The author(s) shown below used Federal funds provided by the U.S. 

Department of Justice and prepared the following final report: 

Document Title: Parole Violations and Revocations in California 

Author: Ryken Grattet, Ph.D. ; Joan Petersilia, Ph.D. ; 

Jeffrey Lin, Ph.D. 

Document No.: 224521 

Date Received: October 2008 

Award Number: 2005-IJ-CX-0026 

This report has not been published by the U.S. Department of Justice. 

To provide better customer service, NCJRS has made this Federallyfunded grant final report available electronically in addition to 

traditional paper copies.

 

Opinions or points of view expressed are those 

of the author(s) and do not necessarily reflect 

the official position or policies of the U.S. 

Department of Justice.
Parole Violations and Revocations in 

California 

Ryken Grattet, Ph.D. 

Joan Petersilia, Ph.D. 

Jeffrey Lin, Ph.D. 

October 13, 2008 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
ACKNOWLEDGEMENTS


The authors wish to thank the many individuals and institutions who contributed to this 

research project. We could not have undertaken the study without the financial support of 

the National Institute of Justice, U.S. Department of Justice. Our program director, 

Marlene Beckman, provided logistical support, substantive feedback, and created several 

opportunities for us to connect with practitioners, experts, and other researchers. Gerry 

Gaes offered extensive feedback on our research design as well as excellent 

methodological advice after the project was underway. The members of the National 

Institute of Justice, Community Corrections Research Network provided us a forum to 

discuss the planning and preliminary results of the study that was essential to 

development of the project. 

The California Department of Corrections and Rehabilitation (CDCR), and particularly 

the Division of Adult Parole Operations (DAPO) and the Board of Parole Hearings 

(BPH), were close collaborators during the three-year duration of the project. Over the 

course of the project, we worked with Secretary Roderick Hickman, Undersecretary 

Kevin Carruth, Secretary Jeanne Woodford, Secretary James Tilton, and Steven 

Chapman, Assistant Secretary, CDCR Research Division. BPH and DAPO directors, 

particularly Richard Rimmer, James L’Etoile, John Monday, Jeff Fagot, and Thomas 

Hoffman were instrumental to assuring that we got the full cooperation of their 

organization and access to all necessary data. DAPO Director Thomas Hoffman took a 

particular interest in the project and his leadership and expertise on parole issues were 

critical to all phases of the project. Parole staff, including Bubpha Chen, Willie Bulda, 

Marilyn Kalvelage, Rick Winistorfer, Robert Ambroselli, Margarita Perez, Robert 

Stinson, Jeff Sellwood, Sharon Barton, Katie White-O’Neil, Chris Haws, and Carrie 

Daves answered endless question about the contents of CDCR databases. 

Additional support for the project came from the Center for Evidence Based Corrections 

at the University of California-Irvine and the Institute for Governmental Affairs at the 

University of California, Davis. A number of graduate students at the University of 

California, Davis and the University of California-Irvine assisted in data collection and 

analysis, including Ryan Fischer, Teresa Casey, Monica Williams, Demetra Kalogrides, 

and Danielle Rudes. Julie Siebens deserves special credit for the amazing programming, 

data management, and data analysis she did for the project. Diane Felmlee, Eric Grodsky 

John Hipp, Xiaoling Shu, and Susan Turner provided assistance with the research design 

and methodology. John Hipp, UCI, and Julie Young at the UCD College of Agricultural 

and Environmental Sciences, Center for Informatics provided extensive help with the 

geocoding of parolee address data. Jonathan Simon gave us many thoughtful and 

challenging comments on the final draft. 

To these individuals and the countless others who assisted us in our efforts, we are 

extraordinarily grateful. 

2


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
TABLE OF CONTENTS


SUMMARY................................................................................................................................................... 4


CHAPTER I. INTRODUCTION AND OVERVIEW OF STUDY ISSUES ......................................... 25


CHAPTER II. CONCEPTUAL FRAMEWORK AND DATA COLLECTION .................................. 34


CHAPTER III: UNDERSTANDING CALIFORNIA’S UNIQUE PAROLE ENVIRONMENT:


RELEASE, SUPERVISION, AND SANCTIONING .............................................................................. 43


CHAPTER IV: CHARACTERISTICS OF CALIFORNIA’S ADULT PAROLEES AND THEIR


SUPERVISION........................................................................................................................................... 58


CHAPTER V: WHAT FACTORS PREDICT PAROLE VIOLATIONS? ........................................... 65


CHAPTER VI: WHAT FACTORS PREDICT PAROLE REVOCATIONS AND RETURNS TO


PRISON?..................................................................................................................................................... 90


CHAPTER VII: CONCLUSIONS AND POLICY IMPLICATIONS ................................................. 115


REFERENCES ......................................................................................................................................... 130


APPENDICES .......................................................................................................................................... 134


3


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
SUMMARY


More than 2.3 million people are now incarcerated in the U.S.—more than one out of 

every 100 adult Americans. Incarceration rates are even higher for some groups: one out 

of nine black men, ages 20 to 34, are serving time. U.S. prison populations have 

experienced 15 years of steady growth and are now at all all-time high, outstripping that 

of any other industrialized country, both numerically and as a percentage of the overall 

population. 

As prison populations have expanded, states’ corrections costs have risen substantially. In 

2007, states spent $44 billion in tax dollars on corrections, up from $10.6 billion in 1987, 

a 127 percent increase when adjusted for inflation. As the U.S. economy slows and state 

budgets tighten, correctional spending is crowding out investments for other valuable 

programs, like health care and education. More and more, policymakers are questioning 

whether states are getting their money’s worth out of prisons and whether imprisonment 

is the most effective means of achieving public safety, especially when it diverts 

increasingly scarce funds away from other social services, some of which have been 

shown to prevent crime in the first place. 

Despite the fact that we are spending increasingly more on prisons each year, recidivism 

rates remain virtually unchanged, with about half of all released inmates returning to 

prison or jail within three years. Most prison systems are severely crowded, and the 

communities to which prisoners return experience a number of negative consequences as 

well. Clear (2007) argues that mass incarceration fractures families, threatens the 

economic infrastructure of already struggling neighborhoods, and leads to increased 

social stresses, especially for children.

1 Incarceration, in other words, may have exactly 

the opposite of its intended effect: it destabilizes the community, thus further reducing 

public safety. 

The debate about the costs and benefits of imprisonment is taking place all across 

America, but the stakes are highest in California. California’s 173,312 prisoners 

constitute the largest prison population of any state. One in seven state prisoners in the 

United States is incarcerated in California, and between 1980 and 2007, California’s 

prison population increased over sevenfold, compared with a fourfold increase nationally. 

And despite a 2003 vow by California Governor Arnold Schwarzenegger to reduce the 

prison population, it continued to grow and recent projections predict a prison population 

of 191,000 in the next five years. 

California’s prison expenditures are also among the highest in the nation—per inmate, 

per staff, and as a share of the overall state budget. The average annual cost of housing a 

California prisoner in 2006-7 was $43,287, 1.6 times higher than the national average of 

about $26,000. At the beginning of the prison building boom in the early 1980s, adult and 

youth corrections accounted for four percent of California’s General Fund expenditures at 

1 Clear, Todd R. (2007) Imprisoning Communities: How Mass Incarceration Makes Disadvantaged 

Neighborhoods Worse, Oxford University Press, NY. 

4


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
$1 billion per year. Today, California’s budget for state corrections is now over $10 

billion a year—and growing at a rate of seven percent annually, the fastest growing 

segment of the state’s criminal justice expenditures. State corrections now accounts for 

approximately ten percent of total California state spending—nearly the same amount the 

state spends on higher education. Even after adjusting for inflation, general fund 

expenditures to support California Department of Corrections and Rehabilitation (CDCR) 

operations increased 50 percent between 2001-2 and 2008-9. 

UNDERSTANDING CALIFORNIA CORRECTIONS AND THE 

IMPORTANCE OF PAROLE VIOLATIONS 

Central to California’s entire debate over its prison system is the topic of parole and 

parole revocation. California’s recidivism rate as measured by the “return to prison rate” 

is 66 percent, compared to a 40 percent national average. At the end of three years, 66 

percent of all California parolees had been returned to a California prison, 27 percent for 

a new criminal conviction and 39 percent for a technical or administrative violation, 

which can result from new crimes or violations of the conditions of parole. On any given 

day, six out of ten admissions to California prisons are returning parolees. 

Part of the explanation for California’s anomalously high parole return rate is its unique 

sentencing and parole system. California, for the most part, has a mandatory parole 

release system. California moved from an indeterminate to a determinate sentencing 

system in the late 1970s, and as a result, most offenders are released after they have 

served their original court-imposed sentence, less any accumulated good time credit. 

California’s Determinate Sentencing Law allows offenders to earn, with some exceptions, 

day-for-day “good time” (a 50 percent reduction). Only offenders sent to prison on a lifeterm (19 percent of prisoners in 2007) are subject to discretionary release, where the 

Board of Parole Hearings (BPH) and the Governor determine fitness for prison release. 

For about 80 percent of California prisoners, there is no appearance before a parole board 

to determine whether they are fit to return to the community; instead, they are 

automatically released. Once released, virtually all prisoners are placed on formal parole 

supervision, usually for three years. California is virtually alone in this practice of 

combining determinate sentencing and placing all released prisoners on parole. Most 

other states either have an indeterminate sentencing system, where a discretionary parole 

board determines release dates, or they reserve parole for only their most serious 

offenders. 

California’s growing prison population, combined with its universal parole practices and 

lengthy parole terms, has resulted in California supervising far more parolees than any 

other state. The Bureau of Justice Statistics reports that in 2007, California supervised 

about 120,000 parolees on any given day, accounting for 15 percent of all parolees in the 

country.

2 

California’s parole population is now so large and its parole agents are so overburdened 

that parolees who represent a serious public safety threat are not watched closely, and 

2 Glaze, L., and T. Bonczar (2007), Probation and Parole in the United States, 2006, Bureau of Justice 

Statistics, Washington DC, NCJ 220218. 

5


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
those who wish to go straight cannot get the help they need. About 80 percent of all 

California parolees have fewer than two 15-minute face-to-face meetings with a parole 

agent each month, and nearly all of these meetings take place in the parole agent’s office. 

Two-thirds of all California parolees are thought to have substance abuse problems and 

nearly all of them are required to be drug tested. Yet, few of them will participate in 

appropriate treatment while in prison or on parole. California’s recent Expert Panel on 

Adult Offender Recidivism found that fully 50 percent of all exiting California prisoners 

did not participate in any rehabilitation or work program, nor did they have a work 

assignment, during their entire prison stay. They didn’t get the help they needed on 

parole either: 56 percent of parolees didn’t participate in any formal program while under 

parole supervision.

3 

Clearly, this low level of supervision and service provision does not prevent crime. As 

noted above, two-thirds of all California parolees return at least once to a California 

prison within three years. Due to their high failure rate, parolees account for the bulk of 

California prison admissions: In 2006, nearly two-thirds (64 percent) of all persons 

admitted to California prisons were parole violators. Parole revocations have been rising 

nationally over the last 20 years, but California’s have increased more so. Nationally, 

over the last 20 years, the number of parole revocations has increased about six-fold. In 

California, the number of parole revocations has increased 30-fold. 

California’s unique decision-making process partly explains its high parole revocation 

rate. The decision to send a parole violator back to prison for an additional sentence is not 

often made in California by a judge, but rather by a politically appointed deputy 

commissioner at the Board of Parole Hearings. Criminologists have coined the term 

“back-end sentencing” to describe how the parole revocation process centers on parole 

board practices. Not only are back-end sentences determined by correctional officials 

instead of judges, but the standard of evidence used is much lower than is required in a 

court of law. Parole board officials use the more lenient legal standard of “preponderance 

of the evidence,” as opposed to the “beyond a reasonable doubt” standard that is required 

in criminal court convictions. This more lenient standard is deemed appropriate because a 

California prisoner still remains in the legal custody of the CDCR while on parole. Parole 

in California is not a reward for good behavior, as it might be in an indeterminate 

sentencing state, but rather an extension of a felon’s sentence and a period of extended 

surveillance after prison. As such, if the parolee does not abide by the imposed parole 

conditions, the State has the legal right to revoke their parole term and return them to 

prison. 

California’s parole revocation process is also unique in another way. The maximum term 

for a parole violation in California is 12 months in prison. If a parolee is sentenced to that 

maximum term, there is usually a day-for-day credit for time served in prison or in jail 

awaiting case disposition, assuming no prison rule infractions. The upshot is that the 

parole violator who is not convicted of a new crime by a criminal court—totaling nearly 

3 California Expert Panel on Adult Offender Recidivism Reduction Programming. (2007). A Roadmap for 

Effective Offender Programming in California: Report to the California State Legislature. Sacramento, 

CA: California Department of Corrections and Rehabilitation. 

6


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
70,000 prison commitments in 2006—will only spend, on average, slightly more than 

four months in custody.

4 And of course, not everyone gets the maximum 12-month 

sentence. Data analyzed by California’s Rehabilitation Strike Team found that of all 

parolees returned to a prison in 2004, 20 percent—one in five parole violators—served 

less than one month in a California prison.

5 

This system of “catch and release” makes little sense from the standpoints of deterrence, 

incapacitation, treatment, or cost. Parolees quickly learn that being revoked from parole 

doesn’t carry serious consequences, and the State will have wasted the resources of the 

police, the parole board, and parole officers, who have to reprocess the same individuals 

over and over again. This constant churning of parolees also disrupts community-based 

treatment, since parolees who are enrolled in community treatment programs are 

constantly having that treatment disrupted for what, in the treatment providers’ views, are 

predictable and minor rule violations (e.g., testing positive for drug use). Churning also 

encourages the spread of prison gang culture into the communities where inmates are 

discharged, while undercutting the deterrent effect of serving prison time. And of course, 

given California’s overcrowding crisis, there is the high opportunity cost of occupying a 

limited number of prison beds that, in some cases, could be used for offenders who pose a 

greater risk to the public safety. 

Policymakers and practitioners agree that an overhaul of California’s parole system is 

urgently needed. In fact, more than a dozen reports published since 1980 have 

recommended changes in California’s parole revocation procedures. Unfortunately, 

California’s parole violation process is so complex and involves decisions by so many 

parties, including the police, prosecutors, judges, parole agents, and parole board 

commissioners, that understanding exactly what needs to be done to fix the problem is 

unclear. 

In September 2005, the National Institute of Justice (NIJ) funded the authors to undertake 

a three-year comprehensive study of the causes and consequences of parole violations 

and revocations in California. The study was supported fully by the California 

Department of Corrections and Rehabilitation (CDCR), the umbrella agency that 

oversees all of California state corrections. Their cooperation was essential to access and 

understand the extensive data that our project required. We believe our study represents 

the largest, most comprehensive, and most rigorous study of parole violations and 

revocations (returns to prison) ever conducted. 

STUDY RESEARCH QUESTIONS & DATA 

To better understand the complexities of the parole violation process and the 

characteristics of parolees who are returned to prison, we needed to unpack the “black 

box” of the parole violation and revocation process. We needed to study not only 

parolees’ characteristics, but also the characteristics of the supervising agency, parole 

agents, and the communities to which parolees return. We needed to identify the key 

4 California Expert Panel, note 3.
 5 Governor Schwarzenegger’s Rehabilitation Strike Team Report (2007), Sacramento, CA: California


Department of Corrections and Rehabilitation.


7


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
decision points that ultimately lead to parole revocation and prison returns, and also how 

characteristics of the parole agent, caseload type, and variations in community 

characteristics impact the processes of violation and revocation. 

We also had to better understand the critical role of the Board of Parole Hearings (BPH), 

which has the ultimate responsibility for deciding which parole violators are returned to 

prison and which are allowed to remain in the community. In the mid-1990s, California 

adopted a “zero tolerance” policy for “serious” and “violent” parolees (as defined in the 

Penal Code), such that parole agents are required to report every offender originally 

convicted of these crimes who violates any condition of parole to the BPH for 

disposition. The BPH is a politically appointed body and has a history, especially in 

recent years, of returning to prison most parolees coming before it. The BPH may be the 

most important gatekeeper of using prison for the sanctioning of parole violations, and 

yet their role and impact has gone virtually unnoticed and unstudied. 

We assembled an extraordinarily large and complex database that tracks every adult on 

parole in California at any point during the calendar years 2003 and 2004. The resulting 

study sample consisted of 254,468 separate individuals. These parolees were responsible 

for 151,750 parole violations that made it to the court or board hearing level (thousands 

more were terminated at the parole unit level) over the two study years. These parole 

violation and revocation incidents were the central focus of our study. In addition to 

recording the details of each parolees’ behavior on a weekly basis during the two year 

study period, we also merged data about each parolee reflecting their personal 

characteristics and criminal histories, the nature and types of supervision to which they 

were subjected, the characteristics of agents who supervised them, and the communities 

to which they returned. 

The combined database allowed us to analyze the way in which three clusters of 

factors—reflecting characteristics of the parolee, the agency and the community— 

interact to produce variations in parole outcomes. We address these and other critical 

questions: 

1.	 What basic patterns of violations characterized the population of parolees during 

2003 and 2004? What kinds of offenders were on parole during the period and 

what kinds of violations were they found to commit? 

2.	 What individual, organizational, and community factors affected violations? Did 

different factors affect different kinds of violations? 

3.	 What basic patterns of revocations characterized the population of parolees during 

2003 and 2004? What kinds of violations were handled by local criminal courts? 

What kinds of violations did the parole board process? 

