realignment SOURCE: Author’s analysis of California Department of Corrections and Rehabilitation (CDCR) prison release data. NOTE: T his figure compares the reconviction outcomes of offenders released from prison to PRCS under realignment (between October 1, 2011 and March 31, 2012) to th ose of offenders with similar characteristics released from prison to parole before realignment (between October 1, 2010 and March 31, 2011). -6%-4%-2% 0%2%4%6%8% Mendocino Napa Humboldt Santa Cruz Riverside San Diego Shasta San Bernardino Yuba El Dorado San Luis Obispo VenturaMerced San Joaquin Placer Sonoma Lake Kings San Francisco Santa Barbara OrangeFresno Tehama Madera Alameda Santa Clara Los Angeles Sacramento Kern Butte Contra Costa Yolo Monterey Stanislaus San Mateo Tulare Imperial Sutter Solano Percentage point change in 6 month felony reconviction rate http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 13 Figures 1 and 2 present trends in recidivism in our data. However, these trends do not adjust for the possible differences in offender characteristics across counties and over time. In the next section, we make these adjustments, allowing us to estimate the effect of realignment on statewide recidivism for the PRCS population . Statewide Effects of Realignment on Recidivism We cannot assume that realignment caused all c hanges in recidivism after October 1, 2011. Researchers must overcome three challenges to estimate realignment ’s effect accurately : The characteristics of the released offender population vary over time. This variation may affect the recidivism levels we observe. For example, i f offender s released after realignment were at lower risk of reoffending than those released before realignment, we might misinterpret lower recidivism outcomes as the effect of realignment . To address possibilit ies like this one, we make adjustments for the changing individual characteristics of the released offender population. Like individuals, counties also vary in their characteristics. Some counties have stronger eco nomies or a wider range of service providers in their communities , and factors like these can affect recidivism outcomes. In addition, the share of released offenders returning to a particular county may vary over time. For these reasons, it is important to adjust for the county of release in a statewide analysis . Finally, c hanges in recidivism may reflect trends already under way in California before Oct ober 1, 2011 and, therefore, we need to be sure to examine any preexisting trends in recidivism before we draw conclusions about the effect of realignment on recidivism. Afte r adjust ing for differences in offender and county characteristics , we estimate that felony rearrest s for the PRCS population increased 4.7 percentage point s and felony reconvictions increased 1.9 percentage points following realignment . In other words, offenders whose supervision shifted from state parole to county probation under realignment were more likely to be rearrested and reconvicted for serious crimes than their pre -realignment counterparts . However, when we u se a broader rearrest measure, includ ing supervision violations, misdemeanors, and felonies , we find no evidence of an increase among the PRCS population after realignment. Although PRCS offenders were more likely to be re arrested for felon ies than their pre -realignment counterparts were, they were less likely to be re arrested for supervision violations and minor offenses. When these measures are combined , the increase in felony rearrests is offset by decreases in other kinds of rearrests. Available data do no t indicate whether these patterns reflect changes in offender behavior or actions of local officials, although it seems likely that the increases in felony arrests and convictions and the corres ponding declines in arrests for supervision violations may result from the removal of the possibility of revocation to state prison. Without the option of revocation to prison, counties may be adjusting their arresting and prosecuting to bring offenders in to the formal criminal justice process (see Loftstrom, Raphael, and Grattet 2014). Reconvictions for the PRCS group follow a different pattern. Even w hen misdemeanor convictions are included, PRCS offenders have high er reconviction rates than their pre -realignment counterparts. We estimate the combined felony and misdemeanor reconviction rate rose 2.3 percentage points after realignment. 4 4 CDCR and PPIC (Lofstrom, Raphael, and Grattet 2014) also found increases in felony arrests and convictions after realignment. Our study and the CDCR and PPIC studies found slight decreases or no difference in r ecidivism for all arrests. PPIC and CDCR looked at all released prisoners, while we analyzed only PRCS offenders and their pre -realignment counterparts. Our study also used somewhat different methodological approaches to detect preexisting trends, including 6 month observation periods rather than one -year http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 14 We then examine the period before Oct ober 1, 2011 to see whether our estimates of changes in recidivism under realignment reflect factors at work before the new system was introduced. We f ind no evidence that felony rearrest and reconviction rates were rising before realignment , but we do find evidence of pre - realignment increases in rearrest and reconviction rates when we use the measures of recidivism that combine arrests for felonies, misdemeanors, and supervision violations as well as convictions for either felonies or misdemeanors . T hese findings suggest realignment induced a shift in both the likelihood of re -offense and the way in which that re -offense would be measured. Before realignment , released offenders arrested for felonies were often revoked and sent back to prison by the p arole board . Now, given that most supervised offenders canno t be returned to prison without a new conviction, r eleased offenders a re more likely to be rearrested and reconvicted in criminal court . While we find that reconviction rates increased overall under realignment, our analysis also suggests some of this increase may have been driven by preexisting trends in statewide recidivism. These findings are presented in greater detail in the Technical Appendix . We now turn to the role of local policy. Our previous analysis showed recidivism outcomes under realignment vary substantially by county. In the next stage of our analysis , we assess the different implementation strategies used by counties and then examine the relationship between those approaches an d recidivism outcomes . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 15 Realignment Implementation Plans and Budgets The state provides substantial funding to cover the cost of managing realigned offenders . Counties are free to determine how to use th ose dollars but were required to develop plan s that detailed their strategic approaches and spending priorities . County Community Corrections Partnerships (CCPs) drafted these plans and submitted them to the state . Created under realignment, t he CCPs are headed by the c hief of p robation and includ e the she riff, the d istrict attorney, the p ublic defender, and criminal justice and social services agenc y representatives . We simplified the plans by first capturing the range of reentry services counties planned to implement. We then added information about how c ounties planned to allocate their realignment funds to fill out the picture for each county. While this approach allows us to examine the impact of broad policy decisions, it does not permit us to study how individual programs, sanction s, or supervision strategies affect ed recidivism rates . First -Year Realignment Implementation Plans To categorize approaches to realignment , we identified the specific reentry service types included in each implementation plan . Figure 3 shows t he prevalence of different ki nds of reentry services. Services consisted of health -related programs , including mental health, substance abuse, and cognitive behavioral therapy; housing and income support services; employment and education services; family and gender- based services; an d peer and community -based serv ices. We also include needs assessment because evaluation of the factors that might lead a released offender to commit new crimes is the first step toward determining what services that person should get. The prevalence of di fferent services varie d. Nearly every plan called for introduc ing or expan ding needs assessment. Similarly, most plans included mental health, substance abuse, and cognitive behavioral treatment components . In other respects , implementation plans ranged considerably . M any included education and housing programs. A minority included new or expanded health care, family, or parenting services. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 16 FIGURE 3 Implementation plans varied widely in the types of reentry services emphasized SOURCE : Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. First-Year Realignment Budget Allocations We also examined how implementation plans document the funds they proposed to allocate to particular areas (Figure 4) . It is challenging to use written budgets to determine where counties actually directed the money because the state did not require standardized reporting methods . We consulted researchers at Stanford Law School , the American Civil Liberties Union , and the Board of State an d Community Corrections on how to classify budget allocations. 5 Ultimately, we arrived at five main spending categories: s heriff, probation, new jail beds, law enforcement, and programs and services. In some cases, fund s for jail expansion came indirectly through the s heriff’s office . In those cases, we moved the funds from the s heriff c ategory to the jail category. Similarly , fund s allocated to the sheriff or probation w ere often redirected to programs and services. In those cases, we put the allocation into the programs and services category . 5 See Lin and Petersilia (2013), American Civil Liberties Union (2012), and BSCC (2013) on categorizing realignment allocations . 0 10 2030405060 Mentorship Gender-based Self Help Restorative Justice Parent Income FamilyHealth Housing Vocational Education Employment Cognitive Behavior Therapy Education Mental Health Substance Abuse Needs Assessment Number of counties http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 17 FIGURE 4 Implementation plans varied widely in their resource allocations SOURCE: Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. Figure 4 shows the range of variation in how counties proposed to allocate their state realignment funds. The boxes represent 50 percent of the counties on each measure, encompassing the quartiles above and below the median (i.e., the counties arrayed between the twenty -fifth percentile and the seventy -fifth percentile). The whiskers to the right and left of the boxes show the range between the minimum and maximum values. The specific patterns of variation include : Programs and services expenditures var ied from zero to 84 percent of total realignment funding . The median was 18 percent . Half the counties directed between 8 and 33 percent to the category. For l aw enforcement , the median expenditure was zero, mean ing that at least half the counties did not allocate any money for this categor y. The highest law enforcement allocation was 23 percent. Jail bed expenditures ranged from zero to 70 percent . Half the counties directed from zero to 19 percent to expanding jail capacity. Expenditures in the s heriff category ranged from zero to 72 percent, with a median of 17 percent . H alf the counties directed between 7 and 30 percent to the sheriff’s office . Probation expenditures varied the most, ranging from zero to 86 percent , with a median of 27 percent . H alf the probation budgets were between 20 and 38 percent. 0% 200% Probation SheriffJails Law Enforcement Programs Percent of total budget allocation http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 18 Categorizing Implementation Policies Based on Plans and Budgets The variation in strategic plans and budgets across counties provides a basis for categorizing differences in approaches to realignment . To create a simple, replicable, and balanced categoriz ation method , we settled on one measure from the budgets and one from the strategic plans. We experimented with a longer list of measur es, b ut this did not improve our ability to clearly delineate differences in implementation strategies. (For more detail regarding our methods, please see the Technical Appendix .) Our budget measure emphasizes custody and law enforcement. W e combined allocations to sheriff’s agencies, jails, and law enforcement to determine to what degree counties directed funds to these areas or made the s heriff responsible for distributing state realignment money . By contrast, o ur measure from the strategic plan s focuses on new or expanded reentry services for PRCS offenders, as described in the previous section. Using these measures, we identified two distinct approaches to realignment implementation : enforcement - focused and reentry -focused. We categorized 19 plans as enforcement -focused and 24 as reentry -focused. We excluded 15 mixed- approach plans from our analysis because there was insufficient support for placing them in either category (see Technical Appendix for further details) . T able 1 shows on average the enforcement-focused plans allocate d more than three times as much realignment money to the sheriff’s agency, jail , and law enforcement than the reentry -focused plans did . Given that budgets are fixed, the share of the budget allocated toward enforcement is directly related to the share allocated toward programs and services in each county. The table a lso shows that enforcement -focused plans averaged slightly fewer reentry services offerings than reentry -focused plans did . TABLE 1 Enforcement - and r eentry -focused i mplementation p lans differ in terms of priorities Budget allocation to sheriffs, jails, and l aw enforcement Number of reent ry services Number of c ounties Enforcement -focused plans 56.1% 8.0 19 Reentry- focused plans 15.3% 8.6 24 Average/Total 33.4% 8.4 43 SOURCE : Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. The enforcement -focused and reentry -focused categories represent distinct approaches to realignment. There are many reasons why the approach to realignment may vary across the state. A county may have emphasized a particular approach in its plan based on evidence or beliefs that that approach will be the most ef fective at reducing the recidivism. However, counties may also have other goals in mind. For example, with the goal of the broader public safety in mind, realignment funding may have been directed to fill the greatest resource gaps in the local correctiona l system. Similarly, effective management may have been a higher- priority goal then recidivism reduction. In this analysis, we focus narrowly on the goal of reducing recidivism among the realigned population. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 19 Effects of Realignment Policies on Recidivism We now consider whether county policies, as reflected in their implementation plans , a ffected recidivism . In this analysis, we adjust for differences in the characteristics of offenders released before and after realignment , as well as differences in offe nder characteristics across counties . We also use an approach that compare s the change in recidivism within the enforcement -focused counties under realignment to the change in recidivism within the reentry -focused counties. This approach accounts for underlying differences in county characteristics. We find that recidivism increased over the realignment period for PRCS offenders released to counties that prioritized enforcement relative to those released to counties that prioritized reentry services . We estimate the change in the felony rearrest rate under realignment was 3.7 percentage points great er for offenders released to enforcement -focused counties than for those released to reentry -focused counties. The felony reconviction rate followed a similar pattern. We find the change in the felony reconviction rate was 1.7 percentage points greater for offenders released to enforcement -focused counties. For the broader recidivism measure including rearrests for felonies, misdemeanors, and supervis ion violations , we estimate the change in the rearrest rate was 1.9 percentage point s greater for enforcement -focused counties. Similarly, the change in reconviction rate, including felonies and misdemeanors, was 2.3 percentage point s greater in enforcement -focused counti es than in reentry -focused counties over the period of realignment . W e checked whether pre- realignment relationship s or underlying trends in the counties that composed our two groups ma y have driven our findings and f ound no evidence that preexisting recid ivism trends influenced our results . It is important to note that we group plans together here to identify statewide patterns in the relationship between local approach es to realignment implementation and changes in recidivism. Because the analysis is at the group rather than the county level, it would be inappropriate to draw conclusions about the specific relationship between an implementation plan in a particular county and the recidivism outcomes of offenders released to that county. Taken together, o ur findings suggest policy approaches to implementation matter under realignment. The recidivism outcomes of PRCS offenders were better in counties that emphasized reentry services in their realignment plans than in those that emphasized enforcement . When the legislature approved realignment, it expressed strong support for the use of evidence- based practices. The preliminary evidence presented here suggests that offenders did better in counties that matched their implementation strategy to this legislative intent. However, given the data limitations, the focus of this work is on a population currently under supervision and, therefore, most likely to benefit from reentry services in the near term. We must also consider the possibility that recidivism outcome s reflect not only offender behavior, but also the degree of monitoring of offender behavior in local justice systems. While offenders in enforcement -focused counties may have higher recidivism rates because they have less access to reentry services, it is also possible that offenders are more likely to be closely monitored in enforcement -focused counties. In that case, higher recidivism rates may reflect higher levels of apprehension rather than higher levels of criminal behavior. It is also important to stress that these findings are preliminary. We will need more data to draw strong conclusions about realignment ’s effects on recidivism . Specifically, researchers need data on individual offender characteristics, criminal histories, reentry services and sa nctions received, and recidivism outcomes to definitely evaluate the effects of realignment strategies . At this stage, we are one- step removed from this ideal, as we must rely on stated plans and budget allocations rather than on -the -ground practices. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 20 Conclusions California’s 2011 p ublic safety realignment represents a watershed in correctional policy, providing an important test of whether local management of lower- level felony offenders can improve recidivism outcomes. Realignment presents counties with both opportunities and challenges. Counties gained authority over lower -level felons along with funding for correctional programs, b ut they were required to hit the ground running with only a short time to develop strategies and allocate resources. This report has examined two questions: whether realignment a ffected the recidivism outcomes of the PRCS population and whether county implementation policies had an impact on those recidivism outcomes . Although the present work focuses on a particular segment of the realigned population and uses some different methodological strategies, the findings bear similarities to previous work by PPIC and the CDCR. Like those investigations , we found modest increases in felony arrests and felony convictions. However, our work focuses only on the recidivism of the PRCS population, compared to their pre -realignment counterparts. Although this population represents the majority of prison releases under realignment, our findings are not directly comparable to previous work because of the difference in the population of interest. When we combined arrests for felonies, misdemeanors, and supervision violations , we found rearrests increased in the period before realignment was implemented. We also find evidence that reconviction s, including felonies and misdemeanors, in creased prior to realignment. The implication is that we must be cautious in attributing even modest increases recidivism to realignment alone . We have also examined the relationship between local realignment policies and recidivism outcomes , finding evidence that PR CS offenders released to counties that prioritized reentry in their realignment implementation plans had better recidivism outcomes than their counterparts released to counties that prioritized enforcemen t. This finding implies that shifting resources toward a wide range of reentry programs and services , instead of toward traditional law enforcement and incarceration , may create conditions for reducing recidivism rates among PRC S offenders. One of realignment’s benefits is that it gave counties the opportunity to experiment with policy. The variety of approaches that counties adopted allows policymakers and researchers to learn what works under realignment. This study is an early look at this question. Still, our findings are suggestive. We see potentially important evidence that county policy choices can make a difference under realignment. Most urgently, we need two types of data to improve our ability to draw policy implications from this e xperiment. First, we need data at the state level that captures the recidivism outcomes of the 1170(h) population. This population will ultimately be the largest segment of the offender pool affected by realignment. Not only will they serve time in local c ustody instead of prison, they will also reenter communit ies, both with and without supervision , depending on their sentences . At present, there is no way of tracking how these offenders are faring under realignment . T hus , whether their recidivism rates are improving, worsening, or staying largely the same is unknowable. Second, we need data that captures the on -the -ground experience of individual offenders rather than just formal plans and budgets. This includes data on the specific services, sanctions, an d alternatives to custody that may reduce recidivism. Without such data, identification of effective strategies for managing offenders will remain elusive. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 21 References California Board of State and Community Corrections. 2013. 2011 Public Safety Realignment Act: Report on the Implementation of Community Corrections Partnership Plans. Available at www.bscc.ca.gov/downloads/Repo rt_on_the_Implementation_of_Community_Corrections_Partnership_Plans.pdf . California Department of Corrections and Rehabilitation. 2013. Realignment Report: An Examination of Offenders Released from State Prison in the First Year of Public Safety Realignment. Available at www.cdcr.ca.gov/adult_research_branch/Research_Documents/R ealignment_1_Year_Report_12-23-13.pdf. California Department of Corrections and Rehabilitation. 2012. 2012 Outcome Evaluation Report. Available at www.cdcr.ca.gov/adult_research_branch/Research_Documents/ARB_FY_0708_Recidivism_Report_10.23.12.pdf. Fischer, Ryan. 2005. “Are California’s Recidivism Rates Really the Highest in the Nation? It Depends on What Measure of Recidivism You Use.” Bulletin 1(1). UC Irvine Center for Evidence-Based Corrections. Available at http://ucicorrections.seweb.uci.edu/files/2013/06/bulletin_2005_vol-1_is -1.pdf. Grat tet, Ryken, Joan Petersilia, and Jeffrey Lin. 2008. Parole Violations and Revocations in California . Final Report to the National Institute of Justice. Available at https://www.ncjrs.gov /pdffiles1/nij/grants/224521.pdf. Hopper, Allen, Margaret Dooley -Sammuli, and Kelli Evans . 2012. Public Safety Realignment: California at a Crossroads. American Civil Liberties Union of California. Available at www.aclunc.org/sites/default/files/public_safety_realignment_california_at_a_crossroads.pdf. Langan, Patrick A , and David J. Levin. 2002. Recid ivism of Prisoners Released in 1994 . U.S. Department of Justice. Bureau of Justice Statistics Special Report. NCJ 193427. Available at www.bjs.gov/content/pub/pdf/rpr94.pdf. Lin, Jeffrey , and Joan Petersilia. 201 3. Follow the Money: How California Counties Are Spending T heir Public Safety Realignment Funds . Stanford Criminal Justice Center, Stanford Law School. Available at www.law.stanford.edu/sites/default/files/publication/443760/doc/slspublic/LinMoneyFinalReport022 814.pdf . Lofstrom, Magnus, and Steven Raphael. 2013. Impact of Realignment on County Jail Populations . Public Policy Institute of California. Available at www.ppic.org/main/publication.asp?i=1063. Maltz, Michael D. 1984. Recidivism . Academic Press. Available at www.uic.edu/depts/lib/forr/pdf/crimjust/recidivism.pdf. Misczynski, Dean. 2012. Corrections Realignment: One Year Later. Public Policy Institute of California. Available at www.ppic.org/main/publication.asp?i=1029. Petersilia, Joan , and Jessica Greenlick Snyder. 2013. “Looking Past the Hype: 10 Questions Everyone Should Ask About California’s Prison Realignment.” Califo rnia Journal of Politics and Policy 5(2): 266 –306. Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2254110. Pew Center on the States. 2011. State of Recidivism: The Revolving Door of America’s Prisons. Washington, DC: Pew Charitable Trusts ). Available at www.pewtrusts.org/en/research -and -analysis/reports/2011/04/12/state -of- recidivism -the-revolving -door-of-americas -prisons . Schlanger, Margo. 2013. “Plata v. Brown and Realignment: Jails, Prisons, Courts, and Politics.” Harvard Civil Rights -Civil Liberties L aw Review. 48(1): 165– 215. Available at http://harvardcrcl.org/wp - content/uploads/2013/04/Schlanger_165- 215.pdf . Stuntz, William J. 2011. The Collapse of American Crimi nal Justice. Harvard University Press. Santos, Michael. 2013. “California’s Realignment: Real Prison Reform or Shell Game?” Blogpost, Huffington Post Crime. March 11. Available at www.huffingtonpost.com/michael -santos/california-prison - realignment_b_2841392.html. Weisberg, Robert. 2011. “California’s De Facto Sentencing Commissions.” Stanford Law Review SLR Online . 64 STAN. L.REV.ONLINE 1: 1 -7. Available at www.stanfordlawreview.org/sites/default/files/online/articles/64 - SLRO -1.pdf . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 22 About the Authors Mia Bird is a r esearch fellow at the Public Po licy Institute of California specializing in c orrections and h ealth and human services. Her current projects focus on the effects of p ublic safety realignment on reentry and recidivism outcomes. Before coming to PPIC, she was a research and evaluation cons ultant with the San Francisco Office of the Public Defender and the San Francisco Superior Court. She holds a Ph.D. in p ublic p olicy, M.A. in d emography , and M.P.P. from the University of California, Berkeley. She also serves on the faculty of the Goldman School of Public Policy at the University of California, Berkeley. Ryken Grattet is a research fellow at the Public Policy Institute of California and p rofessor of sociology at the University of California, Davis. Previously, he was assistant secretary of r esearch in the California Department of Corrections and Rehabilitation. His current work focuses on California correctional policy at the state and local levels. He is the author of Making Hate a Crime: From Soc ial Movement to Law Enforcement (with Valerie Jenness), Parole Violations and Revocations in California (with Joan Petersilia and Jeffrey Lin), and numerous articles in professional and policy publications. His scholarship and public service contributions have been honored by the America n Sociological Association’s Section on the Sociology of Law, the Law and Society Association, the Pacific Sociological Association, and the Society for the Study of Social Problems Crime and Delinquency Section . He was also a recipient of the U .C . Davis D istinguished Scholarly Public Service Award and the College of Letter’s and Sciences Dean’s Innovation Award. Acknowledgments This project benefitted from assistance from Brenda Grealish and Kevin Grassel of the California Department of Corrections and Re habilitation Office of Research Staff, Professors Joan Petersilia, Susan Turner, and Steve Raphael, and Eric McG hee, Patrick Murphy, Hans Johnson, Joe Hayes, Caroline Danielson, and Sonya Tafoya at the Public Policy Institute of California. This work also benefited from the comments and questions of participants at the Association for Policy Analysis and Management 2013 annual meeting. External reviewers Michael Maltz and Lee Seale provided helpful feedback on an early version of the report. Throughout this project, Magnus Lofstrom provided enormous substantive and methodological feedback. Any errors in this work are our own. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 23 PUBLIC POLICY INSTITUTE OF CALIFORNIA Board of Directors Donna Lucas, Chair Chief Executive Officer Lucas Public Affairs Mark Baldassare President and CEO Public Policy Institute of California Ruben Barrales President and CEO GROW Elect María Blanco Vice President, Civic Engagement California Community Foundation Brigitte Bren Attorney Walter B. Hewlett Member , Board of Directors The William and Flora Hewlett Foundation Phil Isenberg Vice Chair Delta Stewardship Council Mas Masumoto Author and Farmer Steven A. Merksamer Senior Partner Nielsen, Merksamer, Parrinello, Gross & Leoni, LLP Kim Polese Chairman ClearStreet, Inc. Thomas C. Sutton Retired Chairman and CEO Pacific Life Insurance Company The Public Policy Institute of California is dedicated to informing and improving public policy in California through independent, objective, nonpartisan research on major economic, social, and political issues. The institute’s goal is to raise public awar eness and to give elected representatives and other decisionmakers a more informed basis for developing policies and programs. The institute’s research focuses on the underlying forces shaping California’s future, cutting across a wide range of public poli cy concerns, including economic development, education, environment and resources, governance, population, public finance, and social and health policy. PPIC is a public charity. It does not take or support positions on any ballot measures or on any local, state, or federal legislation, nor does it endorse, support, or oppose any political parties or candidates for public office. PPIC was established in 1994 with an endowment from William R. Hewlett. Mark Baldassare is President and Chief Executive Officer of PPIC. Donna Lucas is Chair of the Board of Directors. Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source. Research publications reflect the views of t he authors and do not necessarily reflect the views of the staff, officers, or Board of Directors of the Public Policy Institute of California. Copyright © 201 4 Public Policy Institute of California All rights reserved. San Francisco, CA PUBLIC POLICY INSTITUTE OF CALIFORNIA 500 Washington Street, Suite 600 San Francisco, California 94111 phone: 415.291.4400 fax: 415.291.4401 www.ppic.org PPIC SACRAMENTO CENTER Senator Office Building 1121 L Street, Suite 801 Sacramento, California 95814 phone: 916.440.1120 fax: 916.440.1121"