8


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
4.	 What case, individual, organizational, and community factors affected decisions 

to prosecute criminal violations in criminal courts, as opposed to referring them to 

the parole board (California Board of Parole Hearings, or BPH)?

6 

5.	 What case, individual, organizational, and community factors were related to the 

likelihood that an offender would be returned to prison by the parole board, 

holding constant the severity of their violation and their criminal history? 

In addition to answering these and other research questions, the research also investigates 

the major aspects of California’s sentencing and parole system that we believe impact 

parole revocations and prison returns. Because California releases nearly all prisoners 

subject to its Determinate Sentencing Law, with no opportunity to retain even the most 

likely recidivists, and then places all of them on parole supervision, the state’s parole 

agents end up supervising some individuals who pose a far more serious threat to society 

than the typical parolee in a state with discretionary release. In states that use 

discretionary release, these high-risk prisoners can be denied parole and kept in prison. 

California parole officers often point out that their high revocation rates are caused by the 

behavior of parolees who were almost certain to reoffend and should not have been 

released from prison in the first place. 

On the other hand, since California law allows minor technical parole violators to be 

returned to prison (whereas some states do not), and these prisoners are also eventually 

released to parole supervision, California parole caseloads also include many “less 

serious” offenders as well. This point is critical to understanding parole violations in 

California: California parole caseloads likely contain offenders at both extremes of the 

seriousness continuum—offenders who probably would not be on parole in other states, 

either because they are too serious to have been released from prison in the first place by 

parole boards operating in indeterminate states, or because they are such low-risk 

offenders that they wouldn’t have been assigned to post-prison parole supervision at 

release. The upshot is California parole caseloads probably contain some of the nation’s 

highest risk offenders as well as the some of the nation’s lowest risk offenders. 

California’s Determinate Sentencing Law (DSL) not only changed the way in which 

prisoners got automatically released and required all prisoners to serve a post-prison 

parole term, but it also simultaneously and significantly increased both the length of the 

initial parole supervision term imposed and the length of the prison term that could be 

subsequently imposed if the parolee violated parole conditions. Before the passage of the 

DSL in 1977, prisoners released to parole were subject to a one-year period of parole. But 

DSL tripled the length of time on parole for most prisoners. Equally important, DSL also 

doubled the length of prison time that can be imposed upon parole revocation from six 

months to one year. And under California law, when a person is returned to prison for a 

parole violation, the “clock stops” on the time owed for parole supervision. So, when a 

person leaves prison after serving time for a parole violation, he still faces the remaining 

supervision time he owed the State before he went back to prison for the violation. As 

such, parole supervision can stretch out for years for particular individuals. Offenders 

6 BPH was formerly called the Board of Prison Terms (BPT). 

9


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
often call it “doing a life sentence on the installment plan” since they go in and out, never 

able to formally discharge from parole supervision. 

In addition to changes in sentencing policy and the structure of parole, in the last decade, 

the discretion held by California parole agents in the handling of violations has 

substantially eroded. Over the last several years, BPH implemented new regulations that 

significantly added to the list of parole violations DAPO is required to refer to the parole 

board, thereby exposing more parolees to BPH decisions to return them to prison. 

Whereas once parole agents and supervisors wielded discretion about how to handle 

many violations, now much of that authority has shifted to the BPH. DAPO estimated 

that in 2005, 85 percent of parole violations, including technical violations, were subject 

to mandatory referral policies. This means that parole agents and their supervisors have 

very little discretion in the handling of these cases and these offenders. The BPH makes a 

decision about whether or not to return the parolee violator to prison, and the vast 

majority of cases that go before the BPH result in a return to prison. In 1993, about 65 

percent of parolees referred to BPH for parole violations were returned to prison and 35 

percent were continued on parole. By 2007, however, about 90 percent of parolees were 

returned to prison by BPH and only 10 percent were continued on parole. Whether these 

mandatory referral rules are appropriate or not is a political determination, but one thing 

is clear: parole agents, parole supervisors, and the DAPO division retain discretionary 

decision-making power over a declining percentage of violations. 

Like California’s sentencing system, discretion in parole has shifted from corrections 

professionals to legislative and regulatory bodies that are politically elected or appointed. 

This change has occurred with virtually no discussion or public input, but the 

consequences are critically important. For one, it means that much is written erroneously 

about how changes in parole agent recruitment, training, or culture could reduce the 

number of parolee returns to prison. The parole agent recommends the disposition for the 

violation (e.g., to prison or not), but ultimately, the parole board has the sole authority to 

return a parolee to custody. These and other legal and procedural constraints are 

important to understanding the very complicated processes of prison release, parole 

supervision, and all too often, return to prison. 

The growth of California’s prison population, combined with the policy of placing all 

exiting prisoners on parole supervision for three years, simultaneously reducing the 

discretion of parole agents to handle minor violations for an increasing proportion of 

parolees, and increasing the prison time served for violations, provides the requisite 

conditions for the growing contribution of parole violators to the state prison population. 

No other state has created this hybrid system—shifting simultaneously to fixed-term 

prison release and universal parole supervision—while at the same time reducing parole 

agent discretion, and lengthening parole terms and prison terms upon revocation. 

Our hope is that the empirical data analyzed in this report will permit California 

policymakers to devise more sound parole supervision and revocation policies which 

better balance public safety and public resources. Importantly, such research should help 

10


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
advise policymakers on the “seriousness” of parole violators being returned to California 

prisons, which in turn can greatly influence the prison capacity discussion. 

DATA AND ANALYTIC APPROACH 

Our statistical models separately investigate the prediction of parole violations, which are 

largely behavioral events, and the prediction of parole revocations, which reflect system 

responses to that behavior. We relied solely on official records rather than offender selfreports, even though we recognized that not all (or even most) parole violations came to 

the attention of authorities. Our database consisted of detailed information about every 

adult on parole in California at any point during 2003 and 2004. The resulting sample 

was comprised of 254,468 separate individuals. Some individuals were already on parole 

at the start of our study (January 1, 2003), whereas others were either free or in prison at 

the start of our study, but were released to parole at some time during the two-year study 

period. Study subjects were observed for two years (January 1, 2003 – December 31, 

2004). However, since many subjects were already on parole at the start of the study 

period, we were able, through various methods of statistical estimation, to analyze 

violation and revocation patterns over longer periods of time. 

We assembled a detailed personal and parole supervision profile for each parolee in the 

sample, consisting of their demographic characteristics and criminal records, the type(s) 

of parole supervision to which they were assigned, and all new technical and criminal 

recidivism events that occurred during the study period. For each parolee, we also 

recorded information about their supervising parole agent (e.g., age, race, gender, job 

tenure) and, using the parolee’s address, characteristics of the community to which the 

parolee returned upon release from prison. Data were merged from over a dozen different 

state and national databases to create as comprehensive a profile as possible for each 

subject. 

With the databases assembled and merged, we were then able to conduct our statistical 

analyses. In terms of parole violations, we structured the data for survival analysis—a 

multivariate method that examines both the likelihood and timing of violations. This 

statistical approach required that the data be arranged such that each individual parolee 

was observed on a weekly basis throughout 2003 and 2004. The data format allowed us 

to construct multivariate survival models predicting the likelihood and timing of different 

types of violation behavior. 

For our analyses of parole revocations, we created a dataset documenting every parole 

violation case heard in criminal court and/or by the California Board of Parole Hearings 

(BPH). These data, reflecting 151,750 violation reports, were used to estimate logistic 

regression models predicting revocation outcomes of interest—specifically, whether 

criminal violation cases were successfully prosecuted in court as opposed to being 

referred to the parole board, and whether cases heard by the BPH were returned to prison 

or continued on parole. Thus, we were able to assess the relative impact of individual, 

organizational and community level measures on numerous parole outcomes. In all 

analyses, we investigated the likelihood (i.e., probability) as well as the severity of the 

outcome. 

11


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
In addition to the administrative data we compiled, we also collected extensive 

qualitative information from field observations, staff interviews, and reviews of agency 

directives and policy memos. 

DEMOGRAPHIC AND CRIME PROFILES OF CALIFORNIA PAROLEES 

There were 254,468 adults on parole supervision in California at some time during 2003 

and 2004—accounting for one in seven parolees supervised in the U.S. during that time. 

The characteristics of parolees in our sample resembled those of the California prison 

population in many ways, which is not surprising given that under California’s 

Determinate Sentencing Law, all prisoners are released at the expiration of their prison 

term and placed on a three-year term of parole supervision. Most parolees in our sample 

were male (90 percent), minority (70 percent), and young (52 percent younger than age 

30). Nearly half (46 percent) had previously been on parole, and more than ten percent 

had been on parole six or more times. Most of the sample had served their most recent 

prison term as a result of a property (29 percent) or drug conviction (35 percent), but 20 

percent had been convicted of a violent crime, and five percent had been convicted of sex 

crimes. About 20 percent of parolees were considered “serious” or “violent” according to 

California’s official penal code designation. 

More than one in five (21 percent) parolees had an officially documented mental health 

condition, and seven percent were required by statute to register as sex offenders. Six in 

ten parolees in the sample had served less than a year in prison prior to their current 

release on parole. 

WHAT PREDICTS PAROLE VIOLATIONS? 

Nearly half (49 percent) of the parolees in our sample had at least one formal parole 

violation report during our study period, and 24 percent had multiple parole violation 

reports. Each report could contain multiple violations of any type (e.g., criminal, 

technical). Together, these parolees were responsible for 296,958 violation reports. 

CDCR tracks 247 different types of prohibited parolee behavior, ranging from violations 

of the parole process, usually referred to as “technical violations,” to serious and violent 

criminal offenses like robbery, assault with deadly weapons, and homicide. 

Over a third (35 percent) of all the recorded parole violations were for noncriminal or 

“technical” violations. Two-thirds of technical violations were for absconding 

supervision, meaning that the parolee missed an appointment and/or his or her 

whereabouts were unknown. Other technical violations include weapons access, 

psychological endangerment, and various violations of the parole process, such as 

violations of special conditions of parole imposed by a parole agent or deputy 

commissioner. Interestingly, if one adds up all of the parole violation reports that pertain 

to drug use or drug sales—there are over 110,000 of them—they comprise over a third of 

all parole violation reports (37 percent) during our study period. 

Two-thirds (65 percent) of all parole violations were for new criminal behavior (arrests). 

Using CDCR’s internal classification system, 39 percent of these new criminal violations 

12


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
were classified as Type I (“the least serious”—mostly drug use and possession), 17 

percent were classified as Type II (“moderately serious”—e.g., forgery, drug sales, 

burglaries, battery without serious injury, driving violations), and ten percent —nearly 

29,000 violation reports—were classified as Type III (“the most serious”—e.g., major 

assaults, major drug crimes, robberies, rapes, and homicides). 

In terms of the timing of violations among parolees in the study, the risk of all kinds of 

violations was highest during the first 180 days following release from prison, and 

declined thereafter. A major reason behind this declining risk pattern was that the most 

risk-prone parolees tended to be violated earlier and returned to prison. The remainder 

were probably more compliant, less likely to violate, and more likely to successfully 

complete their parole period. Indeed, after 360 days on parole, a “surviving” parolee’s 

risk of violation had dropped 70 percent from what it was during the first two months of 

parole. From 360 to 900 days, a parolee’s risk only dropped another ten percent. In other 

words, after about 360 days, a parolee’s risk of violation—while not zero—had 

substantially leveled off. 

In terms of demographic and other personal characteristics, the youngest parolees, aged 

18-30, posed the greatest risk of all kinds of violations except Type I criminal violations 

(the least serious). Male parolees posed significantly higher risks for all types of 

violations except absconding. Black parolees posed the same risks as non-black parolees 

for technical violations but much greater risks than parolees from other racial 

backgrounds for the most serious and violent criminal violations. Parolees with a record 

of mental health problems had higher risks for all types of violations, and they had 

particularly elevated risks for the most violent criminal violations. 

The single biggest predictor of parole violation risk was a parolee’s number of prior adult 

prison incarcerations in California. For all violation types, an offender coming out on 

their second release from prison had a 20 percent higher risk of violation than an offender 

on their first release. An offender on their third release had a 39 percent higher risk of 

violation than an offender on their first release. By the ninth release, an offender had a 

124 percent higher risk of violation than an offender on their first release. 

In general, the extent of prior criminal record had more predictive value than the 

seriousness of prior record, but certain “seriousness indicators” did exhibit relationships 

to violation risk. Age at first adult commitment to a California prison, for example, 

predicted Type III (the most serious) criminal violations. For every additional year older 

a parolee was at their first prison commitment, their risk of a Type III violation decreased 

by 2.5 percent. However, parolees who were older when first committed to California 

prisons tended to present higher risks for technical violations and Type I criminal 

violations. This latter group was probably largely composed of drug offenders that had 

substance dependence driving their offending, and as a result of drug use, were prone to 

generating technical and Type I criminal violations, but were less likely to be involved in 

more serious criminal behavior. 

The seriousness of the current commitment offense, while exhibiting a relationship to 

violation risk, did not predict violations in the ways that policymakers often assume. 

13


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Parolees committed for violent and sex offenses, overall, had lower risks for most 

violations than those offenders committed for property and drug crimes. However, those 

who had been committed for violent offenses did show elevated risk for violent criminal 

violations and serious sexual violations. 

Sex offender registrants posed lower risk for violations than non-sex offenders for several 

types of violations (e.g., having any violation, absconding, Type I criminal violations). 

Sex offender registrants were no more likely to commit the most violent violations than 

other offenders. 

Policymakers are particularly interested in the threat that sex offenders pose to commit 

further sex crimes, so we investigated these outcomes separately. We did find that sex 

offender registrants were more significantly more likely to be violated for sex crimes, but 

it is critical to note that sexual violations were very rare, constituting 1.5 percent of all 

violations during the study period, and about two-thirds of them were victimless offenses 

caused by sex offenders failing to register under California Penal Code section 290. 

Moreover, the majority of sexual violations, including the most serious violations 

involving rape, sexual assault, and child molestation, were committed by parolees who 

were not registered sex offenders. Setting aside the violations involving failure to 

register, of the 1,528 sexual violations committed during 2003 and 2004, just 25 percent 

were committed by sex offender registrants. The vast majority of sexual violations, 

including 78 percent of the most serious Type III sexual violations, were committed by 

non-sex offender registrants. 

Intensity of Supervision, Parole Agent Characteristics, and Parole Organization 

California parolees are assigned to one of five levels of supervision, with the assigned 

level determining the frequency and degree of oversight provided by parole agents. 

Twenty-three percent of parole supervision performed during 2003 and 2004 was 

classified as “Minimum Service,” with the requirement that parolees see their parole 

agents only twice a year. Most contact between agents and parolees under Minimum 

Service supervision is done through the mail; that is, parolees periodically mail a postcard 

to their agents to check in. Another 43 percent of supervision during our study period was 

classified as “Control Service;” parolees supervised at this level see a parole officer once 

every six weeks. These two classifications—in which relatively little supervision or 

programming is actually applied to parolees—accounted for 65 percent of the total 

supervision applied to parolees in 2003 and 2004. 

Given that these offenders are placed in low risk categories because they are not expected 

to be likely recidivists, one cannot help but wonder whether the effort expended to 

provide cursory oversight to so many former inmates is an effective use of resources. 

This issue is particularly pressing because California loses track of so many of its 

parolees, and one wonders if greater intensity of supervision or services for higher risk 

parolees could help prevent new crimes, or if the resources expended could be better used 

to locate those whose whereabouts are unknown. On any given day, nearly 17 percent of 

all California parolees—more than 20,400 people—are “parolees-at-large,” meaning they 

14


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
have absconded supervision. This is the highest abscond rate in the nation and is far 

above the national average of seven percent. 

We found that, consistent with prior research, supervision intensity affected the risk 

of reported violations. More intensive parole supervision increased the risk of all 

violations, holding constant the offender’s personal attributes, offense background, 

and community conditions. The biggest differences in the effects of supervision on 

violation risk were found in the contrast between Minimum Service supervision and 

“active supervision” (i.e., supervision at all other levels). Parolees who were on 

Minimum Service caseloads, which involved infrequent face-to-face or collateral 

contact, monthly mail correspondence, and no narcotics testing, had significantly 

lower risks for all kinds of violations than those parolees who were more actively 

supervised. 

The differences in violation risk between parolees on Minimum Service supervision 

and active supervision were most pronounced among the most discretionary 

violations—technical violations not involving absconding and Type I criminal 

violations (the least serious, mostly involving drug use and possession). Compared to 

Minimum Service parolees, actively supervised parolees had between two and three 

times the risk of technical and Type I criminal violations. Active supervision parolees 

also had consistently higher risks of absconding, Type II, Type III, and violent 

criminal violations, although the differences were not as great as among the more 

discretionary violation types. What became clear from the contrast between active 

and Minimum Supervision was that more closely supervised parolees did not seem to 

be deterred from violation behavior. 

We also detected differences in violation risks among active supervision categories, 

but these differences were not as pronounced as those between active supervision and 

Minimum Service supervision. Parolees in more intensive supervision categories, in 

general, posed higher risks for violations. 

California is subdivided into four parole regions, each supervising roughly one-fourth of 

the California parole population. The regions are understood to have differences their 

organizational cultures and in the types of parolees they supervise. Region 3, which is 

comprised entirely of Los Angeles County, is perceived to be the most overstretched and 

harried part of the parole system, responsible for supervising the most serious parolees in 

the state. As a result, some believe that there is a lower rate of reporting of less serious 

violations in Region 3, as they have more serious criminal violations to contend with (i.e., 

“bigger fish to fry”). 