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string(57320) "Do Local Realignment Policies Affect Recidivism in California ? August 2014 Mia Bird and Ryken Grattet with research support from Daniel Krimm, Brandon Martin , and Alexander Becker Summary California is now completing the third year of one of the most ambitious correctional reforms it has ever carried out , A ssembly Bill 109, known as “p ublic safety realignment .” When the state legislature approved this sweeping overhaul in 2011, which transferred authority over lower- level felons from the state prison and parole system to the count y jail and probation systems, it had few alternatives . A federal court had ordered California to sharply cut back priso n overcrowding because of the state’s failure to provide inmates adequate health care . Lawmakers were also under pressure to reduce skyrocketing prison costs and California’s historically high recidivism rate . In other words, California had to fundamentally redesign its correctional system under urgent and pressing circumstances that left little time for study and deliberation . In the months between the passage of realignment and its implementation, counties had to quickly develop strategies to manage the new population of offenders that would now be held and supervised locally. Realignment was motivated , in part, by the idea that “locals c an do it better ”—that counties would be able to reduce the recidivism rates of lower -level offenders more ef fectively than the state prison and parole system. This report examines this issue in two ways. First, it looks at whether realignment reduced recidivism among a particular group of offenders —the Post-Release Community Supervision (PRCS) population , a segm ent of the released prisoner population with current sentences for offenses that are neither serious nor violent. Before realignment, these types of offenders were under the state parole system and now they are supervised by county probation authorities . We find that the post -realignment period has not seen dramatic changes in rearrests or reconvictions among this population, a finding in line with recent research focused more broadly on this topic ( CDCR 2013; Lofstrom, Raphael, and Grattet 2014 ). For the PRCS population, we estimate that felony rearrest s increased 4.7 percentage point s and felony reconvictions increased 1.9 percentage points following realignment. However, these increases are likely due to the elimination of the option to use parole revoc ation to return offenders to prison . Second, the report examines variation across counties in realignment implementation policies . Under realignment, the state provided counties with $400 million dollars to help cover their increased workload. C ounties were required to submit plans describ ing how they would implement realignment, but they had wide dis cretion in which programs to adopt and how to allocate these funds . These choices appear to have mattered. When we examine the relationship between the polici es counties chose to implement and changes in recidivism under realignment, we find that offenders did better in counties that emphasized reentry services . We find that recidivism increased over the realignment period for PRCS offenders released to counties with implementation policies that prioritized enforcement relative to those released to counties with policies that prioritized reentry services. We estim ate the change in the felony rearrest rate under realignment was 3.7 percentage points greater for offenders released to counties with enforcement -focused plans than for those released to counties with reentry -focused plans . The felony reconviction rate followed a similar pattern. We find the change in the felony reconviction rate was 1.7 percentage points greater for offenders released to counties with enforcement -focused plans. It is important to interpret these findings with caution . The available data limits our analysis to only one segment of the realigned offender population, t hose released from state prison and supervised by county probation. In addition, o ur analysis focuses on the first year of realignment, during which c ounties faced a momentous change and had limited time to design and implement realignment plans. We also relied on realignment plans and budget allocations submitted to the s tate, which may not provide a complete view of http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism in California? 2 county strategic approaches. Nonetheless, these plans and budget allocations represent important policy levers available to county leaders. Finally , we deliver these findings with caution because there may be factors at work that we were unable to observe in this study and that explain, in part, differences across counties in recidivism outcomes. While this study offers a first look into the r elationship between county imp lementation policies and recidivism, w e expect to be able to learn a great deal more as better data become available . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism in California? 3 Contents Summary 2 Figures 5 Tables 5 Abbreviations 6 Introduction 7 Recidivism under Realignment 9 Defining and Measuring Recidivism 9 Early Research on Realignment and Recidivism 10 Defining the Realignment Population 10 Recidivism Varies Over Time and Across Counties 11 Statewide Effects of Realignment on Re cidivism 14 Realignment Implementation Plans and Budgets 16 First-Year Realignment Implementation Plans 16 First-Year Realignment Budget Allocations 17 Categorizing Implementation Policies Based on Plans and Budgets 19 Effects of Realignment Policies on Recidivism 20 Conclusions 21 References 22 About the Authors 23 Acknowledgments 23 A technical appendi x to this paper is available on the PPIC website: www.ppic.org/content/pubs/other/814MBR_appendix.pdf Figures 1. Felony rearrest rates varied widely across counties after realignment 12 2. Felony reconviction rates varied widely across counties after realignment 13 3. Implementation plans varied widely in the types of reentry services emphasized 17 4. Implementation plans varied widely in their resource allocations 18 Tables 1. Implementation plans cluster into two categories 19 http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 5 Abbreviations 1170(h) The penal code designation for felons convicted of non-violent, non-serious, or non- sexual crimes who u nder realignment serve sentences in county jails rather than state prison. BSCC Board of State and Community Corrections CDCR California Department of Corrections and Rehabilitation PRCS Post-Release Community Supervision, county-based supervision of offenders released from state prison . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 6 Introduction October 1, 2011 marked the beginni ng of a new era for corrections and rehabilitation in California . State correctional authorities and their counterparts in 58 count ies began carrying out a fundamental realignment of responsibilities for managing tens of thousands of lower-level felons. This change , known as p ublic safety realignment, represented one of the most far -reaching correctional policy reforms in recent U.S. history. Federal courts had ruled that state prison overcrowding had made it impossible for California to provide inmates a level of health care required by the U.S. Constitution. The state was ordered to cut the prison population to 137.5 percent of design capacity. At the same time, California was facing an acute budget crisis and could no longer afford rapidly rising prison costs. Governor Brown proposed a series of changes that became the basis for Assembly Bill 109, which authorized realignment. T he changes this law ushered in have been described as “revolutionary and sudden” (Weisberg 2011), “the most significant correcti onal reform in decades” (Misczynski 2012), and “the biggest penal experiment in modern history” (Santos 2013). Realignment shifted authority over most non- serious, non-violent, non- sexual offenders from the state to counties and granted counties discretio n over how to manage these offenders. The idea behind realignment was that local governments have better information about what their communities need than the state, and that offenders would do better when held at the local level. Under realignment , state prison and parole populations have dropped dramatically , while county jail and probation caseloads have increased s ubstantially (Lofstrom and Raphael 2013; Petersilia and Snyder 2013). The net result has been lower overall levels of incarceration in California. A key question is w hether realignment can reduce California’s historically high rates of recidivism. Before realignment, California was among the states with the highest parolee rearrest rates (Fischer 2005; Langan and Levin 2002). In the years immediately before the change, some 60 percent of offenders paroled from state prison were arrested in the first year of release. By three year s after release, the re arrest rate reached over 80 percent (CDCR 2012). Even more striking was the proportion of released offenders returned to prison through parole revocations and reconvictions (Grattet, Petersilia, and Lin 2008) , precisely the revolving door t hat realignment sought to stop . Now the majority of offenders who violate terms of release go to county jails or community -based alternative form s of incarceration. T he state provided counties $400 million to help pay their increased correctional costs , but did not dictate how the money sh ould be spent. However, c ounties were required to create implementation plan s that de scribed their realignment strategies and explained how they would use funds provided by the state. These documents provide a unique research opportunity. V ariations across the counties in implementation strategies and spending priorities allow us to see how local correctional policies affected recidivism. T his report consider s two broad policy questions . First, we assess how realignment affected the recidivism rates of the P ost -Release Community Supervision (P RCS) population, the group of lower- level felons released from prison to county probation supervision under realignment . 1 And second , we examine how 1 PRCS is a designation created by AB 109. It refers to offenders whose current commitment offense is not serious or violent and who are not high -risk sex offenders or mentally disordered offender s Prior to realignment this group was not treated as distinct from other prison releases who were sent into the state parole system. Therefore, strictly speaking, PRCS did not exist as a recognized category of offe nders before http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 7 local policy choices affected the recidivism outcomes of this population . We start by reviewing the conceptual and measurement issues surrounding recidivism , as well as the existing literature on realignment and recidivism . Then we analyze the recidivism outcomes of the PRCS population compared with the recidiv ism of their pre- realignment counterparts. Finally, we examine how county realignment plans and budgets varied in how much they emphasize d reentry services versus enforcement , and how those implementation strategies affect ed PRCS recidivism outcomes . realignment. After realignmen t, PRCS are released to county probation departments. This group of offenders is uniquely affected by realignment and thus provides an opportunity to examine the consequences of shifting community supervision from state parole to county pr obation. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 8 Recidivism under Realignment Defining and Measuring Recidivism Among researchers there is widespread agreement about how recidivism should be defined—as a concept. In his book Recidivism, Michael Maltz defines recidivism as “the reversion of an individual to criminal behavior after he or she has been convicted of a prior offense, sentenced, and (presumably) corrected” (2001). This definition closely resembles th at used in The PEW Charitable Trusts’ State of Recidivism repo rt, which regards it as “the act of reengaging in criminal offending despite having been punished” (20 11). The contestation over recidivism emerges not because of lack of agreement about definition, but in terms of how it should be measured. T hree routinel y tracked points in the criminal justice process provide way s to measure recidivism —rearrest, reconviction, and return to custody —and each has its advocates. Rearrest can be subdivided into rearrest for a misdemeanor or felony , or for a supervision violat ion. Criminal rearrest is the most relevant for gauging how a released offender ’s behavior affects public safety . However, rearrest for a crime only happens when that crim e comes to light, the offender is identified as the perpetrator, and is apprehended. To the extent that this leaves out undetected or unreported crimes, it under states the true extent of recidivism. Conversely , to the degree that individuals are arrested for crimes they did not commit, rearrest over states recidivism. Reconviction sets a higher bar. When a released offender is reconvict ed, criminal justice authorities have found enough evidence of a crim e to prosecute or plea bargain . This measure of recidivism is conservative because it omits crim es for which there is insufficient eviden ce or other reasons for not prosecuting. Moreover, r econviction only measures result s of formal criminal prosecution s and does not include administrative parole revocations . Despite these flaws , advocates for us ing conviction as a recidivism measure argue that it covers “validated” criminal activity and better captures recidivism’s impact on local criminal justice resources . Return to custody includes only those released inmates sent back to prison or jail following criminal reconviction or revocation . Offenders may be revoked if they are arrested for a new crime or if they commit a technical violation of supervision rules , such as failure to report to a supervising officer or travel outside of a restricted area . For many years, the California Department of Corrections and Rehabilitation ’s (CDCR) official recidivism statistic was return to the department’s custody. For any given year, CDCR wanted to know how many felons released from its custody came back and occupied a bed with in one, two, or three years . For this purpose, it was not relevant whether the return reflected a new criminal conviction or a parole revocation. By this measure, California had an exceptionally high three- year recidivism rate of more than 65 percent before realignment . The return -to -prison -custody measure had many critics because it included large number s of technical parole violators. Still, it made sense to CDCR because it measured the impact of parole failure on the department’s r esources. Now , under realignment, offenders released from prison can only be revoked to county jail . Revocations generally cannot result in returns to prison and the problem s of return to custody as a recidivism measure have become more apparent . http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 9 Early Research on Realignment and Recidivism In the past fifteen months , the first studies have appeared of the effect s of realignment on recidivism. A CDCR report compar es offenders released from prison in realignment’s first year with those released in the year before realignment. CDCR found that one -year post -realignment returns to prison have dropped from 32 percent to 7 percent (CDCR 2013) , a his torical low. 2 T his is not surprising. Realignment was intended to end the revolving door of parole violators and low -level offenders in to a nd out of prison . CDCR also found that one -year rearrest rates dropped from 59 to 56 percent after realignment , although the proportion of felony rearrests rose from 37 to 43 percent . The average number of rearrests for each offender also rose. Rec onvictions were unchanged , although the proportion of felony reconvictions rose from 57 to 58 percent . PPIC researchers analyz ing CDCR’s data found that offenders released from prison pre - and post - realignment differed in several ways (Lofstrom, Raphael, and Grattet 2014). M ost important was the declining proportion of re turns to prison resulting from parole revocations , which was one of the main goals of realignment . Therefore, release d prisoners were less likely to be “frequent flyers” who cycled in a nd out of prison on parole revocations. After adjusting for these differences in the characteristics of pre- and post - realignment prison releases, t he PPIC study l argely corroborat ed CDCR findings of slight declines in arrests and slight increases in convi ctions, particularly for felonies. Taken together, t he PPIC and CDCR studies suggest: 1) released offenders now return to prison at a historically low rate ; 2) overall rearrests appear to be declining, although the composition and frequency of rearrests is changing; and 3) without parole revocation to send released offenders back to prison, reconvictions are increasing , driven by rising felony re convictions. These changes must be set against a larger context in which reductions to the prison popul ation have saved the state a considerable amount of money . Finally , total incarceration levels have fallen , with a big drop in the state prison population more than offsetting rising numbers in county jails . Lower overall incarceration levels suggest relea sed offenders may be spending more time in the community where they are at risk of committing new crimes. O ur work takes a somewhat different approach. We focus specifically on the PRCS population because they are much more likely, when compared with offenders released from prison to parole, to be affected by county policy choices under realignment . Also, f or the methodological reasons we describe below, we use a six -month observation period rather than a one -year period. As a result, estimates generated from the present work are not directly comparable to the investigations described above. Defining the Realignment Population Realignment delineated three populations of offenders: PRCS . Offenders convicted of non- violent, non- serious, and non- sexual crimes, released from state prison to county supervision instead of state parole . 1170(h) . Felons with no current or prior serious, violent, or sexual convictions , previously subject to state prison sentences and state parole supervision , but now jailed and supervised at the county level . S tate parole . Mentally disordered, high- risk sex offenders , or felons most recent ly convicted of a serious or violent offense. 2 The changes in recidivism cited in this paper are rounded up from CDCR findings to ease readability. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 10 Under realignment, counties manage the PRCS and 1170(h ) populations, but have no responsibility for state parole es unless the y violate the terms of their supervision and are revoked to county jail. The PRCS offenders are of particular interest because, like the pre- realignment prison population , they served t heir sentences in state prison . However, PRCS offenders differ from their pre- realignment counterparts because they are supervised by county probation rather than by state parole. F ocusing on the PRCS population allows us to assess the statewide effect of realignment on PRCS recidivism. At the same time, because the PRCS population is exposed to county supervision strategies, evaluating outcomes for this population provides a window into the role of local policy choices in mitigating recidivism outcomes under realignment . While the 1170(h) population is also exposed to local implementation strategies, the kind of statewide data that would allow for analysis is not currently available for this population . 3 Recid ivism Varies Over Time and Across Counties CDCR data allow us to compare PRCS offenders with similar offenders who left prison before realignment. We selected a control population of prisoners released between October 2010 and March 2011. These offenders were sentenced to prison for crimes that would have put them under PRCS had they been released after realignment took effect. We then selected a PR CS population that left prison between October 2011 and March 2012, the first six months of realignment. We chose t he same release months for both populations to control for seasonal effects and we chose six -month observation periods because doing so allow ed us to conduct further analyses to ensure we account for any preexisting trends in reci divism outcomes. Although r esearch has demonstrated that the largest share of recidivism occurs within 180 days of release (Grattet, Petersilia, and Lin 2008) , we also conduct an analysis of one -year recidivism rates and discuss these findings in the Technical Appendix . Before realignment, we see wide variation in recidivism patterns across California’s counties. S ix-month felony rearrest rate s rang ed from 8 to 35 percent and f elony conviction rates from 1 to 15 percent. After realignment, we see even greater variation in these outcomes . S ix -month felony rearrest rates rang ed from 3 to 53 percent and felony reconviction rates from zero to 1 7 percent in the period that followed realignment . There are many underlying factors, such as local demographic and economic characteristics, that may drive differences in the level of recidivism across counties. Rather than analyze differences in the levels of recidivism, we focus on how recid ivism changed within counties over the time period of realignment. Figure 1 shows the six -month percentage point change in felony rearrest rates in the 39 California counties that supervised at least 30 PRCS offenders . Twelve counties experienced decreases and 27 experienced increases in felony rearrest rates . However, t hese changes might reflect a number of factors, including differences in the post - realignment offender population or variation across counties in realignment implementatio n policies. 