We found little support for regional differences in parole outcomes. Once the 

characteristics of parolees and communities were statistically controlled, Region 3 

reported violations in a similar manner as the other three regions. Region 3 did report 

fewer drug use and possession violations (Type I criminal violations), but its reporting 

patterns for technical violations—both absconding and violations of the parole process— 

was not different from other regions. Nor was the risk that a parolee in Region 3 would 

be cited for a Type II or Type III criminal violation different from other regions. 

15


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
We also explored the extent to which differences in parole outcomes were traceable 

to parole agent characteristics, and were able to detect some relationships between 

agent characteristics and violation risk. We found that female agents (who performed 

28 percent of parole supervision during 2003-2004) appeared to exercise discretion 

in ways that were more forgiving of low level criminal violations (i.e., Type I, mostly 

drug use and possession). Male agents, on the other hand, appeared to adopt a more 

lenient approach toward absconding than female agents. No gender differences were 

found in the reporting of the more serious Type II and III criminal violations. 

Research literature suggests that, as a group, black parole agents might have more 

tolerance for less serious violations. During our study, 32 percent of all supervision 

was done by black agents, 25 percent by Hispanic agents, 35 percent by white agents, 

and the rest was performed by Asian agents and those from other racial categories. 

Black agents, like blacks in the rest of American society, may be more likely to have 

friends or family members who have had contact with the criminal justice system. As 

a result, research suggests they might be more sensitive to the conditions that foster 

criminal behavior and more wary of the effectiveness of system responses. 

Therefore, black agents may have more tolerance for less serious violations. Our 

results supported this argument. Parolees supervised by black agents had lower risks 

of technical violations and Type I criminal violations. But parolees with black agents 

were no different than other parolees in terms of their risks for Type II and III 

criminal violations. 

Nearly half (48 percent) of parole supervision during 2003-2004 was done by parole 

agents having less than three years of job experience as a parole agent. Thirty percent 

of supervising agents were under 40 years of age, and 83 percent of agents had 

previously worked in a CDCR correctional institution. We were told that older agents 

and those who have not worked in the prison system as correctional officers are more 

likely to see “shades of gray,” and thus tolerate some parolee behavior that other 

agents would elect to violate. Contrary to expectations, parolees assigned to agents 

with prior employment experience in a prison actually had an eight percent lower 

risk of the least serious Type I criminal violations than parolees assigned to agents 

with no prior prison employment. Prior employment in a prison did not affect the 

risks for any other type of criminal or technical violation. Moreover, neither parole 

agent age, nor tenure on the job as a parole agent, was significantly related to any 

type of criminal or technical violation. 

CDCR announced a number of significant parole policy changes during 2003 and 2004. 

One policy, referred to as the “New Parole Model,” was announced with much fanfare in 

February 2004, before being scaled back significantly in April 2005. The New Parole 

Model proposed the greater use of intermediate sanctions for parole violators and the 

adoption of a parole violation matrix to standardize the handling of violations. We found 

no evidence that this announced policy change had any observable impact on parole 

decision-making or case processing outcomes at the aggregate level. 

16


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Community Conditions and Reentry Environments 

Research suggests that community characteristics can have criminogenic or reintegrative 

effects on parolee behavior. In other words, neighborhood factors can either promote or 

guard against illicit activities. Communities with greater financial resources may be able 

to fund more rehabilitation and work programs, which can provide parolees with 

pathways out of criminal lifestyles. Communities with more progressive political views 

may have more tolerance for minor rule violations. Less socioeconomically 

disadvantaged communities may provide better informal social supports that suppress 

criminal activity (i.e., increased residential stability). On the other hand, socially 

disorganized (i.e., disadvantaged) communities may not be able to fund many alternatives 

to prison, and may exhibit other conditions that are conducive to criminal behavior. 

Politically conservative communities may have less tolerance for illicit behavior, and 

may exhibit an increased propensity to violate parolees. 

To explore these ideas, we used parolee address records to link individuals to data about 

their communities. For example, we mapped parolee addresses to U.S. Census Tracts to 

compile measures of poverty, unemployment, and public assistance. As a measure of 

service availability in parolees’ reentry environments, we drew data from the United 

States Substance Abuse and Mental Health Services Administration (SAMHSA) listing 

the addresses of all substance abuse and mental health treatment providers in California 

that accept clients from criminal justice agencies. And to generate a county-level measure 

of the “punitiveness” of different communities, we collected information on the results of 

ballot proposition voting and party registration from the Secretary of State. We selected 

data reflecting voting patterns of ballot propositions that pertained directly to state 

correctional practices—for example, Proposition 36, which allows some nonviolent, drug 

offenders to receive treatment instead of incarceration, and Proposition 66, which 

proposed a scaling back of California’s “three strikes” law. Our hypotheses were that 

community conditions and attitudes, as well as the availability of treatment, would be 

related to parole practices. 

We found modest support for these hypotheses as they relate to an understanding of 

parole violations in California. Parolees who lived in neighborhoods that scored highly 

on socioeconomic disadvantage were at greater risk to abscond than parolees who lived 

in less disadvantaged environments. However, parolees residing in disadvantaged 

neighborhoods did not pose a greater risk to commit other kinds of violations than those 

from less disadvantaged neighborhoods. 

Importantly, we found some evidence that the availability of substance abuse and mental 

health treatment services lowered the risk of Type I (the least serious) criminal 

violations—which mainly involved drug use, drug possession and misdemeanor 

violations of the law. This may have been attributable to the effectiveness of these 

programs, but it may also have been due to a “parole agent effect;” that is, parole agents 

may have been less likely to violate parolees for low level violations when they perceived 

that there were program opportunities that posed alternatives to initiating the formal 

violation and revocation process. Given that there were few alternatives to prison during 

17


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
2003-2004, this observed effect is important and may be strengthened if more programs 

were in existence. 

WHAT PREDICTS PAROLE REVOCATIONS AND RETURN TO PRISON? 

There are two ways parolees experience revocation: through county criminal courts and 

through the parole board (BPH). Courts only handle criminal violations—those that result 

from an arrest by a police officer or parole agent. The BPH handles technical violation 

cases, as well as criminal violation cases that county courts do not successfully prosecute. 

Technical violations are violations of the rules or conditions of parole. These violations 

do not involve new convictions, although they can involve a new arrest for which there 

was no conviction. The process by which cases are sorted through one venue versus the 

other, as well as the reasons that some parole violators are returned to custody while 

others are allowed to remain in the community, are not well-understood. 

The parolees in our study sample generated 151,750 parole violation cases in 2003 and 

2004 that were processed either through the criminal court system or the parole board 

(BPH). Eighty-four percent (127,742) of these cases involved new criminal violations. 

These criminal violation cases were heard first in criminal court, and if a conviction 

could not be obtained in court, they were referred for assessment by the parole board. 

Sixteen percent (24,008) of all cases only involved technical violations, and these cases 

were heard by the parole board. Importantly, the board operates under a more lenient 

standard of evidence than the courts, and may only return a parole violator to prison for a 

maximum term of 12 months. 

Of the 127,742 criminal violation cases reported during 2003 and 2004, 25 percent 

(31,417 cases) resulted in a new prison term delivered in criminal court. The other 75 

percent (96,325 cases) were referred to the parole board. Among these referred criminal 

violation cases, the board elected to return 73 percent to prison. Not surprisingly, more 

serious criminal charges were more likely to result in a prison return. Type III violation 

cases—the most serious—resulted in prison return 88 percent of the time. Moderately 

serious criminal cases (Type II) resulted in return almost as frequently; these parole 

violators were returned 80 percent of the time. The least serious criminal cases (Type I) 

only resulted in return to prison 52 percent of the time. Thus, when moderately serious 

and very serious criminal parole violations are evaluated by the board, the certainty of 

return is extremely high. The board appears to exercise greater discretion over cases 

involving Type I crimes—most of which involve drug use and possession violations. 

A small but significant number of violent crimes, such as homicide, robbery and rape, 

were processed through the parole board.

7 These crimes carry lengthy prison terms when 

they are prosecuted in courts of law. However, when handled through the parole board, 

the maximum return time is capped at 12 months. Even though the proportion of 

homicide, robbery and rape cases constituted a very small share of the total number of 

criminal parole violations returned to custody through the board, the fact that such cases 

7 In 2003 and 2004, the board returned parolees for 246 homicides, 1,006 robberies, and 691 crimes 

involving rape or sexual assault—together accounting for 1.5 percent of all criminal violation cases during 

this time. 

18


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
were pursued in this arena is significant. The board was clearly not a venue that 

exclusively dealt with “small time” criminal cases. Even though minor offenses appeared 

to be the norm, cases involving serious offenses were also heard in this venue. Further, 

because the board operates under a more lenient standard of evidence, there is a greater 

possibility that factually innocent criminal parole violators may be returned to custody. 

Adding together the criminal violation cases that resulted in a new term through criminal 

courts, and those criminal violation cases that resulted in a return to prison through the 

parole board, we found that among the 127,742 criminal violation cases officially 

recorded in 2003 and 2004, over three-quarters (77 percent) resulted in some form of 

prison return, either through the courts or through the board. 

In addition to criminal violation cases referred from courts, the parole board also heard 

24,008 technical violation cases (16 percent of all cases)—many of which involved 

absconding. Like criminal violation cases, technical violation cases heard by the parole 

board exhibited a high rate of prison return. About 85 percent of these technical violation 

cases resulted in a return to custody. Those cases involving technical charges (without 

absconding) were returned 79 percent of the time. Cases involving absconding (without 

other technical charges) were returned 85 percent of the time. Cases involving both 

technical and absconding charges were returned 91 percent of the time. Overall, the board 

returned 75 percent of all violation cases it heard. 

We next turned to understanding the patterns and logic of the parole revocation process. 

Our analysis was designed to answer two interrelated questions: What factors affected the 

sorting of violation cases through the courts versus through the parole board, and, once in 

front of the parole board, what affected the chances that a parolee would be returned to 

custody, as opposed to being continued on parole? Like our multivariate analysis of 

parole violations, we examined how parolee characteristics, organizational factors, and 

community characteristics impacted revocation decision-making. We also investigated 

the relationship between case characteristics—such as the number and severity of 

violation charges—and revocation outcomes. 

Case and Individual Characteristics 

Violation case characteristics were critical to determining whether or not criminal 

violation cases were processed through criminal courts or through the parole board. They 

also influenced whether a case processed by the parole board resulted in a return to 

prison. As expected, cases involving more charges, and more serious charges, were likely 

to receive harsher treatment. In court decisions, the number of criminal charges contained 

in a case was not related to decisions to reimprison, but the severity of those charges did 

predict court sanctioning decisions. Board decisions were, for the most part, driven by 

both the number and severity of charges involved in violation cases. 

In terms of individual factors, parolees with longer, and more serious, histories of 

criminal behavior were likely to be considered public safety risks by court and board 

decision-makers, and their cases were treated accordingly. Net of the seriousness of their 

current parole violations, parolees’ histories of imprisonment, for example, were 

19


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
significantly predictive of harsher treatment in both decision venues. Those who had 

served more adult prison spells (both for new court-ordered terms and returns to custody 

on parole violations) in California were more likely to be sent back to custody by both the 

court and the board. Parolees on their “second strike” were also significantly more likely 

to be returned through the court than parolees without such status, and when their cases 

were referred to the board, they were significantly more likely to be re-incarcerated in 

cases involving criminal violations. 

Statutorily-defined “serious” and “violent” offenders were actually less likely than others 

to experience court return to prison, but when their criminal violation cases were referred 

to the parole board, they were more likely to be returned to custody. Similarly, registered 

sex offenders were less likely than others to be returned to prison through court, but they 

were treated more severely by the board. One explanation for these findings is that the 

criminal violation cases of serious and violent offenders, as well as sex offender 

registrants, may have been unappealing to court decision-makers because they tended to 

lack compelling evidence. However, court decision-makers may have also referred these 

cases because they felt that the board, using a lower standard of evidence, could act 

quickly and decisively to re-incarcerate parolees who were perceived as particularly 

threatening to public safety. The board sanctioned these types of parolees especially 

severely in low level (Type I) criminal violation cases—the type allowing for the most 

discretion. It appears that low-level criminal activity, much of which is detected through 

parolee drug testing, was a crucial mechanism by which the parole board re-incarcerated 

“high profile” parole violators. Note that the criminal courts could not legally impose 

very harsh sanctions for these low level crimes, and so they seemed to opt, through case 

referral, for the greater certainty of punishment that the board was able to provide. 

Demographic characteristics were also somewhat predictive of case outcomes. Parolee 

age affected criminal court decisions, but not board decisions. Courts were inclined to 

prosecute the criminal violation cases of the youngest parolees (ages 18-30). Black 

parolees were more likely to have their cases referred to the Board—the more 

discretionary venue—and when their cases were heard by the Board, they were more 

likely to be incarcerated for criminal violations. Asian and Hispanic parolees were the 

most likely to be successfully prosecuted in criminal court, and Hispanics were further 

penalized in front of the board, where they were among the most likely to be returned to 

custody in criminal violation cases. White parolees, who had the lowest likelihood of 

court conviction, also had the lowest likelihood of return through the Board for criminal 

violation cases (although they were among the most likely to be returned when they 

absconded). These findings suggest that there may be observable or unobservable traits 

associated with parolees of different demographic groups that affect their case outcomes. 

Organizational factors 

Over and above case- and parolee-specific characteristics, organizational factors also 

affected revocation decisions by the court and the parole board. Los Angeles County 

(Region 3) appeared distinct in its treatment of parole violators. Criminal violations in 

Los Angeles were more likely to result in reincarceration through the court. Board 

decisions were also uniquely patterned in Los Angeles. Technical parole violators were 

20


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
more likely to be returned to custody by the board in this region, while absconders were 

less likely to be returned by the board. These findings could have been due to many 

factors: differences in organizational culture across parole regions, unmeasured variation 

in local parolee populations that affected sanctioning decisions (e.g., gang affiliation, 

addiction and employability), or the effectiveness of policing practices in different 

regions. 

Practical constraints on decision-making also appeared to play a role in violation case 

outcomes. A key practical constraint was available custodial space. We found that when 

available space in prison reception centers decreased, for example, the parole board was 

more likely to continue cases on parole, as opposed to returning parolees to prison. 

Moreover, in courts, workload pressures (measured as the ratio of felony cases to district 

attorneys in each county) were linked to an increased likelihood of case referral to the 

parole board. As felony court caseloads increased, courts were inclined to refer more 

criminal parole violation cases to the parole board. 

Community Factors 

Our statistical models showed that, net of all other measured factors, some characteristics 

of parolees’ communities were related to the treatment of parole violations in court and 

before the parole board. For example, more “punitive” counties—as measured by 

political party affiliation and electoral ballot voting outcomes—were more likely to 

return criminal parole violators through the court, and in violation cases heard by the 

board, these counties were more likely to return parolees to prison, regardless of whether 

the case involved a criminal violation, absconding, or other technical violations. 

Community characteristics can also serve as cues to decision-makers that reflect 

something about individual parolees themselves. The extent of “racial threat” in a 

community is illustrative of this point. Census tracts with higher proportions of black 

residents, and those with higher black unemployment rates, may be perceived as 

particularly unstable or crime-ridden, and parolees that live in these communities may be 

penalized by decision-makers because they come from, and are therefore representative 

of, these disadvantaged environments. In our models, parolees who came from 

communities that had more black residents, and higher black unemployment rates, were 

more likely to be returned by the court with a new term, as opposed to being referred to 

the parole board. When their cases were heard by the parole board, these parolees were 

generally more likely to be returned to prison, especially for criminal violations. 

However, while community characteristics can have a stigmatizing effect on case 

outcomes, they can also have the opposite effect. For example, census tracts with more 

mental health and substance abuse services in close proximity were associated with more 

lenient outcomes among criminal violation cases and technical violation cases (not 

involving absconding) decided by the parole board. This may have been due to the fact 

that decision-makers had more treatment options in these communities, and therefore 

more opportunities to keep parole violators out of prison, or that parolees from servicerich communities somehow appeared less threatening than parolees from communities 

that lack services. 

21


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
A central implication of our analyses of revocations is that the response of criminal 

justice institutions does not totally derive from, and is not necessarily proportionate to, 

the extent of parolees’ criminal behavior, as is often assumed by policymakers, 

government officials, and the public. While case characteristics matter in terms of court 

and board outcomes, so too do the characteristics of the individual, the organizations 

handling that individual’s case, and the community that the person comes from. 

POLICY & RESEARCH IMPLICATIONS 

Our findings suggest a number of policy and research implications, the most important of 

which are: 

1.	 Concentrate supervision and services on the first six months. Parole should 

front-load services and surveillance to focus on a parolee’s first six months after 

release, when the risk of recidivism is the highest. 

2. Expand use of early and earned discharge. Parolees are most at risk of all kinds 

of violations during the first six months on parole. Parolees that make it to the 

sixth month without violation pose significantly lower risks than parolees who do 

not. The duration of the imposed parole term should be closely linked to an 

offender’s risk level or accomplishment of individual benchmarks. Low-risk 

offenders might not be assigned parole supervision at all, or those who adjust well 

to parole could be released after six months of supervision. Moderate-risk 

offenders might be assigned a year or two of parole, whereas high-risk offenders 

might serve two years or more, and very high-risk offenders might be assigned 

lifetime parole. 

3.	 Align parolee risk and supervision levels. Parole services and surveillance 

should be primarily risk-based rather than offense-based. The CDCR needs to 

assign parole caseloads and supervision levels so that offenders are “matched” to 

types of surveillance and services that are most appropriate for them. Resources 

should be more heavily focused on higher-risk parolees, and very intensive (and 

expensive) programs should be reserved for those whose risk and need profiles 

suggest they will likely benefit from program participation. 