3 PPIC is collecting data on 1170(h) offenders as part of a project with the Board of State and Community Corrections. These data should allow us to say m ore about 1170(h) recidivism in the future . http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 11 FIGURE 1 Felony rearrest rates varied widely across counties after realignment SOURCE: Author’s analysis of California Department of Corrections and Rehabilitation (CDCR) prison release data. NOTE: T his figure compares the rearrest outcomes of offenders released from prison to PRCS under realignment (between October 1, 2011 and March 31, 2012) to those of offenders with similar characteristics released from prison to parole before realignment (between October 1, 2010 and March 31, 2 011). -20%-10% 0% 20% Mendocino Humboldt San Luis Obispo San Francisco San Mateo SolanoLake Sonoma Santa Clara Santa Cruz ShastaPlacer Madera Kings Riverside Sacramento Napa San Bernardino Kern Contra Costa Alameda Monterey TulareYolo San Diego Los Angeles MercedSutterButte San Joaquin Yuba El Dorado Tehama Santa Barbara Orange Imperial Fresno Stanislaus Ventura Percentage point change in 6 month felony arrest rate http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 12 Figure 2 shows changes in felony reconviction s after realignment . The six -month felony reconviction rate fell in 14 counties and rose in 25. FIGURE 2 Felony reconviction rates varied widely across counties after realignment SOURCE: Author’s analysis of California Department of Corrections and Rehabilitation (CDCR) prison release data. NOTE: T his figure compares the reconviction outcomes of offenders released from prison to PRCS under realignment (between October 1, 2011 and March 31, 2012) to th ose of offenders with similar characteristics released from prison to parole before realignment (between October 1, 2010 and March 31, 2011). -6%-4%-2% 0%2%4%6%8% Mendocino Napa Humboldt Santa Cruz Riverside San Diego Shasta San Bernardino Yuba El Dorado San Luis Obispo VenturaMerced San Joaquin Placer Sonoma Lake Kings San Francisco Santa Barbara OrangeFresno Tehama Madera Alameda Santa Clara Los Angeles Sacramento Kern Butte Contra Costa Yolo Monterey Stanislaus San Mateo Tulare Imperial Sutter Solano Percentage point change in 6 month felony reconviction rate http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 13 Figures 1 and 2 present trends in recidivism in our data. However, these trends do not adjust for the possible differences in offender characteristics across counties and over time. In the next section, we make these adjustments, allowing us to estimate the effect of realignment on statewide recidivism for the PRCS population . Statewide Effects of Realignment on Recidivism We cannot assume that realignment caused all c hanges in recidivism after October 1, 2011. Researchers must overcome three challenges to estimate realignment ’s effect accurately : The characteristics of the released offender population vary over time. This variation may affect the recidivism levels we observe. For example, i f offender s released after realignment were at lower risk of reoffending than those released before realignment, we might misinterpret lower recidivism outcomes as the effect of realignment . To address possibilit ies like this one, we make adjustments for the changing individual characteristics of the released offender population. Like individuals, counties also vary in their characteristics. Some counties have stronger eco nomies or a wider range of service providers in their communities , and factors like these can affect recidivism outcomes. In addition, the share of released offenders returning to a particular county may vary over time. For these reasons, it is important to adjust for the county of release in a statewide analysis . Finally, c hanges in recidivism may reflect trends already under way in California before Oct ober 1, 2011 and, therefore, we need to be sure to examine any preexisting trends in recidivism before we draw conclusions about the effect of realignment on recidivism. Afte r adjust ing for differences in offender and county characteristics , we estimate that felony rearrest s for the PRCS population increased 4.7 percentage point s and felony reconvictions increased 1.9 percentage points following realignment . In other words, offenders whose supervision shifted from state parole to county probation under realignment were more likely to be rearrested and reconvicted for serious crimes than their pre -realignment counterparts . However, when we u se a broader rearrest measure, includ ing supervision violations, misdemeanors, and felonies , we find no evidence of an increase among the PRCS population after realignment. Although PRCS offenders were more likely to be re arrested for felon ies than their pre -realignment counterparts were, they were less likely to be re arrested for supervision violations and minor offenses. When these measures are combined , the increase in felony rearrests is offset by decreases in other kinds of rearrests. Available data do no t indicate whether these patterns reflect changes in offender behavior or actions of local officials, although it seems likely that the increases in felony arrests and convictions and the corres ponding declines in arrests for supervision violations may result from the removal of the possibility of revocation to state prison. Without the option of revocation to prison, counties may be adjusting their arresting and prosecuting to bring offenders in to the formal criminal justice process (see Loftstrom, Raphael, and Grattet 2014). Reconvictions for the PRCS group follow a different pattern. Even w hen misdemeanor convictions are included, PRCS offenders have high er reconviction rates than their pre -realignment counterparts. We estimate the combined felony and misdemeanor reconviction rate rose 2.3 percentage points after realignment. 4 4 CDCR and PPIC (Lofstrom, Raphael, and Grattet 2014) also found increases in felony arrests and convictions after realignment. Our study and the CDCR and PPIC studies found slight decreases or no difference in r ecidivism for all arrests. PPIC and CDCR looked at all released prisoners, while we analyzed only PRCS offenders and their pre -realignment counterparts. Our study also used somewhat different methodological approaches to detect preexisting trends, including 6 month observation periods rather than one -year http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 14 We then examine the period before Oct ober 1, 2011 to see whether our estimates of changes in recidivism under realignment reflect factors at work before the new system was introduced. We f ind no evidence that felony rearrest and reconviction rates were rising before realignment , but we do find evidence of pre - realignment increases in rearrest and reconviction rates when we use the measures of recidivism that combine arrests for felonies, misdemeanors, and supervision violations as well as convictions for either felonies or misdemeanors . T hese findings suggest realignment induced a shift in both the likelihood of re -offense and the way in which that re -offense would be measured. Before realignment , released offenders arrested for felonies were often revoked and sent back to prison by the p arole board . Now, given that most supervised offenders canno t be returned to prison without a new conviction, r eleased offenders a re more likely to be rearrested and reconvicted in criminal court . While we find that reconviction rates increased overall under realignment, our analysis also suggests some of this increase may have been driven by preexisting trends in statewide recidivism. These findings are presented in greater detail in the Technical Appendix . We now turn to the role of local policy. Our previous analysis showed recidivism outcomes under realignment vary substantially by county. In the next stage of our analysis , we assess the different implementation strategies used by counties and then examine the relationship between those approaches an d recidivism outcomes . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 15 Realignment Implementation Plans and Budgets The state provides substantial funding to cover the cost of managing realigned offenders . Counties are free to determine how to use th ose dollars but were required to develop plan s that detailed their strategic approaches and spending priorities . County Community Corrections Partnerships (CCPs) drafted these plans and submitted them to the state . Created under realignment, t he CCPs are headed by the c hief of p robation and includ e the she riff, the d istrict attorney, the p ublic defender, and criminal justice and social services agenc y representatives . We simplified the plans by first capturing the range of reentry services counties planned to implement. We then added information about how c ounties planned to allocate their realignment funds to fill out the picture for each county. While this approach allows us to examine the impact of broad policy decisions, it does not permit us to study how individual programs, sanction s, or supervision strategies affect ed recidivism rates . First -Year Realignment Implementation Plans To categorize approaches to realignment , we identified the specific reentry service types included in each implementation plan . Figure 3 shows t he prevalence of different ki nds of reentry services. Services consisted of health -related programs , including mental health, substance abuse, and cognitive behavioral therapy; housing and income support services; employment and education services; family and gender- based services; an d peer and community -based serv ices. We also include needs assessment because evaluation of the factors that might lead a released offender to commit new crimes is the first step toward determining what services that person should get. The prevalence of di fferent services varie d. Nearly every plan called for introduc ing or expan ding needs assessment. Similarly, most plans included mental health, substance abuse, and cognitive behavioral treatment components . In other respects , implementation plans ranged considerably . M any included education and housing programs. A minority included new or expanded health care, family, or parenting services. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 16 FIGURE 3 Implementation plans varied widely in the types of reentry services emphasized SOURCE : Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. First-Year Realignment Budget Allocations We also examined how implementation plans document the funds they proposed to allocate to particular areas (Figure 4) . It is challenging to use written budgets to determine where counties actually directed the money because the state did not require standardized reporting methods . We consulted researchers at Stanford Law School , the American Civil Liberties Union , and the Board of State an d Community Corrections on how to classify budget allocations. 