4.	 Employ a parole violation matrix. The parole division and the parole board 

should adopt policy-driven approaches to parole violations using a decisionmaking matrix and graduated community-based sanctions. This tool would allow 

parole officials to respond consistently to parole violations, using a welldeveloped range of intermediate sanctions. The response should reflect the 

original risk level of the parolee coupled with a proportionate response to the 

seriousness of the violation. Every major study on California’s prison system 

published since the 1980s has recommended the use of such a tool, but it has 

never been implemented, even though such instruments are used in over 20 other 

states. California is currently developing such an instrument and plans to pilot test 

it in fall 2008. 

22


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
5.	 Expand intermediate sanctions options. The CDCR should implement 

additional intermediate sanction programs, particularly for drug-involved 

parolees. Current program offerings are woefully inadequate to appropriately deal 

with the wide range of parole violations. The CDCR cannot do this alone, as the 

most effective reentry programs and intermediate sanctions require community 

engagement and collaboration. The expansion of evidence-based intermediate 

sanctions should both reduce recidivism and save expensive prison beds for the 

most violent criminals. 

6.	 Encourage criminal prosecution. Parolees who commit new crimes should be 

prosecuted in criminal courts whenever possible. California’s “back-end 

sentencing” system allows some very serious criminals to evade the more severe 

criminal penalties that would have been imposed had their cases been criminally 

prosecuted as opposed to handled by the parole board, where the maximum term 

imposed was only 12 months. Further, we found some evidence that stresses on 

the capacity of California’s justice system—as measured by jail and prison 

overcrowding and district attorney caseloads—resulted in greater likelihoods that 

the BPH would handle criminal violation cases. While case and offender 

characteristics are appropriate criteria for board referral decisions, system 

capacity should not affect these decisions. 

7.	 Track extra-legal factors affecting revocation. The CDCR should develop 

better evaluation methods to reduce the influence of extra-legal factors— 

particularly parolee race—on violation case outcomes. We found that black parole 

violators were more likely to experience referral to the parole board, and more 

likely to be returned by the board for certain types of violations. We also found 

effects related to age, gender and mental health status. The state must explore the 

causes and consequences of the influences of demographic and personal 

characteristics on sanctioning decisions. 

8.	 Expand substance abuse and mental health programs. Substance abuse-related 

violations and the violations of parolees with mental health problems make up a 

large share of all violations. These populations are not well-served by short 

returns to prison, where there are few services and sanctions are of insufficient 

duration to improve their outcomes. The CDCR should expand intermediate 

sanctions specifically for these populations, so as to allow for community-based 

and in-custody treatment in a non-prison environment for sufficient time periods 

to address these criminogenic needs. 

This study is just the first step towards a better understanding of California’s parole 

violation and revocation process. The data we collected were primarily administrative; 

other types of data, such as systematic interviews with parolees about their parole 

experiences, would highlight issues of discretion and sanctioning that are difficult to 

capture through quantitative analyses alone. Future research on parole outcomes could 

also benefit from improvements to data quality. Some of our variables were underspecified (e.g., the community variables, parole agent characteristics). Other factors that 

may be related to parole outcomes (e.g., addiction, employability of parolees) were 

23


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
beyond the scope of our data collection effort. Data on the extent and type of programs 

parolees participated in could also expand on what we have done here. Given that many 

parolees are violated for program non-compliance, and that others may benefit from work 

and educational programming, it would be useful to know the degree to which parolees 

are engaged in assigned programming. Future studies might also address parole policies 

more specifically. Our research has generated many insights that can inform certain 

policies, such as early discharge from parole and the timing of service delivery. 

It is also important to note that our data is from 2003-2004 and California’s parole system 

is currently undergoing the most significant changes in its procedures since the late 

1970s. Currently, California is implementing a new evidence-based parole violation 

decision-making instrument (PVDMI) to help agents and the parole board assess risk and 

needs in determining sanctions. The PVDMI was specifically designed for California 

parolees using another new instrument, the California Static Risk Assessment (CSRA). 

The CSRA uses the offender’s past criminal history and characteristics such as age and 

gender to predict the likelihood they will re-offend. 

The CSRA, combined with the severity ranking of all parole violations, has been 

incorporated into the PVDMI, which results in a score that designates the appropriate 

violation response level. The response levels range from least intensive (i.e. community 

programs etc.) to most intensive responses (in-custody drug treatment or return to prison 

recommendations). The PVDMI is designed to focus California’s prison resources on 

higher-risk parolees while targeting less serious parole violators for community-based 

alternatives that address the root sources of their problems. DAPO is acquiring or 

redirecting treatment resources to plan for the expanded use of community based 

sanctions in responding to parole violations in California. The PVDMI was developed 

with the full participation and support of BPH and it is anticipated that it will impact their 

decision-making as well. Implementation of the PVDMI will be evaluated by the UCI 

Center for Evidence-Based Corrections.

8 

As these and other parole reforms move forward, and parole data systems and knowledge 

about parole outcomes improve, it should be easier to implement studies that focus 

specifically on the potential effectiveness of various policy choices. We hope that this 

piece of research will provide guidance for future research efforts, as well as the 

important discussion that will be taking place over the next several years about parole in 

California and the United States. 

8 The details of the PVDMI and CSRA can be found at http://www.cdcr.ca.gov/News/2008_Press_Releases/Oct_3.html

(accessed October 6, 2008).

24


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER I. INTRODUCTION AND OVERVIEW OF STUDY ISSUES


One of America’s most vexing challenges is the management of its prison system. More 

than 2.3 million people are now incarcerated in the U.S.—more than one out of every 100 

adult Americans. Incarceration rates are even higher for some groups: one out of nine 

black men, ages 20 to 34, are serving time, as are one in 36 Hispanic men. U.S. prison 

populations have experienced 15 years of steady growth and are now at all all-time high, 

outstripping that of any other industrialized country, both numerically and as a 

percentage of the overall population.

9 

As prison populations have expanded, states’ corrections costs have risen substantially. In 

2007, according to the National Association of State Budget Officers, states spent $44 

billion in tax dollars on corrections. That is up from $10.6 billion in 1987, a 127 percent 

increase when adjusted for inflation. States are on track to spend an additional $25 billion 

by 2011. On average, states spend almost 7 percent of their budgets on corrections, 

trailing only health care, education, and transportation.

10 

As the U.S. economy slows and state budgets tighten, correctional spending is crowding 

out investments for other valuable programs, like health care and education. For example, 

a study by the Pew Foundation found that over the last 20 years, inflation-adjusted 

general fund spending on corrections rose 127 percent while higher education 

expenditures rose just 21 percent.

11 More and more, policymakers are questioning 

whether states are getting their money’s worth out of prisons and whether imprisonment 

is the most effective means of achieving public safety, especially when it diverts 

increasingly scarce funds away from other social services, some of which have been 

shown to prevent crime in the first place. 

Despite the fact that we are spending increasingly more on prisons each year, recidivism 

rates remain virtually unchanged, with about half of all released inmates returning to 

prison or jail within three years.

12 Most prison systems are severely overcrowded, and the 

communities to which prisoners return experience a number of negative consequences as 

well. Clear (2007) argues that mass incarceration fractures families, threatens the 

economic infrastructure of already struggling neighborhoods, and leads to increased 

9 The Pew Center on the States, “One in 100: Behind Bars in America in 2008”


(http://www.pewcenteronthestates.org/report_detail.aspx?id=33428) The Pew study combines prison and


jail populations. In 2007, the U.S. prison population was 1,596,127.
 10 “U.S. Imprisons One in 100 Adult, Report Finds,” Adam Liptak, The New York Times, February 29,


2008:A2.
 11 Pew Charitable Trust. (2007). Public Safety, Public Spending: Forecasting America's Prison Population


2007-2011. Chicago, Ill.
 12 Langan, Patrick, and David Levin (2002). Recidivism of Prisoners Released in 1994, Washington, D.C.:


Bureau of Justice Statistics.


25


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
social stresses, especially for children.

13 Incarceration, in other words, may have exactly 

the opposite of its intended effect: it destabilizes the community, thus further reducing 

public safety. 

The debate about the costs and benefits of imprisonment is taking place all across 

America, but the stakes are highest in California. California’s 173,312 prisoners 

constitute the largest prison population of any state. One in seven state prisoners in the 

United States is incarcerated in California, and between 1980 and 2007, California’s 

prison population increased over sevenfold, compared with a fourfold increase nationally. 

And despite a 2003 vow by California Governor Arnold Schwarzenegger to reduce the 

prison population, it continued to grow and recent projections predict a prison population 

of 191,000 in the next five years.

14 

California’s prison expenditures are also among the highest in the nation—per inmate, 

per staff, and as a share of the overall state budget. The average annual cost of housing a 

California prisoner in 2006-7 was $43,287, 1.6 times higher than the national average of 

about $26,000.

15 At the beginning of the prison building boom in the early 1980s, adult 

and youth corrections accounted for four percent of California’s General Fund 

expenditures at $1 billion per year. Today, California’s budget for state corrections is 

now over $10 billion a year—and growing at a rate of seven percent annually, the fastest 

growing segment of the state’s criminal justice expenditures. Corrections now accounts 

for approximately ten percent of total California state spending—nearly the same amount 

the state spends on higher education.

16 Even after adjusting for inflation, general fund 

expenditures to support California Department of Corrections and Rehabilitation (CDCR) 

operations increased 50 percent between 2001-2 and 2008-9. 

Yet despite these vast expenditures, California prisons remain dangerously overcrowded. 

More than 15,000 inmates—approximately ten percent of the total prison population— 

are housed in gyms, dayrooms, holding cells, and even hallways. This level of crowding 

also appears to contribute to California’s anomalously high rate of prison violence. 

California prisons have nearly twice as many assaults as the Texas prison system, and 

both states have roughly the same number of prisoners.

17 During a recent three-year 

period, California’s Legislative Analyst’s Office (LAO) reported that 1,700 staff health 

13 Clear, Todd R. (2007) Imprisoning Communities: How Mass Incarceration Makes Disadvantaged 

Neighborhoods Worse, Oxford University Press, NY. 14 It is important to note, however, that California’s inmate population declined by almost 1,900 inmates. 

http://www.lao.ca.gov/analysis_2008/crim_justice/cj_anl08009.aspx#zzee_link_1_1202846137 It is 

unclear whether this downward population trend will continue but it may signal a historical shift. California 

Department of Corrections and Rehabilitation. (2008). Adult Population Projections 2008-2013. 

Sacramento, CA. Available at 

http://www.cdcr.ca.gov/Reports_Research/Offender_Information_Services_Branch/Population_Reports.as


p, accessed May 23, 2008.
 15 See Legislative Analyst’s Office (2007), California’s Criminal Justice System: A Primer, Sacramento:


CA; and also Legislative Analyst’s Office, Analysis of the 2008-09 Budget Bill, Judicial and Criminal


Justice, at http://www.lao.ca.gov/laoapp/Analysis.aspx?2008&cap=4&toc=1, accessed May 2008.
 16 Sterngold, James (2007) “Prison Budget to Trump Colleges,” San Francisco Chronicle May 21:A1.
 17 Legislative Analyst’s Office, Analysis of the 2005-06 Budget Bill, Judiciary and Criminal Justice, 2005.


http://www.lao.ca.govanalsis.aspx?year=2005&chap=4&toc=1, accessed May 2008.


26


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
and workers’ compensation claims were filed for injuries resulting from inmate violence. 

This is partially attributable to prison overcrowding, but it is also the result of the state’s 

violent prison gang culture and the fact that so many inmates sit idle, without 

participating in any prison programming. 

In October 2006, Governor Schwarzenegger declared a state of emergency, allowing him 

to transfer inmates to prisons in other states in order to help relieve some of the pressures 

of overcrowding. In May 2007, the Governor signed into law historic prison reform 

legislation, Assembly Bill 900, or the Public Safety and Offender Rehabilitation Services 

Act of 2007. AB 900 authorized $7.9 billion in spending for the creation of 53,000 more 

prison and jail beds. But the crowding has not diminished, and a federal court is now 

threatening to take over the entire prison system in response to claims that overcrowded 

conditions violate the constitutional rights of prisoners. As California’s economy slides 

into recession, state leaders are asking the critical question: Are rising prison costs really 

worth the public safety benefits? 

No one disputes the fact that California’s prison system is in deep crisis. The state must 

either continue to divert public resources away from higher education and other public 

programs, raise taxes to provide more funds, or take a hard look at who is currently in 

prison and decide whether some of them could be punished in less expensive communitybased programs. This latter option requires a consideration of two aspects of the criminal 

justice system that California politicians and policymakers have been reluctant to 

approach: the sentencing system, which determines who goes to prison and for how long, 

and the parole revocation system, which determines what happens to parolees when they 

violate parole. In other words, does everyone now being committed to a California prison 

really need to be there? Are these prisoners’ crimes so serious that the public would not 

allow such persons to be placed in the community (i.e., the principles of retribution or 

“just deserts”), or is their risk of recidivism so high that they cannot be allowed to return 

to the community for fear of the crimes they are predicted to commit (i.e., the goal of 

incapacitation)? These are the central questions that must be answered before California 

policymakers can decide whether they need to spend more money on expanding prison 

capacity. If the prison population is sufficiently serious, then expanding prison space 

might be warranted. But if a significant portion of prison population is not so steeped in 

criminality that they cannot be released, then alternative sanctions might be pursued. 

THE IMPORTANCE OF PAROLE VIOLATIONS AND REVOCATIONS 

Central to California’s entire debate over its prison system is the topic of parole and 

parole revocation. In terms of the ratio of prisoners to resident population, or the ratio of 

incarceration rates to crime rates, California is roughly at or just above the average for the 

50 states.

18 The most striking anomaly in the California statistics is the recidivism rate. 

Traditionally, a recidivism rate is based on a three-year follow-up period. The three most 

common recidivism measures are rearrest, reconviction, or return to prison (for either a 

new court conviction or a parole violation). California’s recidivism rate as measured by 

18 Petersilia, Joan (2006), Understanding California Corrections, California Policy Research Center, 

University of California. Available at http://ucicorrections.seweb.uci.edu/ 

27


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
the “return to prison rate” is 66 percent, compared to a 40 percent national average.

19 At 

the end of three years, 66 percent of all California parolees had been returned to a 

California prison, 27 percent for a new criminal conviction and 39 percent for a technical 

or administrative violation, which can result from new crimes or violations of the 

conditions of parole. On any given day, six out of ten admissions to California prisons are 

returning parolees. 

Part of the explanation for California’s anomalously high parole return rate is its unique 

sentencing and parole system. California, for the most part, has a mandatory parole 

release system. California moved from an indeterminate to a determinate sentencing 

system in the late 1970s, and as a result, most offenders are released after they have 

served their original court-imposed sentence, less any accumulated good time credit. For 

example, first-degree burglary is punishable by imprisonment for two, four, or six years; 

the particular sentence depends on the decision of the judge. Once prisoners have served 

the prison term specified by the sentencing judge (minus good time), they are 

automatically and mandatorily released. California’s Determinate Sentencing Law allows 

offenders to earn, with some exceptions, day-for-day “good time” rate (a 50 percent 

reduction). Only offenders sent to prison on a life-term (19 percent of prisoners in 2007) 

are subject to discretionary release, where the Board of Parole Hearings (BPH) and the 

Governor determine fitness for prison release. For about 80 percent of California 

prisoners, there is no appearance before a parole board to determine whether they are fit 

to return to the community. 

Once released from a California prison, virtually all prisoners are placed on formal parole 

supervision, usually for three years. California is virtually alone in this practice of placing 

all released prisoners on parole. Most other states reserve parole for only their most 

serious offenders. New York, Florida, and Texas, for example, only place about one-third 

of released prisoners onto formal parole supervision.

20 

California’s growing prison population, combined with its universal parole practices and 

lengthy parole terms, has resulted in California supervising far more parolees than any 

other state. The Bureau of Justice Statistics reports that in 2007, California supervised 

about 120,000 parolees on any given day, accounting for 15 percent of all parolees in the 

country.

21 California’s parole population also continues to outpace the growth in the rest 

of the nation: in 2006, California experienced a 6.1 percent increase in its parole 

population, compared with the U.S. state average increase of 2.2 percent.

22 

California’s parole population is now so large and agents are so overburdened that 

parolees who represent a serious public safety threat are not watched closely and those 

who wish to go straight cannot get the help they need. About 80 percent of all California 

parolees have fewer than two 15-minute face-to-face meetings with a parole agent each 

month, and nearly all of them take place in the parole agent’s office. Two-thirds of all 

19 Petersilia, note 10 above.
 20 Petersilia, note 10.
 21 Glaze, L., and T. Bonczar (2007), Probation and Parole in the United States, 2006, Bureau of Justice


Statistics, Washington DC, NCJ 220218.
 22 Glaze and Bonczar, note 11.


28


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
California parolees are thought to have substance abuse problems and nearly all of them 

are required to be drug tested. Yet, few of them will participate in appropriate treatment 

while in prison or on parole. California’s recent Expert Panel on Adult Offender 

Recidivism found that fully fifty percent of all exiting California prisoners did not 

participate in any rehabilitation or work program, nor did they have a work assignment, 

during their entire prison stay. They didn’t get the help they needed on parole either: 56 

percent of parolees didn’t participate in any formal program while under parole 

supervision.

23 

Clearly, this low level of supervision and service provision does not prevent crime. As 

noted above, two-thirds of all California parolees return at least once to a California 

prison within three years. In Texas, the state most comparable in the size of its prison 

population to California, the “return to prison” rate is about 20 percent.

24 Due to their 

high failure rate, parolees account for the bulk of California prison admissions: In 2006, 

nearly two-thirds (64 percent) of all persons admitted to California prisons were parole 

violators. Parole revocations have been rising nationally over the last 20 years, but 

California’s have increased more so. Nationally, over the last 20 years, the number of 

parole revocations has increased about six-fold. In California, the number of parole 

revocations has increased 30-fold. 

Part of California’s high parole revocation rate is explained by its unique decisionmaking process. The decision to send a parole violator back to prison for an additional 

sentence is not often made in California by a judge, but rather by a politically appointed 

deputy commissioner at the Board of Parole Hearings. Criminologists have coined the 

term “back-end sentencing” to describe how the parole revocation process centers on 

parole board practices.

25 Not only are back-end sentences determined by correctional 

officials instead of judges, the standard of evidence used is much lower than is required 

in a court of law. Parole board officials use the more lenient legal standard of 

“preponderance of the evidence,” as opposed to the “beyond a reasonable doubt” 

standard that is required in criminal court convictions. This more lenient standard is 

deemed appropriate because a California prisoner still remains in the legal custody of the 

CDCR while on parole. Parolees involved in the board revocation process do not have 

their cases heard in front of a jury and they have no right to appeal board decisions. 

(However, they do have legal representation.) Parole in California is not a reward for 

good behavior, as it might be in an indeterminate sentencing state, but rather an extension 

of a felon’s sentence and a period of extended surveillance after prison. As such, if the 

parolee does not abide by the imposed parole conditions, the State has the legal right to 

revoke their parole term and return them to prison. 

23 California Expert Panel on Adult Offender Recidivism Reduction Programming. (2007). A Roadmap for


Effective Offender Programming in California: Report to the California State Legislature. Sacramento,


CA: California Department of Corrections and Rehabilitation.
 24 Governor Schwarzenegger’s Rehabilitation Strike Team Final Report (2007) Meeting the Challenges of


Rehabilitation in California’s Prison and Parole System, , Sacramento, CA. Available at


http://www.cdcr.ca.gov/News/Gov_Rehab__Strike_Team_Release_Rpt.html, accessed May 15, 2008.
 25 Travis, Jeremy (2005). But They All Come Back: Facing the Challenges of Prisoner Reentry, The Urban


Institute, Washington, DC.


29


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
California’s parole revocation process is also unique in another way. The maximum term 

for a parole violation in California is 12 months in prison. If a parolee is sentenced to that 

maximum term, there is usually a day-for-day credit for time served in prison or in jail 

awaiting case disposition, assuming no prison rule infractions. The upshot is that the 

parole violator who is not convicted of a new crime by a criminal court—totaling nearly 

70,000 prison commitments in 2006—will only spend, on average, slightly more than 

four months in custody.

26 

Due to the complexities of the inmate reception process and the number of inmates 

moving through the State’s eleven reception centers, prisoners spend an average of 90 

days (sometimes much longer) in one of these reception centers before being transferred 

to their assigned prison. By the time the parole violator is transported from the local 

county to the State prison reception center, gets processed and then recommended for a 

specific prison placement, that parole violator may have served the required prison 

sentence and simply be paroled (again) right out of the reception center. And of course, 

not everyone gets the maximum 12-month sentence. Data analyzed by California’s 

Rehabilitation Strike Team found that of all parolees returned to a prison in 2004, 20 

percent—one in five parole violators—served less than one month in a California prison 

(they may have served additional time in local jail awaiting disposition). Fully 77 percent 

of California parole violators served less than five months in prison. Since the reception 

center process takes an average of 90 days, tens of thousands of parole violators 

discharged directly from CDCR reception centers.

27 

The result is that more than 45,000 parole violation cases annually go through the 

arduous parole revocation process—which includes a formal revocation hearing with a 

parole commissioner, court reporter, parole officer, attorney representing the parolee, and 

often law enforcement and witnesses. If the parole violation charges are sustained at this 

hearing (and 80-85 percent of the time they are), the parolee is then transported by bus to 

a reception center, where staff begin the process of assessing the offender (for physical, 

mental, gang-related, and other sensitive needs) and recommending that the inmate be 

“endorsed” to serve time in a specific prison. At some point during the routine processing 

of parole violators, many prisoners will be released, having served the required sentence 

before the reception process is complete. They will parole right out of the reception 

center, and the State will again pay for their transportation back to their county of 

commitment. This system of “catch and release” makes little sense from the standpoints 

of deterrence, incapacitation, treatment, or economic sensibility. Parolees quickly learn 

that being revoked from parole doesn’t carry serious consequences, and the State will 

have paid thousands of dollars to classify, assess, test, and endorse inmates to prison who 

will not be there long enough to serve a prison term. 

Rapid “churning” into and out of prison also wastes the resources of the police, the parole 

board, and parole officers, who have to reprocess the same individuals over and over 

again. Churning disrupts continuity of treatment, making it difficult or pointless for 

inmates, who know they will be back on the street in a few months, to begin participating 

26 California Expert Panel, note 15.
 27 Governor Schwarzenegger’s Rehabilitation Strike Team Report, note 16.


30


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
in sorely needed educational, vocational, or substance-abuse programs. It also disrupts 

community-based treatment since parolees who are enrolled in community treatment 

programs are constantly having that treatment disrupted for what, in the treatment 

providers’ views, are predictable and minor rule violations (e.g., testing positive for drug 

use). Churning also encourages the spread of prison gang culture into the communities 

where inmates are discharged, while undercutting the deterrent effect of serving prison 

time. 

The fiscal consequences of handling parole violators this way are also staggering. 

Processing the prison admissions of parole violators takes as much time and money as 

processing admissions of new convictions—recently estimated to be $900 million per 

year in California

28

—for offenders who mostly will be in prison only for a few months. 

And of course, given California’s overcrowding crisis, there is the high opportunity cost 

of occupying a limited number of prison beds that, in some cases, could be used for 

offenders who pose a greater risk to the public safety. 

In sum, California’s “catch and release” system of handling parole violators makes little 

sense from a deterrence, incapacitation, rehabilitation, or economic standpoint. And 

because the parole system contributes so heavily to prison crowding, improved parole 

practices could have an immediate and lasting impact on the need for more prison beds. 

Unfortunately, scientific knowledge about California’s parole system is so scant that, 

despite the fact more than a dozen reports have urged an overhaul in California’s parole 

revocation procedures, exactly what needs to be done is not clear. 

In September 2005, the National Institute of Justice (NIJ) funded the authors to undertake 

a three-year comprehensive study of the causes and consequences of parole violations 

and revocations in California. The research project was supported fully by CDCR, the 

umbrella agency that oversees all of California state corrections. Their cooperation was 

essential to access and understand the extensive data that our project required. 

RESEARCH QUESTIONS & DATA 

To better understand the complexities of the parole violation process and the 

characteristics of parolees who are returned to prison, we need to unpack the “black box” 

of the parole violation and revocation process. We need to study not only parolees’ 

characteristics but also the characteristics of the supervising agency, parole agents, and 

the communities to which parolees return. We need to identify the key decision points 

that ultimately lead to parole revocation and prison returns, and also how characteristics 

of the parole agent, caseload type, and variations in community characteristics impact the 

processes of violation and revocation. 

We must also analyze data that allows us to better understand the critical role of the 

Board of Parole Hearings (BPH), which has the ultimate responsibility for deciding 

which parole violators are returned to prison and which are allowed to remain in the 

28 Little Hoover Commission. (2007). Solving California’s Corrections Crisis: Time is Running Out. 

Sacramento: CA, and Little Hoover Commission (2003), Back to the Community: Safe & Sound Parole 

Policies, Sacramento: CA, both reports available at http://www.lhc.ca.gov/lhcdir/crime.html. 

31


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
community. In the mid-1990s, California adopted a “zero tolerance” policy for “serious” 

and “violent” parolees (as defined in the Penal Code), such that parole agents are required 

to report every offender originally convicted of these crimes who violates any condition 

of parole to the BPH for disposition. The BPH is a politically appointed body and has a 

history, especially in recent years, of returning to prison most parolees coming before it. 

The BPH may be the most important gatekeeper of using prison for the sanctioning of 

parole violations, and yet their role and impact has gone virtually unnoticed and 

unstudied. 

We designed this project to be the largest, most comprehensive, and most scientifically 

rigorous study of parole violations and revocations ever undertaken. With the full 

cooperation of CDCR, we assembled an extraordinarily large and complex database that 

tracks every adult on parole in California at any point during the calendar years 2003 and 

2004. The resulting study sample consisted of 254,468 unique individuals. These parolees 

were responsible for 151,750 parole violations that made it to the court or board hearing 

level (thousands more were terminated at the parole unit level) over the two study years. 

These parole violation and revocation incidents were the central focus of our study. In 

addition to recording the details of each parolees’ behavior on a weekly basis during the 

two year study period, we also merged data about each parolee reflecting their personal 

characteristics and criminal history, the nature and type of supervision to which they were 

subjected, the characteristics of agents who supervised them, and the communities to 

which they returned. 

The combined database allowed us to answer these and other critical questions: 

•	 What are the personal and criminal history characteristics of California 

parolees? How are they supervised? What types of communities do they come 

from and return to? 

•	 How many parolees violate parole, and how do individual background, current 

supervision, and community environment affect the likelihood an individual will 

violate parole? 

•	 What factors affect the occurrence and timing of parole violations? Do different 

factors predict different types of violations (i.e., criminal, technical, absconding)? 

•	 Do different factors predict more and less serious criminal violations? 

•	 What factors shape decisions to prosecute criminal violations in criminal courts, 

as opposed to referring them to the parole board (BPH)? 

•	 What factors are related to the likelihood an offender will be returned to prison, 

holding constant the severity of their current violations and their criminal 

history? 

•	 Do community characteristics and parole region influence the decision to return 

an individual to prison? 

32


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
These and other questions are answered in this report. Our hope is that this empirical data 

will permit California policymakers to devise more sound parole supervision and 

revocation policies, which better balance public safety and public resources. Importantly, 

such research should help advise policymakers on the “seriousness” of parole violators 

being returned to California prisons, which in turn can greatly influence the prison 

capacity discussion. 

ORGANIZATION OF THIS REPORT 

This report is organized in the following manner. Chapter II describes the study’s 

conceptual framework and the details of our data collection. Chapter III briefly describes 

the major aspects of California’s sentencing and parole system that we believe impact 

parole revocations and prison returns. Chapter IV begins the presentation of our study’s 

findings, describing the demographic and crime profiles of our sample, as well as the 

parole supervision regimes to which they are subject and the characteristics of the 

communities to which they return. Chapters V and VI present the study’s major 

multivariate analyses and findings. Chapter V answers the question, “what predicts parole 

violations?” and Chapter VI answers the question, “what predicts parole revocations and 

return to prison?” Finally, Chapter VII presents a summary of our major findings, along 

with relevant policy implications. 

33


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER II. CONCEPTUAL FRAMEWORK AND DATA


COLLECTION


Our study’s core question is “what parolee characteristics, parole agency activities, and 

community conditions affect parolee recidivism?” Of course we recognize that not all 

violation behavior comes to the attention of parole agents or law enforcement and hence 

is not recorded in any fashion. The actual rates of technical violations and new criminal 

behavior are unknown and have only been estimated using self-reports. Our current study 

design does not incorporate parolee self-reports although future phases of this project 

could do so. 

The aspect of our project that is perhaps most unique is that we view the parole violation 

process as reflecting not only the parolee’s behavior, but the system’s responses and 

communities’ influences on that behavior. Our overarching question thus necessitates a 

set of separate investigations into parole violations, which are largely (but not entirely) 

behavioral events, and revocations, which reflect system responses to that behavior. 

Figure 2.1 illustrates our notions of how three clusters of factors, reflecting characteristics 

of the parolee, the agency and the community interact to produce variations in parole 

outcomes. 

At a general level, parolees face three major kinds of recorded recidivism events while on 

parole. First, they can violate the terms of their parole agreement. Some stipulations are 

standardized such that all parolees must abide by them. For example, a parolee must 

report changes in their residence, they must get approval from their parole agent to travel, 

they may not have any access to weapons, and, of course, they must not commit a new 

crime. In addition, a parolee typically has a set of special conditions that relate to the 

crime for which they were convicted. These conditions are designed by their parole agent 

and represent the individualized portion of their parole agreement. Violation of any of 

these conditions may result in revocation, but not always. Parole agents and supervisors 

have considerable discretion in determining how to handle less serious violations and 

may not refer an individual case to the parole board if the violations are not sufficiently 

numerous or serious. 

34


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Parolee Characteristics 

Parolee Outcomes 

Community Environment Agency Activities 

Figure 2.1: Trinity of Factors that Influence Parole Outcomes 

A second type of recidivism event is an arrest for a new crime—itself a form of parole 

violation, as mentioned above. In this circumstance, parole is not necessarily revoked 

automatically, as one might assume. When a parolee is arrested, the county criminal court 

will first evaluate the case. If the prosecutor successfully convicts the parolee for the new 

crime or crimes, the parolee is given a new prison term of any length appropriate to the 

crime(s) and the parolee’s parole term is “reset.”29 If the prosecutor declines to prosecute, 

or cannot obtain a conviction, the case is typically taken up by the parole board. Here, the 

process is the same as for other violations, although sometimes the parolee will be 

returned to prison even though the new charges are dismissed. Sometimes a parolee who 

has committed a new crime will be allowed to continue on parole while undergoing 

criminal proceedings for new crimes; in such cases, the parolee is typically held in 

custody, making return to prison less necessary to protect public safety. 

The third major recidivism event is parole revocation, which is the process of sanctioning 

the criminal and noncriminal parole violations described above, typically through a brief 

return to prison. If a parole agent and his or her supervisor feel the violation is serious 

and that the parolee poses a threat to public safety, they can recommend to the state 

parole board (BPH) that the parolee be returned to prison. The BPH, which in California 

is represented in revocation hearings by a single commissioner, typically follows the 

recommendation of the parole unit, and then a commissioner uses his or her discretion to 

29 That is, when the parolee is released from prison after serving a new term, the parole time clock will start 

over again. The parolee will get no credit for previous periods of parole. 

35


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
set the length of time for the parolee’s return to prison. At the parole revocation hearing, 

the BPH commissioner may impose a maximum sentence of 12 months in prison. 

Violation, arrest, and revocation represent key turning points in an individual’s career on 

parole and yet little is known about the factors that affect each kind of event and how the 

events might be interconnected. Policy makers want to know what types of offenders are 

most likely to violate their parole agreements, get arrested, and have their parole revoked. 

They also want to know which types of offenders are more likely to survive six months or 

a year on parole without a violation—those who are thus less in need of costly 

supervision. Such information would be useful for parole agents who currently design 

supervision programs based on such things as past experiences, established unit practices, 

unscientific folk wisdom about types of offenders, and even biases regarding certain 

types of offenders. This problem leads to idiosyncratic applications of parole supervision 

and sanctions. Without data on aggregate patterns of parolee behavior, decision-makers 

may apply more supervision than necessary to many cases, thereby misallocating 

resources that that might be better deployed on truly high risk parolees. 

Moreover, policymakers also want to know what criminal history and personal 

background factors affect the risk of violations, especially the most serious criminal 

offenses. Such knowledge will assist parole agents in better targeting supervision to the 

most risk-prone parolees. Finally, policymakers want to know if the discretion used by 

parole officials in the system is being used appropriately (i.e., in accordance with state 

laws and regulations, professional norms, or unit-level protocols). Are there instances 

where parolees who do not pose a threat to public safety and have not committed a new 

criminal offense (i.e., parolees whose violations are primarily “technical” violations of 

the terms of their parole agreement) are treated too harshly? Related, does the system 

produce a reasonable degree of standardization, such that similarly situated cases receive 

similar treatment? If variability exists in the treatment of similarly situated cases, which 

set of factors contributes the greatest amount to that variability? 

These policy-relevant questions are central to the analyses presented in this report, and 

guide our interpretations of the findings. 

DATA COLLECTION 

Our research required us to assemble an extensive database that included information 

about California parolees and their behavior while on parole, details about the agency and 

its agents, as well the communities to which parolees are released. We also required a 

study population that was large enough for us to examine variation across people, 

locations, and organizational units, and a long enough follow-up period in the community 

so that violations would have proceeded through the decision-making process with the 

final outcome (to prison or not) recorded. No single database contained all of the 

information our study required, and we knew that assembling the data would be difficult 

and time consuming. Indeed, assessing, merging, and cleaning the requisite data 

consumed a full year and a half of effort. We believe it is the most comprehensive data 

set ever assembled on parole outcomes. 

36


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
We received full cooperation from the California Department of Corrections and 

Rehabilitation (CDCR), the Division of Adult Parole Operations (DAPO), and the Board 

of Parole Hearings (BPH). Each of these divisions possesses data relevant to the project’s 

goals. This project was also helped tremendously by the fact that the two principle 

investigators were working closely with CDCR during the project’s duration.

30 

We made the decision early in the project to collect data on every adult on parole in 

California at any point during the calendar years 2003 and 2004. The resulting study 

sample consisted of 254,468 unique individuals (i.e., no individual was double counted). 

These individuals were responsible for 296,958 parole violation cases. 151,750 violation 

cases were heard by a criminal court or the Board of Parole Hearings (BPH) over the two 

years (thousands more were terminated at the parole unit level). These parole violation 

and revocation incidents were the central focus of our study. 

Figure 2.2 illustrates the three ways that parolees were selected for inclusion in the study. 