5 Ultimately, we arrived at five main spending categories: s heriff, probation, new jail beds, law enforcement, and programs and services. In some cases, fund s for jail expansion came indirectly through the s heriff’s office . In those cases, we moved the funds from the s heriff c ategory to the jail category. Similarly , fund s allocated to the sheriff or probation w ere often redirected to programs and services. In those cases, we put the allocation into the programs and services category . 5 See Lin and Petersilia (2013), American Civil Liberties Union (2012), and BSCC (2013) on categorizing realignment allocations . 0 10 2030405060 Mentorship Gender-based Self Help Restorative Justice Parent Income FamilyHealth Housing Vocational Education Employment Cognitive Behavior Therapy Education Mental Health Substance Abuse Needs Assessment Number of counties http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 17 FIGURE 4 Implementation plans varied widely in their resource allocations SOURCE: Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. Figure 4 shows the range of variation in how counties proposed to allocate their state realignment funds. The boxes represent 50 percent of the counties on each measure, encompassing the quartiles above and below the median (i.e., the counties arrayed between the twenty -fifth percentile and the seventy -fifth percentile). The whiskers to the right and left of the boxes show the range between the minimum and maximum values. The specific patterns of variation include : Programs and services expenditures var ied from zero to 84 percent of total realignment funding . The median was 18 percent . Half the counties directed between 8 and 33 percent to the category. For l aw enforcement , the median expenditure was zero, mean ing that at least half the counties did not allocate any money for this categor y. The highest law enforcement allocation was 23 percent. Jail bed expenditures ranged from zero to 70 percent . Half the counties directed from zero to 19 percent to expanding jail capacity. Expenditures in the s heriff category ranged from zero to 72 percent, with a median of 17 percent . H alf the counties directed between 7 and 30 percent to the sheriff’s office . Probation expenditures varied the most, ranging from zero to 86 percent , with a median of 27 percent . H alf the probation budgets were between 20 and 38 percent. 0% 200% Probation SheriffJails Law Enforcement Programs Percent of total budget allocation http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 18 Categorizing Implementation Policies Based on Plans and Budgets The variation in strategic plans and budgets across counties provides a basis for categorizing differences in approaches to realignment . To create a simple, replicable, and balanced categoriz ation method , we settled on one measure from the budgets and one from the strategic plans. We experimented with a longer list of measur es, b ut this did not improve our ability to clearly delineate differences in implementation strategies. (For more detail regarding our methods, please see the Technical Appendix .) Our budget measure emphasizes custody and law enforcement. W e combined allocations to sheriff’s agencies, jails, and law enforcement to determine to what degree counties directed funds to these areas or made the s heriff responsible for distributing state realignment money . By contrast, o ur measure from the strategic plan s focuses on new or expanded reentry services for PRCS offenders, as described in the previous section. Using these measures, we identified two distinct approaches to realignment implementation : enforcement - focused and reentry -focused. We categorized 19 plans as enforcement -focused and 24 as reentry -focused. We excluded 15 mixed- approach plans from our analysis because there was insufficient support for placing them in either category (see Technical Appendix for further details) . T able 1 shows on average the enforcement-focused plans allocate d more than three times as much realignment money to the sheriff’s agency, jail , and law enforcement than the reentry -focused plans did . Given that budgets are fixed, the share of the budget allocated toward enforcement is directly related to the share allocated toward programs and services in each county. The table a lso shows that enforcement -focused plans averaged slightly fewer reentry services offerings than reentry -focused plans did . TABLE 1 Enforcement - and r eentry -focused i mplementation p lans differ in terms of priorities Budget allocation to sheriffs, jails, and l aw enforcement Number of reent ry services Number of c ounties Enforcement -focused plans 56.1% 8.0 19 Reentry- focused plans 15.3% 8.6 24 Average/Total 33.4% 8.4 43 SOURCE : Authors’ analysis of county Community Corrections Partnership (CCP) realignment plans. The enforcement -focused and reentry -focused categories represent distinct approaches to realignment. There are many reasons why the approach to realignment may vary across the state. A county may have emphasized a particular approach in its plan based on evidence or beliefs that that approach will be the most ef fective at reducing the recidivism. However, counties may also have other goals in mind. For example, with the goal of the broader public safety in mind, realignment funding may have been directed to fill the greatest resource gaps in the local correctiona l system. Similarly, effective management may have been a higher- priority goal then recidivism reduction. In this analysis, we focus narrowly on the goal of reducing recidivism among the realigned population. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 19 Effects of Realignment Policies on Recidivism We now consider whether county policies, as reflected in their implementation plans , a ffected recidivism . In this analysis, we adjust for differences in the characteristics of offenders released before and after realignment , as well as differences in offe nder characteristics across counties . We also use an approach that compare s the change in recidivism within the enforcement -focused counties under realignment to the change in recidivism within the reentry -focused counties. This approach accounts for underlying differences in county characteristics. We find that recidivism increased over the realignment period for PRCS offenders released to counties that prioritized enforcement relative to those released to counties that prioritized reentry services . We estimate the change in the felony rearrest rate under realignment was 3.7 percentage points great er for offenders released to enforcement -focused counties than for those released to reentry -focused counties. The felony reconviction rate followed a similar pattern. We find the change in the felony reconviction rate was 1.7 percentage points greater for offenders released to enforcement -focused counties. For the broader recidivism measure including rearrests for felonies, misdemeanors, and supervis ion violations , we estimate the change in the rearrest rate was 1.9 percentage point s greater for enforcement -focused counties. Similarly, the change in reconviction rate, including felonies and misdemeanors, was 2.3 percentage point s greater in enforcement -focused counti es than in reentry -focused counties over the period of realignment . W e checked whether pre- realignment relationship s or underlying trends in the counties that composed our two groups ma y have driven our findings and f ound no evidence that preexisting recid ivism trends influenced our results . It is important to note that we group plans together here to identify statewide patterns in the relationship between local approach es to realignment implementation and changes in recidivism. Because the analysis is at the group rather than the county level, it would be inappropriate to draw conclusions about the specific relationship between an implementation plan in a particular county and the recidivism outcomes of offenders released to that county. Taken together, o ur findings suggest policy approaches to implementation matter under realignment. The recidivism outcomes of PRCS offenders were better in counties that emphasized reentry services in their realignment plans than in those that emphasized enforcement . When the legislature approved realignment, it expressed strong support for the use of evidence- based practices. The preliminary evidence presented here suggests that offenders did better in counties that matched their implementation strategy to this legislative intent. However, given the data limitations, the focus of this work is on a population currently under supervision and, therefore, most likely to benefit from reentry services in the near term. We must also consider the possibility that recidivism outcome s reflect not only offender behavior, but also the degree of monitoring of offender behavior in local justice systems. While offenders in enforcement -focused counties may have higher recidivism rates because they have less access to reentry services, it is also possible that offenders are more likely to be closely monitored in enforcement -focused counties. In that case, higher recidivism rates may reflect higher levels of apprehension rather than higher levels of criminal behavior. It is also important to stress that these findings are preliminary. We will need more data to draw strong conclusions about realignment ’s effects on recidivism . Specifically, researchers need data on individual offender characteristics, criminal histories, reentry services and sa nctions received, and recidivism outcomes to definitely evaluate the effects of realignment strategies . At this stage, we are one- step removed from this ideal, as we must rely on stated plans and budget allocations rather than on -the -ground practices. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 20 Conclusions California’s 2011 p ublic safety realignment represents a watershed in correctional policy, providing an important test of whether local management of lower- level felony offenders can improve recidivism outcomes. Realignment presents counties with both opportunities and challenges. Counties gained authority over lower -level felons along with funding for correctional programs, b ut they were required to hit the ground running with only a short time to develop strategies and allocate resources. This report has examined two questions: whether realignment a ffected the recidivism outcomes of the PRCS population and whether county implementation policies had an impact on those recidivism outcomes . Although the present work focuses on a particular segment of the realigned population and uses some different methodological strategies, the findings bear similarities to previous work by PPIC and the CDCR. Like those investigations , we found modest increases in felony arrests and felony convictions. However, our work focuses only on the recidivism of the PRCS population, compared to their pre -realignment counterparts. Although this population represents the majority of prison releases under realignment, our findings are not directly comparable to previous work because of the difference in the population of interest. When we combined arrests for felonies, misdemeanors, and supervision violations , we found rearrests increased in the period before realignment was implemented. We also find evidence that reconviction s, including felonies and misdemeanors, in creased prior to realignment. The implication is that we must be cautious in attributing even modest increases recidivism to realignment alone . We have also examined the relationship between local realignment policies and recidivism outcomes , finding evidence that PR CS offenders released to counties that prioritized reentry in their realignment implementation plans had better recidivism outcomes than their counterparts released to counties that prioritized enforcemen t. This finding implies that shifting resources toward a wide range of reentry programs and services , instead of toward traditional law enforcement and incarceration , may create conditions for reducing recidivism rates among PRC S offenders. One of realignment’s benefits is that it gave counties the opportunity to experiment with policy. The variety of approaches that counties adopted allows policymakers and researchers to learn what works under realignment. This study is an early look at this question. Still, our findings are suggestive. We see potentially important evidence that county policy choices can make a difference under realignment. Most urgently, we need two types of data to improve our ability to draw policy implications from this e xperiment. First, we need data at the state level that captures the recidivism outcomes of the 1170(h) population. This population will ultimately be the largest segment of the offender pool affected by realignment. Not only will they serve time in local c ustody instead of prison, they will also reenter communit ies, both with and without supervision , depending on their sentences . At present, there is no way of tracking how these offenders are faring under realignment . T hus , whether their recidivism rates are improving, worsening, or staying largely the same is unknowable. Second, we need data that captures the on -the -ground experience of individual offenders rather than just formal plans and budgets. This includes data on the specific services, sanctions, an d alternatives to custody that may reduce recidivism. Without such data, identification of effective strategies for managing offenders will remain elusive. http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 21 References California Board of State and Community Corrections. 2013. 2011 Public Safety Realignment Act: Report on the Implementation of Community Corrections Partnership Plans. Available at www.bscc.ca.gov/downloads/Repo rt_on_the_Implementation_of_Community_Corrections_Partnership_Plans.pdf . California Department of Corrections and Rehabilitation. 2013. Realignment Report: An Examination of Offenders Released from State Prison in the First Year of Public Safety Realignment. Available at www.cdcr.ca.gov/adult_research_branch/Research_Documents/R ealignment_1_Year_Report_12-23-13.pdf. 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Available at www.aclunc.org/sites/default/files/public_safety_realignment_california_at_a_crossroads.pdf. Langan, Patrick A , and David J. Levin. 2002. Recid ivism of Prisoners Released in 1994 . U.S. Department of Justice. Bureau of Justice Statistics Special Report. NCJ 193427. Available at www.bjs.gov/content/pub/pdf/rpr94.pdf. Lin, Jeffrey , and Joan Petersilia. 201 3. Follow the Money: How California Counties Are Spending T heir Public Safety Realignment Funds . Stanford Criminal Justice Center, Stanford Law School. Available at www.law.stanford.edu/sites/default/files/publication/443760/doc/slspublic/LinMoneyFinalReport022 814.pdf . Lofstrom, Magnus, and Steven Raphael. 2013. Impact of Realignment on County Jail Populations . Public Policy Institute of California. Available at www.ppic.org/main/publication.asp?i=1063. Maltz, Michael D. 1984. Recidivism . Academic Press. Available at www.uic.edu/depts/lib/forr/pdf/crimjust/recidivism.pdf. Misczynski, Dean. 2012. Corrections Realignment: One Year Later. Public Policy Institute of California. Available at www.ppic.org/main/publication.asp?i=1029. Petersilia, Joan , and Jessica Greenlick Snyder. 2013. “Looking Past the Hype: 10 Questions Everyone Should Ask About California’s Prison Realignment.” Califo rnia Journal of Politics and Policy 5(2): 266 –306. Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2254110. Pew Center on the States. 2011. State of Recidivism: The Revolving Door of America’s Prisons. Washington, DC: Pew Charitable Trusts ). Available at www.pewtrusts.org/en/research -and -analysis/reports/2011/04/12/state -of- recidivism -the-revolving -door-of-americas -prisons . Schlanger, Margo. 2013. “Plata v. Brown and Realignment: Jails, Prisons, Courts, and Politics.” Harvard Civil Rights -Civil Liberties L aw Review. 48(1): 165– 215. Available at http://harvardcrcl.org/wp - content/uploads/2013/04/Schlanger_165- 215.pdf . Stuntz, William J. 2011. The Collapse of American Crimi nal Justice. Harvard University Press. Santos, Michael. 2013. “California’s Realignment: Real Prison Reform or Shell Game?” Blogpost, Huffington Post Crime. March 11. Available at www.huffingtonpost.com/michael -santos/california-prison - realignment_b_2841392.html. Weisberg, Robert. 2011. “California’s De Facto Sentencing Commissions.” Stanford Law Review SLR Online . 64 STAN. L.REV.ONLINE 1: 1 -7. Available at www.stanfordlawreview.org/sites/default/files/online/articles/64 - SLRO -1.pdf . http://www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 22 About the Authors Mia Bird is a r esearch fellow at the Public Po licy Institute of California specializing in c orrections and h ealth and human services. Her current projects focus on the effects of p ublic safety realignment on reentry and recidivism outcomes. Before coming to PPIC, she was a research and evaluation cons ultant with the San Francisco Office of the Public Defender and the San Francisco Superior Court. She holds a Ph.D. in p ublic p olicy, M.A. in d emography , and M.P.P. from the University of California, Berkeley. She also serves on the faculty of the Goldman School of Public Policy at the University of California, Berkeley. Ryken Grattet is a research fellow at the Public Policy Institute of California and p rofessor of sociology at the University of California, Davis. Previously, he was assistant secretary of r esearch in the California Department of Corrections and Rehabilitation. His current work focuses on California correctional policy at the state and local levels. He is the author of Making Hate a Crime: From Soc ial Movement to Law Enforcement (with Valerie Jenness), Parole Violations and Revocations in California (with Joan Petersilia and Jeffrey Lin), and numerous articles in professional and policy publications. His scholarship and public service contributions have been honored by the America n Sociological Association’s Section on the Sociology of Law, the Law and Society Association, the Pacific Sociological Association, and the Society for the Study of Social Problems Crime and Delinquency Section . He was also a recipient of the U .C . Davis D istinguished Scholarly Public Service Award and the College of Letter’s and Sciences Dean’s Innovation Award. Acknowledgments This project benefitted from assistance from Brenda Grealish and Kevin Grassel of the California Department of Corrections and Re habilitation Office of Research Staff, Professors Joan Petersilia, Susan Turner, and Steve Raphael, and Eric McG hee, Patrick Murphy, Hans Johnson, Joe Hayes, Caroline Danielson, and Sonya Tafoya at the Public Policy Institute of California. This work also benefited from the comments and questions of participants at the Association for Policy Analysis and Management 2013 annual meeting. External reviewers Michael Maltz and Lee Seale provided helpful feedback on an early version of the report. Throughout this project, Magnus Lofstrom provided enormous substantive and methodological feedback. Any errors in this work are our own. http:// www.ppic.org /main/home.asp Do Local Realignment Policies Affect Recidivism i n California? 23 PUBLIC POLICY INSTITUTE OF CALIFORNIA Board of Directors Donna Lucas, Chair Chief Executive Officer Lucas Public Affairs Mark Baldassare President and CEO Public Policy Institute of California Ruben Barrales President and CEO GROW Elect María Blanco Vice President, Civic Engagement California Community Foundation Brigitte Bren Attorney Walter B. Hewlett Member , Board of Directors The William and Flora Hewlett Foundation Phil Isenberg Vice Chair Delta Stewardship Council Mas Masumoto Author and Farmer Steven A. Merksamer Senior Partner Nielsen, Merksamer, Parrinello, Gross & Leoni, LLP Kim Polese Chairman ClearStreet, Inc. Thomas C. Sutton Retired Chairman and CEO Pacific Life Insurance Company The Public Policy Institute of California is dedicated to informing and improving public policy in California through independent, objective, nonpartisan research on major economic, social, and political issues. The institute’s goal is to raise public awar eness and to give elected representatives and other decisionmakers a more informed basis for developing policies and programs. The institute’s research focuses on the underlying forces shaping California’s future, cutting across a wide range of public poli cy concerns, including economic development, education, environment and resources, governance, population, public finance, and social and health policy. PPIC is a public charity. It does not take or support positions on any ballot measures or on any local, state, or federal legislation, nor does it endorse, support, or oppose any political parties or candidates for public office. PPIC was established in 1994 with an endowment from William R. Hewlett. Mark Baldassare is President and Chief Executive Officer of PPIC. Donna Lucas is Chair of the Board of Directors. Short sections of text, not to exceed three paragraphs, may be quoted without written permission provided that full attribution is given to the source. Research publications reflect the views of t he authors and do not necessarily reflect the views of the staff, officers, or Board of Directors of the Public Policy Institute of California. Copyright © 201 4 Public Policy Institute of California All rights reserved. San Francisco, CA PUBLIC POLICY INSTITUTE OF CALIFORNIA 500 Washington Street, Suite 600 San Francisco, California 94111 phone: 415.291.4400 fax: 415.291.4401 www.ppic.org PPIC SACRAMENTO CENTER Senator Office Building 1121 L Street, Suite 801 Sacramento, California 95814 phone: 916.440.1120 fax: 916.440.1121"
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