1.	 Already on parole at the start of the study: First, a parolee could have been 

released from prison before January 1, 2003, and been on parole at the start of the 

study period. 

2.	 In prison at the start of the study, but released during the study. Second, a 

parolee could have been incarcerated at the start of the study period and released 

onto parole during the study period. 

3.	 Free at the start of the study, but committed to prison and released during 

the study period. Finally, a person could have started a prison term during the 

study period and been released onto parole before the end of the period. 

30 Dr. Grattet took a leave from his faculty position at the University of California, Davis, and served as 

acting Assistant Secretary for Research in the California Department of Corrections and Rehabilitation, 

where he established the Office of Research and provided a voice for research at the executive level policy 

and planning discussions. Dr. Petersilia is the founding director of UCI’s Center for Evidence-Based 

Corrections, a research center devoted to assisting corrections officials analyze data for policy purposes. 

She also co-chaired CDCR’s Expert Panel on Rehabilitation, and chaired the Governor’s Strike Team on 

Rehabilitation. In each of these capacities, she was focused on prison and parole operations in California. 

37


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
1/1/03	 12/31/04 

Observation Period 

1. 

Prison Parole 

Pr Parole ison 

2. 

Parole 

3. Prison 

Figure 2.2: Study Subject Selection Criteria 

For each parolee who “entered” our study sample in one of the three ways described in 

above, we assembled a personal and parole supervision profile for them, which consisted 

of all of the data elements illustrated in Table 2.1 below. Broadly, this profile was 

comprised of information describing their demographic details and legal histories, 

recorded recidivism events that occurred during the study period, details about the 

intensity of parole supervision, information about supervising parole agents, and 

characteristics of the communities that parolees lived in. Information about each parolee 

was extracted from several CDCR data systems and connected to other pieces of data 

using appropriate administrative and geographic identifiers. The central databases used in 

the study were: 

•	 Offender Based Information System (OBIS): OBIS contains information on all 

offenders in California correctional institutions. The database includes 

background information on all active parolees during 2003 and 2004. OBIS 

contains parolee identification codes (called CDC numbers), which allowed us to 

link individual parolees to other data sources. OBIS is the principal source of 

demographic, criminal and institutional history data. 

•	 Revocation Scheduling and Tracking System (RSTS): Using parolees’ CDC 

numbers, RSTS tracks the dates and details of parole violations that result from 

arrests or are referred from parole units, including specific charges and outcomes. 

•	 Statewide Parolee Database (SPDB): SPDB was used to identify the parole 

violations that did not produce RSTS revocation cases. SPDB identifies the 

parolee’s address, and the parole unit and parole agent to which a parolee is 

assigned. SPDB also provides information on weekly parole caseloads across 

agents and units. 

The data sources described above provided information for the outcome variables of our 

study—specifically, the timing of violations, arrests, and revocation decisions—as well 

38


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
as information about parolees’ personal characteristics and criminal histories. These data 

were combined with other CDCR sources to construct measures of parole agent, unit, and 

community characteristics. Organizational measures were drawn from the following 

31 sources:

•	 Parole Agent Database (PACD): We used data from the California State 

Personnel Board to compile the background characteristics of all state parole 

agents (gender, age, race, tenure at job, history of working in a correctional 

institution). 

•	 CDCR Annual Population Reports: Prison reception center occupancy, a 

measure of organizational pressure on decision-making, was compiled monthly 

and these data were drawn from CDCR’s publicly available annual population 

reports (e.g., CDCR 2004).

32 

•	 California Corrections Standards Authority Jail Profile Surveys: County jail 

occupancy, another measure of organizational pressure, was measured quarterly. 

The data were obtained from California’s Corrections Standards Authority (e.g., 

California Board of Corrections 2004).

33 

•	 Judicial Council of California Court Statistics Reports: Felony caseload data 

was used to gauge the impact of organizational constraints on local criminal 

justice agencies.

34 This data was put together with staffing data on the number of 

prosecutors was provided by the California Attorney Generals Office to construct 

workload ratios for county prosecutors offices.

35 

Finally, we used parolee address records to link individuals to data about their 

communities. Measures of community conditions were drawn from the following 

sources. 

• The 2000 United States Census: We geocoded (mapped) parolee addresses to 

U.S. census tracts to compile measures of community conditions, downloaded 

from the Census website.

36 These measures included indicators of socioeconomic 

disadvantage such as poverty, unemployment, public assistance and the 

prevalence of single-parent households. They also included measures of “racial 

threat”—specifically the proportion of black residents and the black 

unemployment rate in any given tract. 

31

There were several other sets of organizational- and community-level data which we ultimately decided 

not to use for empirical and/or theoretical reasons. 32

http://www.cdcr.ca.gov/Reports_Research/Offender_Information_Services_Branch/Annual/CalPris/CAL 

PRISd2004.pdf 33 http://www.cdcr.ca.gov/Divisions_Boards/CSA/FSO/Docs/2004_JPS_Annual_Report.pdf 34 http://www.courtinfo.ca.gov/reference/documents/csr2004.pdf 35 http://ag.ca.gov/cjsc/statisticsdatatabs/PersoCo.php 36 http://www.census.gov/ 

39


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
•	 The United States Substance Abuse and Mental Health Services 

Administration (SAMHSA): As a measure of service availability in parolees’ 

reentry environments, we drew data from SAMHSA listing the addresses of all 

substance abuse and mental health treatment providers in California that accept 

clients from criminal justice agencies.

37 We geocoded their addresses and then 

created a measure indicating, for every census tract in the state, the number of 

providers within 50 miles of the center of the tract. We chose the 50 mile standard 

because that is typically the distance that parolees are allowed to travel from their 

homes without special permission from their parole agents. 

•	 California Secretary of State: To generate a county-level measure of the 

“punitiveness” of different communities, we collected information on the results 

of ballot proposition voting and party registration from the Secretary of State.

38 

We selected propositions that pertained directly to state correctional practices and 

created a combined “factor” measure based on three relevant indicators. The first 

was based on county-level voting on Proposition 36 (2000 election), which allows 

first- and second-time nonviolent, simple drug possession offenders the 

opportunity to receive substance abuse treatment instead of incarceration. The 

second was based on voting outcomes about Proposition 66 (2004 election), 

which proposed to limit the application of California’s “three strikes” law. 

Finally, we included a measure indicating the proportion of registered 

Republicans in each county. 

•	 Religious Congregations and Membership Study, 2000. We compiled data on 

the number of church adherents by county to see whether communities with 

greater faith-based communities were more or less supportive of reentry, 

including both violations and revocations. 

Table 2.1 displays and organizes the various measures we have compiled. 

37 http://findtreatment.samhsa.gov/ufds/locstates 38 http://www.sos.ca.gov/elections/elections_elections.htm 

40


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 2.1: Measured Study Factors Related to Parole Outcomes 

INDIVIDUAL ADMINISTRATIVE COMMUNITY 

Parolee Characteristics Parole Supervision Community Conditions 

Age, race, gender 

Most recent commitment 

offense 

Age at 1st commitment 

Number of prior incarcerations 

History of "serious" and 

"violent" offending 

Supervision level 

Absconding reports 

Parole agent characteristics 

Agent prior work experience 

Agent workload 

Parole region 

Socioeconomic 

disadvantage 

Racial/ethnic composition 

Minority unemployment 

rate 

Residential turnover 

Public assistance support 

Sex offender registrant Criminal Justice System Church attendance


Characteristics


Second striker District attorney caseloads Treatment service 

availability 

Documented mental health Jail overcrowding 

conditions Community punitive 

Prison overcrowding attitudes 

Parole policy changes 

With the databases assembled and merged, we were then able to conduct our violations 

and revocations analyses. The specific methodologies will be described in greater detail 

in the chapters devoted to these analyses, but we will outline them briefly here. In terms 

of parole violations, we structured the data for survival analysis, which required that the 

data be assembled such that each individual parolee was observed on a weekly basis 

throughout 2003 and 2004. This data format allowed us to run multivariate survival 

models predicting the likelihood and timing of different types of violation behavior. 

Thus, we were able to assess the relative impact of individual-, institutional- and 

community-level measures on the outcomes of interest. 

For our analyses of parole revocations, we created a dataset documenting every parole 

violation case heard by the parole board or that resulted in a return to prison from a 

criminal court. These data were used to estimate logistic regression models predicting 

revocation outcomes of interest—namely, whether criminal violation cases were 

successfully prosecuted in court as opposed to being referred to the parole board, and 

whether cases heard by the board were returned to custody or continued on parole. 

41


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
FOCUS GROUPS, INTERVIEWS, OBSERVATIONS AND REVIEWS OF


CDCR POLICY MEMORANDA


In addition to the administrative and community data described above, we also collected 

extensive information from field observations, interviews with parole agents and 

managers, and reviews of agency policy memos and directives. Since Dr. Grattet and Dr. 

Petersilia were both working closely with the CDCR and DAPO on various parole 

initiatives during this study, they had ample opportunity to observe staff training, 

participate in retreats and meetings, and conduct interviews with parolees and staff. Dr. 

Petersilia chaired the parole working group on the Governor’s Rehabilitation Strike 

Team, and in conjunction with that effort conducted nearly a dozen interviews and focus 

groups focusing on parole violation policy. Dr. Grattet observed parole revocation 

hearings, interviewed parole agents and supervisors, parole regional administrators, 

deputy commissioners, parole and parole board automation staff, and parole and parole 

board executives. He and Dr. Jeffrey Lin also participated in the executive group formed 

in 2007 to develop a parole violation matrix. A graduate student research assistant also 

conducted personal interviews and field observations with more than thirty parole agents 

throughout California during the summer of 2006. In addition, project staff collected all 

major CDCR policy memorandums pertaining to parole revocation policy written 

between 2003 and 2007. These qualitative data helped guide the study design and our 

interpretation of the findings. 

Having sketched the framework of our analysis and sources of data we rely upon, in the 

next chapter we describe the broader context of parole in California, emphasizing some 

of the unique features of the system and providing the necessary background for 

understanding the empirical analyses that follow in Chapters IV, V, and VI. 

42


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER III: UNDERSTANDING CALIFORNIA’S UNIQUE


PAROLE ENVIRONMENT: RELEASE, SUPERVISION, AND


SANCTIONING


California’s prison and parole system is unlike any other in the U.S. and many of its 

unique aspects are not well understood by policymakers, researchers, and the public. 

Since our study’s main objective is to explain variations in parole violation and 

revocation practices, we must first understand how California’s broader sentencing and 

parole laws constrain and influence parole decision-making. This is not the place to 

conduct a complete review of these issues, but this chapter briefly describes those aspects 

of California’s sentencing system and parole supervision regulations that may influence 

parole recidivism rates. 

CALIFORNIA’S DETERMINATE SENTENCING LAW AND PAROLE


REQUIREMENTS


One main driver of parole revocations is the state’s determinate sentencing law, which 

dictates who will be released to parole and hence, who is subject to parole supervision 

and potential revocation. This fact alone has significant implications for the state’s parole 

system. In a determinate sentencing system, prison time served by offenders is primarily 

determined by the length of sentence imposed by the judge, rather than by the 

discretionary release decisions of a parole board. California adopted its Determinate 

Sentencing Law in 1976. Prior to that, California was an indeterminate sentencing state, 

where offenders who were sentenced to state prison would not be released to parole until 

they had completed a minimum term determined by the sentencing judge, and parole 

authorities had determined that they were suitable for release. 

Under California’s current sentencing system, only inmates convicted of very heinous 

crimes (such a murder, or kidnap for ransom), and those convicted of a third strike, are 

still given an indeterminate sentence and appear before the BPH to seek parole. Because 

of their long and indeterminate sentences, these types of offenders comprise a much 

smaller fraction of the parole population than others. 

As of June 2007, 12.5 percent of all the adult prisoners were serving life with the 

possibility of parole, 4.7 percent were third strike inmates, and 0.4 percent were serving 

death sentences. Therefore, just 17.6 percent of the state’s prison population is serving an 

indeterminate sentence.

39 The remainder—82.6 percent of California’s inmates—are 

serving determinate sentences. Once an offender has served his or her sentence, they must 

be released from prison to a set period of parole, and no review is conducted in advance 

of release to determine in advance if the inmate is suitable for placement in the 

community. The only way for prisoners to get out of prison is to serve the statutorily 

mandated percentage of the sentence a judge gave them, with some reductions allowed 

for good time credits. Under state law, inmates can receive 50 percent off their sentences 

39 CDCR: “Prison Census Data as of June 30, 2007” 

http://www.cdcr.ca.gov/Reports_Research/Offender_Information_Services_Branch/Annual/Census/CENS 

USd0706.pdf 

43


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
if they were convicted of nonviolent offenses and if they behave well in prison, and 15 

percent off their sentence if they were originally convicted of a violent offense. 

Once released from prison, virtually all offenders are required to serve a period of parole 

supervision, overseen by CDCR. Technically, state law permits the parole board to 

discharge an eligible offender from state prison and avoid parole altogether for “good 

cause,” but this occurs in only a handful of cases each year. In 2006, only 1,994 of 

129,811 felons (1.5 percent) released from state prison were not released to parole 

supervision.

40 By law, a parolee must generally be released to the county that was the 

offender’s last legal residence before commitment to prison. 

Because California releases nearly all prisoners subject to its determinate sentencing law, 

with no opportunity to retain even the most likely recidivists, and then places all of them 

on parole supervision, the state’s parole agents end up supervising some individuals who 

pose a far more serious threat to society than the typical parolee in a state with 

discretionary release. In states that use discretionary release, these high-risk prisoners can 

be denied parole and kept in prison. California parole officers often point out that their 

high revocation rates are caused by the behavior of parolees who were almost certain to 

reoffend and should not have been released from prison in the first place. On the other 

hand, since California law allows minor technical parole violators to be returned to prison 

(whereas some states do not), and these prisoners are also eventually released to parole 

supervision, California parole caseloads also include many “less serious” offenders as 

well. This point is critical to understanding parole violations in California: California 

parole caseloads likely contain offenders at both extremes of the seriousness 

continuum—offenders who probably would not be on parole in other states, either 

because they are too serious to have been released from prison in the first place by parole 

boards operating in indeterminate states, or because they are such low-risk offenders that 

they wouldn’t have been assigned to post-prison parole supervision at release. The upshot 

is California parole caseloads probably contain some of the nation’s highest risk 

offenders as well as the some of the nation’s lowest risk offenders. 

California’s Determinate Sentencing Law (DSL) not only changed the way in which 

prisoners got automatically released and required all prisoners to serve a post-prison 

parole term, but it also simultaneously and significantly increased both the length of the 

initial parole supervision term imposed and the length of the prison term that could be 

subsequently imposed if the parolee violated parole conditions. As Table 3.1 shows, 

before the passage of the DSL, prisoners released to parole were subject to a one-year 

period of parole (the maximum was 18 months). But DSL tripled the length of time on 

parole for most prisoners. Prisoners whose offenses were committed on or after January 

1, 1979 are subject to a three-year period of parole unless the parole hearing division sets 

a shorter period, which it rarely does. Most released prisoners can be discharged from 

40 An indispensible guide to understanding the legalities of California’s parole system was prepared by 

attorney Rowan Klein, entitled “An Overview of Parole and the Board of Prison Terms in California,” and 

much of the information in this chapter draws from it. It can be found at 

www.freebatteredwomen.org/pdfs/parole.pdf. The best comprehensive description of the operations of the 

California prison and parole can be found in Fama, S. et.al. (2006) The California State Prisoners 

Handbook, Prison Law Office, Berkeley, CA. 

44


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
parole after 13 months if they have committed no parole violations or new crimes while 

in the community.

41 

Equally important, DSL also doubled the length of prison time that can be imposed upon 

parole revocation from six months to one year. And under California law, when a person 

is returned to prison for a parole violation, the “clock stops” on the time owed for parole 

supervision. So, when a person leaves prison after serving time for a parole violation, he 

still faces the remaining supervision time he owed the State before he went back to prison 

for the violation. As such, parole supervision can stretch out for years for particular 

individuals. Offenders often call it “doing a life sentence on the installment plan” since 

they go in and out, never able to formally discharge from parole supervision. Typically, 

in order to discharge from parole, a parolee must have spent a minimum of 12 months in 

the community with no parole violations or new crimes. Even then, the parole agents and 

the parole board, both of whom have a say in the 13-month discharge decision, are more 

often than not reluctant to release parolees, even when a given parolee is eligible. Table 

3.1 below describes the conditions of parole discharge and revocation in California. 

Table 3.1: Parole and Revocation Periods for Non-Life Sentences 

Date of Type of Discharge Max Period Max Max Period 

Commitment Offense Review of Parole Revocation of Parole 

Offense Period Jurisdiction 

Commitment Non-Life None 1 year 6 months 18 months 

offense on or 

before 12-31-78 

Commitment Non-Life During 13th 3 years 1 year 4 years 

offense on or month of 

after 1-1-79 cont. parole 

Commitment Violent Within 30 3 or 5 years 1 year 4 years or 

offense on or Felony PC days of Life based 

after 9-26-88 667.5 completion on 

of 2 years commitment 

cont. parole offense 

Source: State of California, California Department of Corrections, Operation Manual, 

Section 81080.1.1. Updated in 2007. 

The growth of California’s prison population, combined with the policy of placing all 

exiting prisoners on parole supervision for three years, simultaneously reducing the 

discretion of parole agents to handle minor violations for an increasing proportion of 

parolees, and increasing the prison time served for violations, provides the requisite 

conditions for the growing contribution of parole violators to the state prison population. 

No other state has created this hybrid system—shifting simultaneously to fixed-term 

41 Murderers who receive and serve a life sentence, and are subsequently released on parole, are subject to 

being on parole for the rest of their lives. Felons receiving a life sentence for an offense other than murder 

are subject to supervision in the community for five years. Certain types of sex offenders are subject to a 

five-year parole term as a result of an amendment to the California Penal Code enacted in 2000 (Fama, note 

32). 

45


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
prison release and universal parole supervision—and at the same time lengthening parole 

terms and prison terms upon revocation. 

Mandatory Referral Policy 

In addition to changes in sentencing policy and the structure of parole, in the last decade, 

the discretion held by California parole agents in the handling of violations has 

substantially eroded. Over the last several years, BPH began implementing new 

regulations (15 CCR 2616), referred to as the “Robin Reagan rules,” that significantly 

added to the list of parole violations DAPO is required to refer to the parole board, 

thereby exposing more parolees to BPH decisions to return them to prison. Whereas once 

parole agents and supervisors wielded discretion about how to handle many violations, 

now much of that authority has shifted to the BPH. In 1993, about 65 percent of parolees 

apprehended for alleged parole violations were return to custody by BPH and 35 percent 

were continued on parole. By 2007, however, about 90 percent of parolees were returned 

to custody and only 10 percent were continued on parole.

42 

The reason for the loss of agent discretion lies in the creation of a policy requiring 

mandatory referrals to the parole board for many types of parolees and violations. These 

include violations deemed “serious” or “violent” by state law (California Penal Code 

Sections 667.5 and 1192.7), as well as any violation, technical or criminal, by an offender 

who has previously been convicted of a “serious” or “violent” offense (Appendix A). 

21.7 percent of parolees have at least one serious or violent offense in their criminal 

history. All of their violations would have to be considered for revocation by the parole 

board. In addition, any parole who commits the following violations are also subject to 

mandatory referral: possession, control or use of firearm, explosive and/or weapon 

(including knife with blade over 2”), involvement in schemes over $1000, sale, 

transportation or distribution of narcotic/controlled substance, absconding for over 30 

days, failure to register as a sexual offender (California Penal Code Section 290), and 

refusal to sign parole agreement, including conditions of parole (California Code of 

Regulations Title 15 2616). These regulations were adopted as a result of a heinous 

murder by a parolee and are known as the Robin Reagan rules. DAPO estimated that in 

2005, 85 percent of parole violations, including technical violations, were subject to 

mandatory referral policies. This means that parole agents and their supervisors have very 

little discretion in the handling of these cases and these offenders. The BPH makes a 

decision about whether or not to return the parolee violator to prison and the vast 

majority of cases that go before the BPH result in a return to prison. 

Whether these mandatory referral rules are appropriate or not is a political determination, 

but one thing is clear: parole agents, parole supervisors, and the DAPO division retain 

42 LAO report, note 20. 

46


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
discretionary decision-making power over a declining percentage of violations.

43 Like 

California’s sentencing system, discretion in parole has shifted from corrections 

professionals to legislative and regulatory bodies that are politically elected or appointed. 

This change has occurred with virtually no discussion or public input, but the 

consequences are critically important. For one, it means that much is written erroneously 

about how changes in parole agent recruitment, training, or culture could reduce the 

number of parolee returns to prison. The parole agent recommends the disposition for the 

violation (e.g., to prison or not), but ultimately, the parole board has the sole authority to 

return a parolee to prison. These and other legal and procedural constraints are important 

to understanding the very complicated processes of prison release, parole supervision, 

and all too often, return to prison. 

SUPERVISION OF PAROLEES 

A prisoner remains in the legal custody of CDCR while on parole. CDCR’s Division of 

Adult Parole Operations (DAPO) governs parole supervision while the BPH’s 

responsibilities include all parole violation hearings as well as the recommitment of 

parolees to prison. DAPO has an annual budget of about $810 million (about one-tenth of 

CDCR’s annual budget), which supports 2,300 parole agents in the field dispersed among 

190 parole units, across four parole regions. DAPO also operates 19 reentry centers and 

two restitution facilities. Parole also operates parole outpatient clinics and has about 150 

clinical social workers serving the mentally ill and sex offenders. According to CDCR, it 

currently spends $4,300 per year to supervise a parolee, compared to the $43,000 annual 

cost per prisoner. 

The BPH, on the other hand, has an annual budget of $109 million. The board has 

seventeen Commissioners who are political appointments made by the Governor and 

confirmed by the California State Senate. The Board is “the administrative board 

responsible for setting parole dates, establishing parole length and conditions, discharging 

sentences for certain prisoners and parolees; granting, rescinding, suspending, 

postponing, or revoking paroles; conducting disparate sentence reviews; advising on 

clemency matters; and handling miscellaneous other statutory duties” (15 CCR § 2000 

a10). While Commissioners conduct revocation hearings themselves, the vast bulk of the 

roughly 45,000 revocation cases are delegated to Deputy Commissioners. Only the BPH 

can return a parolee to prison after holding a revocation hearing. 

Prior to release, parolees are assigned a parole agent in the parolee’s community. A 

prisoner released on parole is usually paroled to the county of his or her legal residence 

prior to incarceration. Generally, “high control” parolees—those deemed to require a 

high level of supervision—must report to a parole office within 24 hours of release from 

prison. All other parolees must make face-to-face contact with their parole agent by the 

43 Mr. Tom Hoffman, current director of DAPO spoke out against the rules which send certain cases 

“straight to the Board,” and in his opinion, resulted in rather minor parolees being returned to prison due to 

these mandatory rules. As a result of his views, his confirmation was opposed by two senators, who called 

his “philosophy is a threat to public safety.” Senator Denham: “California should not be soft on crime. 

http://republican.sen.ca.gov/news/12/pressrelease4695.asp urged more discretion, and was republican 

senators were “outraged over his confirmation.” 

47


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
first working day following prison release, and the agent typically will have them sign off 

on the written description of their conditions of supervision. Certain conditions (called 

general conditions), such as not to violate the criminal law and to report to the local 

parole officer, are imposed on all parolees. Other conditions (called special conditions), 

such as requiring narcotics testing or prohibiting the use of alcohol, may also be imposed. 

The basic requirements of parole imposed on all California parolees are to report 

immediately to their assigned parole agent upon release from prison and as directed by 

the agent; to immediately report any address or employment change; to obey all parole 

agent instructions; to carry or have access to no weapons, including guns and knives with 

long blades; and to commit no new crimes. 

The BPH can impose additional conditions on parole that it deems proper at the time of 

granting parole, and it can impose additional conditions in response to a parolee’s 

violations. The most common special conditions are that a parolee abstains from use of 

drugs and/or alcoholic beverages, submits to narcotics testing, or participates in 

psychiatric treatments. But Penal Code Section 3053(a) requires that all conditions placed 

on parolees be “reasonable,” which means that there has to be a relationship to the crime 

for which the offender was convicted, or that the condition be reasonably related to the 

prevention of future criminality. 

Penal Code Section 290 requires some parolees to register as sex offenders and avoid 

certain housing locations (e.g., near an elementary school). Parolees are notified of these 

parole conditions before they are released, and they must sign a parole agreement 

indicating they are willing to comply with them prior to their date of release. The 

supervising parole agent may also impose additional special conditions of parole. For 

example, most parolees have drug-testing conditions that allow them to be randomly 

tested by parole agents. Parolees with histories of gang-related violence may also be 

required to refrain from associating with gang members. 

DAPO has the responsibility for providing services and supervising all California 

parolees. State law does not specify exactly how CDCR’s parole division is to supervise 

and provide services to most parolees. The final classification of parolees lies with the 

DAPO and parole supervisors in the field. To determine a parolee’s supervision level, 

parole agents use a method of assessment that is quite crude in comparison to modern 

risk assessment techniques.

44 It begins with an examination of the parolee’s commitment 

offense and includes a subjective assessment of the general features of the parolee’s past 

offending history (Table 3.2). 

44 In 2006, DAPO adopted an actuarial risk assessment instrument called COMPAS, a product of 

Northpoint, Inc. However, the division continues to use the older method for placing parolees into 

supervision categories. 

48


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 3.2: Risk Assessment Methodology 

Prior pattern of 

response to 

Pattern of criminal custody / 

behavior Prior patterns supervision 

Score: 8-10	 Long history of 

predatory/violent crimes 

Score: 5-7.99	 Long history of nonviolent or brief history 

predatory/violent crimes 

Score: 0-4.99	 Brief history of nonviolent crimes 

Frequent or severe 

incidents in 3 or more 

areas 

Frequent or severe 

incidents in 1 or 2 

areas 

Moderate or 

occasional incidents 

Frequent or severe 

incidents (gangs, 

escape, etc.) 

Moderately 

frequent or severe 

incidents (minor 

parole violations) 

Minor or infrequent 

incidents 

(nuisance) 

Source: CDCR Department Operations Manual C8:A49. 

A “Base Risk Score” is computed by averaging the scores in the three columns above and 

a rating of commitment offense, also based upon a 0-10 scale. This score is then put 

together with a “Base Needs Score,” which averages six scales that are designed to 

measure various offender needs (housing, means of support, health, transportation, 

community survival skills, and patterns of social activity). The reliability and validity of 

these assessments has never been subjected to research. The Base Risk Score and Base 

Needs Score are then used to determine which of six supervision categories a parolee 

should be placed in. 

Characteristics of Parole Agents 

California parole agents are sworn officers and members of the powerful California 

Correctional Peace Officers Association (CCPOA). CCPOA currently has over 30,500 

members, representing parole agents and the correctional officers who work inside the 

state’s 33 prisons. 

As parole populations have increased so too has the number of parole agents. Increases in 

parole agent hiring in recent years has primarily drawn from the ranks of CDCR’s 

institutions and prisons system. California parole agents starting pay is $60,396 per year 

and receive the same peace officer retirement packages as correctional officers. Parole 

agents in California are required to have either a bachelor’s degree or up to two years 

experience supervising inmates. When parole agent vacancies occur, priority and 

preference points are given to persons currently employed by CDCR. Parole agent 

positions are generally thought to be preferable to correctional officer positions in a 

prison because there is more autonomy and flexibility in work activities, and the 

community environment is not as oppressive as the prison. As a result, the majority of 

parole agents hired in California over the last two decades have come from the prisons. 

During 2003 and 2004, 80 percent of supervising parole agents had previously worked in 

CDCR prisons. 

49


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Some scholars, along with of the parole staff we have discussed the issue with, have 

speculated that this influx of prison personnel to parole has altered the culture of the 

parole division towards a more legalistic, punitive, surveillance orientation, and away 

from a service orientation.

45 Others have questioned whether the symbiotic relationship 

between prison and parole staff is healthy, arguing that prison guards and parole officers 

have a financial incentive to keep the number of inmates high—helping to preserve their 

jobs, ensure high salaries, and increase membership dues for the politically powerful 

CCPOA. 

It is not clear whether recent changes in parole agent hiring practices have influenced the 

culture or violation practices of DAPO. One could argue that prison officers who apply to 

become parole agents do so because they wish to be more helpful than they can be within 

the prison setting. In fact, parole agents in our focus groups often revealed this motivation 

for joining DAPO. 

In our analyses, we are able to test whether the parole agents’ prior work experience— 

specifically whether they had worked previously in a prison or not—is related to their 

handling of parole violations. We are also able to examine whether parole agents’ 

characteristics (e.g., race, gender, age), and prior work experience are related to parole 

outcomes. 

Caseload Size and Contact Standards 

Despite increased the hiring of parole agents, their ranks have not kept pace with the 

growth in parole populations. Caseloads used to be one agent for every 45 parolees in the 

1970s, and are now funded by the California Legislature at 70:1 (70 parolees for every 

parole agent) for purposes of determining DAPO’s budget, but actual “average” 

caseloads are often over 100:1. The American Probation and Parole Association recently 

endorsed 50:1 for adult caseloads. Caseloads, contact standards and working conditions 

for parole agents are delivered in accordance with a longstanding agreement with the 

CCPOA. Agents’ caseloads are measured in “points”—which reflect the number of 

parolees under supervision, as well as the intensity of supervision delivered. (That is, 

parolees in higher supervision categories contribute more points than those in lower 

categories.) According to the current CCPOA agreement, agent points may not exceed 

160 points, and any changes in workload must be negotiated with CCPOA’s bargaining 

unit. 

At release, parolees are assigned to one of five levels of supervision, with the assigned 

level determining the frequency and level of oversight provided by the parole agent. 

Agents have no discretion regarding is the placement of parolees on their caseload. The 

possible classifications are: high control, high service, control service, second striker, 

45 See for example, Simon, J., (1993) Poor Discipline: Parole and the Social Control of the Underclass, 

University of Chicago Press, Chicago, Ill., and McCleary, R. (1979) Dangerous Men: The Sociology of 

Parole, Sage Publications, Thousand Oaks: CA, and the Institute of Governmental Studies (2008) 

California Correctional Peace Officers Association. Berkeley, California. Available at 

http://igs.berkeley.edu/library/htCaliforniaPrisonUnion.htm., accessed May 15, 2008. 

50


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
high-risk sex offender, minimum service, and other. Table 3.3 describes what each 

designation means, relevant contact levels, and other conditions of supervision. 

Table 3.3: California Parole Population Caseloads and Supervision Requirements 

LEVEL OF SUPERVISION SELECTED PAROLE CONTACT AND 

TESTING REQUIREMENTS 

High Control 

Parolees who were convicted of violent 

felonies in Penal Code 667.5(c), must 

register as sex offenders, are validated 

gang members, or high-notoriety cases. 

High Service 

Refers to parolees who have special 

service needs (severe addiction problems) 

or behavioral patterns (severe mental 

illness). 

Control Service 

Require active supervision. Refers to 

parolees who do not meet the criteria for 

High Control or High Services 

High Risk Caseloads 

Second Striker 

Parolees with at least two prior convictions 

for serious or violent offenses. Ideal ratio 

of 40:1 

High Risk Sex Offender 

Defined by the CA Dept of Justice, uses 

criteria set forth under PC 290(n)(1), PC 

667.5 and 667.6. Ideal ratio of 40:1. 

Minimum Service (MS) 

This classification refers to parolees who 

are on monthly mail-in, and these are 

counted as ‘contacts.’ These individuals 

need to make only two to three face to face 

or collateral contacts with their parole 

officer each year 

� 2 face-to-face contacts per month (one must 

be at residence) 

� First home visit within 6 days of release 

� 1 drug test per month, if required 

� 2 collaterals per quarter 

� 2 face-to-face contacts per month (one must 

be at residence) 

� 1 drug test per month, if required (Civil 

addicts may have weekly testing) 

� 2 collaterals per quarter 

� 1 face-to-face in residence every other 

month 

� 2 drug tests per quarter 

� 1 collateral every 90 days 

� Most CS cases drop to MS automatically at 

180 days 

� 2 face-to-face per month; 4 per quarter in 

home 

� 1 drug tests per month 

� 2 collaterals per month 

� 2 face-to-face per month; 4 per quarter in 

home 

� 1 drug test per month 

� 2 collaterals per month 

� Quarterly meeting with person who knows 

parolee well. 

� 1 home visit within 30 days of being 

assigned to MS 

� 1 face-to-face or collateral every 4 months 

� 1 monthly report turned in by 5th of every 

month. 

� Face-to-face contact 30 days prior to 

discharge 

� Drug testing waived 

51


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Parole Officials’ Responsibilities and Powers 

Ensuring that parolees live up to their parole contracts is the principal responsibility of 

parole agents. California parole agents are equipped with the legal authority to carry and 

use firearms, to search places, persons, and property without the requirements imposed 

by the Fourth Amendment (in other words, the protection against unreasonable search 

and seizure), to order arrests without probable cause, and to confine without bail. 

Importantly, the standard CDCR “Notice and Conditions of Parole” provides that “you 

and your residence and any property under your control may be searched without a 

warrant by an agent of the Department of Corrections or any law enforcement officer.” 

The constitutional right to be free from unreasonable searches and seizures is virtually 

non-existent while on parole. A parole officer may authorize a search without the 

parolee’s consent, without a search warrant, and without probable cause or even a 

reasonable suspicion that the parolee has violated parole. The power to search applies to 

the household where a parolee is living and business where a parolee is working. The 

ability to arrest and confine the parolee for violating the conditions of agreement makes 

the parole agent, in a sense, a walking court system.

46 

These broad search powers, combined with urinalysis testing as well as office and home 

visits, often reveal parolees being out of compliance with parole conditions—the result of 

which can be the revocation of parole. Parole can be revoked for cause, including but not 

limited to violating any general or special condition of parole, absconding from parole, 

psychiatric endangerment, failing to sign a parole agreement containing lawfully imposed 

conditions of parole, or committing a crime 

Revocation of parole can result in the parolee receiving up to one year in prison and 

extending the parole period to 48 months, or 84 months in cases where the parolee is 

subject to five years on parole. Parolees are allowed to earn one-day credit for each day 

in prison on a parole revocation period, subject to certain restrictions. Parole revocation 

hearings determine whether a preponderance of evidence is present to show a good cause 

finding that the parolee has violated any law or condition of parole. Parolees may be 

returned to custody for up to 12 months with a good cause finding. Typically, the hearing 

is presided over by a deputy commissioner, and is considered administrative by nature. 

Present at the hearing are the agent of record, the parolee, a hearing agent, requested 

witnesses and an attorney for the parolee. 

There is another agency that is often involved at this point: the county District Attorney’s 

office. The majority of parole violations in California involve the commitment of new 

crimes. Some parolees who commit new crimes are prosecuted for the criminal offense in 

the courts and sentenced to a new prison term—which can be of any length appropriate to 

the crime of conviction. When this happens the parolee’s parole is considered revoked by 

the county court and they are returned to custody with a new term. However, prosecutors 

often decide not to prosecute parolees for new offenses—either because a lack of 

evidence would make a court prosecution difficult, or because the prison sentence 

46 This information is taken from Fama et al., note 32. 

52


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
resulting from court prosecution would not be much longer than the penalty that could be 

imposed by the BPH for a parole violation. These cases are then referred to BPH for a 

revocation hearing. 

A parolee’s parole period terminates after the he or she has served the entire term of 

parole, or if the Agency discharges the parolee from parole early for good behavior. For 

nonviolent parolees (those whose crimes are not enumerated in Penal Code section 

667.5c), parole automatically terminates at the end of any continuous 13 month period in 

which 1) parole has not been revoked or suspended for absconding; 2) the DAPO has not 

recommended retention on parole; and 3) DAPO or BPH has not acted on a 

recommendation to retain them within that period.

47 In most cases, parolees—even those 

with no violations—are not discharged early. 

In sum, while California’s incarceration rate and its ratio of parolees to the California 

population is not the highest in the U.S., its universal application of parole supervision, 

combined with its long initial parole supervision term and its mandatory parole 

revocation rules, provide the requisite conditions for the increasing contribution of parole 

violators to its prison system. 

CRIMINAL JUSTICE SYSTEM CAPACITY 

Beyond California’s state sentencing and parole policies, the characteristics and capacity 

of its local criminal justice system also impact revocations. Presumably, if county jails 

are overcrowded, or the resources of the District Attorney (who prosecutes parolees’ new 

crimes) are strained, the pressure to return parolees to prison via the parole violations 

route, instead of seeking new criminal convictions, would be expected to increase. 

California’s jail system is dangerously overcrowded, and as such, counties may have a 

significant incentive to quickly transfer parolees to state prison to alleviate crowding in 

local custodial institutions (and save the associated costs). A recent study of California’s 

jails found that its adult facilities are bursting at the seams.

48 In 20 of California’s 58 

counties, the local jail system is under a court-ordered population cap. An additional 12 

counties have imposed population caps on themselves to avoid the costly litigation that 

could result from crowding. The study reported that, “In 2005, 233,388 individuals in 

California avoided incarceration or were released early from jail sentences due solely to 

lack of jail space.” 

The fact that many county jails are under court-ordered population caps, while the state 

prison system is not—and must accept all commitments—is critically important for 

understanding parole revocations. Crowded jails probably put pressure on local criminal 

justice systems to revoke parolees through the parole violation process rather than use the 

local criminal courts to prosecute new crimes, especially if the violations are less serious. 

If parole violators get processed through the state-BPH parole revocation route, they 

usually await the disposition of their case in a state-funded prison as opposed to a county47 See Klein, note 32.
 48 California State Sheriffs’ Association (2006) Do the Crime, Do the Time? Maybe Not, in California,


Sacramento: CA.


53


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
funded jail. Moreover, if the violation hearing results in a return to custody, they will 

serve their revocation term in state prison versus county jail. Alternatively, if the district 

attorney chooses to prosecute them for a new crime in criminal court, the parolee awaits 

their case disposition in county jail and if convicted, will often serve their time in a local 

jail. But due to jail crowding, these parole violators may be released early to comply with 

county court-ordered jail population caps. 

Since the standard of proof for a new criminal conviction is higher than the standard of 

proof to sustain a parole violation, if the evidence is weak or witnesses do not cooperate, 

the district attorney may end up losing the case. And even if they win the case but the jail 

is overcrowded, the parolee may end up spending little time incarcerated. Given these 

factors, district attorneys often go for the “sure thing” of a BPH hearing—with the 

maximum term of 12 months and the lower standard of proof—and this dramatically 

impacts the prison return rate of parolees. As the California Coalition on Corrections 

recently concluded: “Problems at the local level directly cause overcrowding at the state 

level. The huge shortage of county jail beds has resulted in a massive shift of short-term 

offenders to prison.”49 This problematic relationship has major implications for the 

processing of parole violators in California. 

COMMUNITY CHARACTERISTICS AND REENTRY ENVIRONMENTS 

Researchers often examine “recidivism” outcomes as stemming from parolee attributes, 

such as personal characteristics and criminal record. In recent years, researchers have 

expanded modeling efforts to include static and dynamic risk factors, but still the models 

are limited and person-centric. We believe parole violations and revocations are a 

function of the offender, the system, and the community, as previously discussed. 

Certainly the underlying characteristics of the reentry environment (e.g., job availability, 

poverty, housing) as well as the political preferences of the local citizenry may be 

important contributors to how parolees are supervised and served, and how parole 

violations are handled. 

California is the largest state in the nation. It currently has a population of over 37 million 

residents, continues to be fast-growing, and 12 percent of all U.S. citizens now live in 

California. It is the third largest state in terms of geographical area, and also represents 

the nation’s most diverse population in terms of ethnicity, political preferences, and 

economic status. In the middle of the state lies the California Central Valley, which is 

California’s agricultural heartland and grows approximately one-third of the nation’s 

food. Democratic strength is centered in coastal regions, especially the San Francisco Bay 

Area, Central Cost and Los Angeles County. Republican strength is greatest in the San 

Joaquin Valley, which includes the rapidly growing cities of Stockton, Modesto, Fresno, 

and Merced, Orange County, and certain sections of San Diego County. 

California is often thought of as wealthy, but that too is highly variable across the state. 

Per capita personal income in California averaged $38,956 in 2006, ranking 11th in the 

49

The California Coalition on Corrections (2007), Rebuilding Corrections, Sacramento, CA. Available at 

www.rebuildcorrections.lincal.com/REBUILDING%20CORRECTIONS%20June%2027%20%202007%2 

0FINAL.pdf 

54


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
nation, but this varies widely by geographic region and profession. The Central Valley is 

the most impoverished, with many migrant farm workers making less than minimum 

wage. Recently, the San Joaquin Valley was characterized as one of the most 

economically depressed regions in the U.S., on par with Appalachia. Yet many of 

California’s coastal cities include some of the wealthiest per-capita areas in the U.S., as 

do some of the entertainment centers (e.g., Beverly Hills). California prisoners returning 

home face very different community contexts depending of which of the state’s 58 

counties, and which areas within those counties, they are released to. 

Figure 3.1 provides a graphical representation of the number of prisoners released by the 

CDCR and the counties to which they returned. A significant proportion of California’s 

prisoners are released in the state’s southern counties. The four southern counties of Los 

Angeles, San Bernardino, San Diego, and Riverside accounted for over half of all 

parolees (53 percent) on July 1, 2006. The county of Los Angeles alone accounted for 

over 30 percent of these parolees. 

Parolees are not distributed evenly across the state, but are instead highly concentrated in 

some neighborhoods. For example, in Los Angeles county, the 1 percent of census tracts 

with the most parolees in them contained 8.6 percent of all parolees on July 1, 2006. The 

top 5 percent of the census tracts contained 23.5 percent of the state’s parolees. The top 

10 percent of the census tracts contained 36.5 percent of parolees (California Expert 

Panel 2007). 

Prisoners are also returning to neighborhoods that are poorer, have more unemployment, 

crime, single-parent families, and transient populations. These environments provide 

greater anonymity, fewer job and positive social opportunities, and tend to be places were 

there are already high concentrations of drug users and gang activity. Sociologists have 

conceptualized these kinds of communities as “socially disorganized” (Bursik and 

Grasmick 1993; Shaw and McKay 1942; Sampson and Wilson 1995) and proposed 

various ways of objectively measuring the phenomena (Sampson, Raudenbush, and Earls 

1997; Kubrin and Weitzer 2003). Two key indices that sociologists use are “concentrated 

disadvantage”—which tracks the number of individuals below the poverty level, 

unemployment, the median income, the percent black, and the percent of single-headed 

households—and “residential instability,” which includes the percent of renters in a 

neighborhood and the percent of residents who currently live in the neighborhood who 

lived somewhere else five years earlier. Parolees in California reside in neighborhoods 

that are significantly more socially disorganized on both measures. 

55


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Figure 3.1: Number of Prisoner Releases by California County, 2006 (Source:


CDCR).


In Los Angeles County alone, the census tracts with high numbers of parolees have 

poverty rates over double that of tracts with low numbers of parolees. These high-density 

parolee tracts also have double the proportion of single parent households, double the 

unemployment rate, 43 percent lower median income, and over double the violent crime 

rate of low-parolee tracts (Hipp and Yates 2007). 

California is not unique in this aspect, as research has shown that most parolees return to 

a small number of census tracks within large urban areas (Clear 2007). There is also the 

sense that with new restrictions on where sex offenders can live (as a result of Jessica’s 

Law), there are fewer and fewer places they can live, and so certain parolees are being 

concentrated in ever-shrinking geographic areas both in California and nationally. 

In sum, California’s diversity in economics, political preferences, and concentration of 

parolees is likely to significantly influence the handling of parole violations. 

Communities with greater financial resources are likely to have access to more 

rehabilitation and work programs, and those having more progressive political views may 

56


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
have more tolerance for minor rule violations. Communities with both resources and 

liberal leanings might be willing or able to fund a greater array of intermediate sanctions 

to respond to violations. On the other hand, resource-poor communities suffering from 

high levels of poverty, homelessness, and unemployment may not be able to fund many 

alternatives to prison, and if scant resources exist in politically conservative communities, 

we may see a higher return-to-prison rate in those places. These and other interactions 

between parolee behaviors, community characteristics, reentry services, and returns to 

prison are explored in our multivariate statistical analyses. 

57


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER IV: CHARACTERISTICS OF CALIFORNIA’S ADULT


PAROLEES AND THEIR SUPERVISION


California’s parole system is the largest in the nation—probably the world. On the last 

day of December in 2003, the parole population in California was 110,173. It has grown 

about six percent since then. However, point in time estimates such as these, which are 

frequently used to characterize the scale of the system, are misleading. Many more 

individuals go on and off parole in a given year. In other words, the parole system 

manages many more people that a static estimate reveals. In fact, during 2003 and 2004 

there were 254,468 individuals that spent time on parole. 

Figure 4.1 below illustrates the scale and fluidity the parole population. At the beginning 

of 2003 many prisoners were completing their prison term and preparing for release to 

parole; others were on parole but nearing discharge; some were in-prison for a parole 

violation waiting to be released; others absconded for part of 2003 and 2004, but were on 

parole for some portion of the period; and finally some spent the entire period under 

supervision. All of these individuals placed demands on the parole system during 2003 

and 2004. In this chapter, we describe the characteristics of this population. 0 

50 100 150 

2

00 

2

50 

# Parole

es, in 1,0

0

0's 

January 2003 July 2003 December 2003 July 2004 December 2004 

On Parole, Not Absconded On Parole, Absconded 

In Prison, Additional Sentence In Prison, Original Sentence 

Discharged from Corrections Not Yet Entered Corrections 

Figure 4.1: Parole Population Status during Study Period 

58 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
DEMOGRAPHIC AND CRIMINAL-LEGAL PROFILES OF CALIFORNIA


PAROLEES


The fact that California places everyone on parole means that the characteristics of its 

parole population are similar to its prison population. The only difference is that certain 

offenders (e.g., Third Strikers, Lifers) will be serving longer terms so that in any given 

year, fewer of them are released and placed on parole. 

Gender, Age, Race 

California parolees are mostly male, minority, and between ages 30 and 44. About 90 

percent of parolees were male, and about 70 percent were persons of color—mostly black 

(26 percent) and Hispanic (39 percent). Roughly 31 percent of parolees in 2003 and 2004 

were white.

50 The average age at release (on the current term) was 35.5 years. 34 percent 

of parolees are aged 30 and under and 15 percent are over age 45 (See Table 4.1). 

Table 4.1: Demographic Characteristics of California Parolees, 2003 and 2004 

Number Percent 

Gender Male 227,665 89.5 

Female 26,800 10.5 

Race White 78,194 30.7 

Black 66,393 26.1 

Hispanic 99,082 38.9 

Asian/P.I. 2,441 1.0 

Other 8,355 3.3 

Age group Age 18-30 93,095 36.6 

(at release) Age 31-44 113,631 44.7 

Age 45+ 41,354 16.3 

Don’t know 6,388 2.5 

Average age 35.5 

Current Commitment Offense and Prior Criminal Record 

Table 4.2 presents the details of parolees’ commitment offenses. The plurality of parolees 

in 2003 and 2004 (35 percent) were released after having served a prison sentence for 

drug charges. Almost 30 percent were property offenders, 20 percent were violent 

offenders, and about five percent were serving time for sex offenses. 

Almost 11 percent of parolees were committed to prison on a serious offense, and 

another 11 percent committed offenses that were considered both serious and violent. 

50 The prison population also over-represents racial minorities relative to their proportion in the state’s 

resident population. Racial and ethnic minorities are 53 percent of the California population but 72 percent 

of the prison population. In this regard, California mirrors the nation, which over-incarcerates minorities 

compared to their percentage in the general population (Petersilia 2006). 

59


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
State law (California Penal Code Sections 667.5 and 1192.7) provides official definitions 

of these terms. Violent offenses include murder, robbery, and rape and other sex offenses. 

Serious offenses encompass the same offenses as the violent category, but also include 

other offenses such as burglary of a residence and assault with intent to commit robbery. 

Table 4.2: Current Commitment Offense Characteristics of California Parolees, 

2003 and 2004 

Number Percent 

Commitment offense Violent 50,628 19.9 

Property 74,528 29.3 

Drugs 89,252 35.1 

Sex 12,035 4.7 

Other 27,042 10.6 

Don’t know 983 0.4 

Serious/violent commitment 

offense Neither 198,934 78.2 

Serious 27,332 10.7 

Serious and violent 28,202 11.1 

"Strike count" 2nd striker 34,610 13.6 

3rd striker 25 0.0 

Sex offender registration required Yes 18,260 7.2 

About 14 percent of parolees were on their “second strike”—stemming from California’s 

1994 “three strikes and you’re out” statute (Chapter 12, Statutes of 1994, AB 971, Jones). 

Under this law, courts are required to impose a prison sentence of 25 years-to-life to 

offenders convicted of three felonies if the first two were serious and/or violent, as 

defined above. The third strike can be for any felony, so parolees on their second strike 

who commit another felony will face the extended prison sentence associated with a third 

strike. There are only 25 third strikers in our study population because the vast majority 

are serving long prison sentences and haven’t yet been released. 

About 7 percent of parolees in our study sample were required by law to register as sex 

offenders. Under this law (California Penal Code Section 290), offenders convicted of 

specified sex offenses are required to register their address with the local police or 

sheriff’s department upon parole. Some areas restrict the places where registered sex 

offenders can live, and due to the passage of Proposition 83 in 2006, California is 

currently moving towards GPS-monitoring of all registered sex offenders. 

Table 4.3 presents the offending histories of the study population. The average age of 

first commitment to California adult prison was 31. Including the current commitment, 

parolees averaged 1.5 lifetime prison sentences and 2.5 lifetime prison “spells.” 

(Sentences are commitments for new offenses, and can include multiple prison spells, 

which are comprised of all prison entries and exits, including those for parole violations). 

60


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Almost 12 percent of parolees had one or more serious prior offenses on record, and 

almost 10 percent had one or more violent priors on record. 

Table 4.3: Offending Histories of California Parolees, 2003-4 

Number Percent 

Age at 1st commitment to CA prison Average 31.2 

Number of prior prison sentences (includes 

current term) 1 186,885 73.4 

2 39,455 15.5 

3 15,340 6.0 

4 7,035 2.8 

5 or more 5,753 2.3 

Average 1.5 

Number of prior prison Spells (includes current 

spell) 1 136,297 53.6 

2 37,320 14.7 

3 24,345 9.6 

4 16,965 6.7 

5 or more 39,541 15.5 

Average 2.5 

Number of serious prior prison commitments 0 225,052 88.4 

(Does not include current commitment offense) 1 21,711 8.5 

2 4,704 1.8 

3 1,183 0.5 

4 455 0.2 

5 or more 436 0.2 

Average 0.2 

Number of violent prior prison commitments 0 229,862 90.3 

(Does not include current commitment offense) 1 17,709 7.0 

2 3,646 1.4 

3 1,136 0.4 

4 499 0.2 

5 or more 689 0.3 

Average 0.1 

Churner status Yes 19,161 7.5 

(6+ returns within 7 years) 

As mentioned previously, policymakers and researchers are concerned about the number 

of offenders who repeatedly “churn” into and out of prison. Blumstein and Beck (2005) 

define churners as people who enter prison six or more times over a seven-year span. By 

definition, churners’ correctional histories are characterized by frequent short spells in 

prison interspersed with frequent short spells on parole. Churners are believed by parole 

officials to have high rates of drug and alcohol addiction, and to be especially difficult to 

61 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
employ and house. While they do not occupy a large amount of prison bed-space on any 

given day, churners consume a greater-than-average share of correctional agency 

resources because of the processing costs associated with their frequent prison entries and 

exits, as well as their entries to and removals from parole caseloads. Based on Blumstein 

and Beck’s definition, 7.5 percent of California parolees in this study can be 

characterized as churners—meaning that they experienced six or more returns to a 

California prison over a seven year period. 

PAROLE CASELOAD AND PAROLE AGENT CHARACTERISTICS 

Table 4.4 presents characteristics of parole supervision and supervising agents during 

2003-4. Twenty-four percent of parole supervision was over parolees in the “Minimum 

Service” category, with the requirement that these parolees see a parole agent only twice 

a year. This sort of parole oversight costs money to provide, and takes up parole agents’ 

time, but cannot possibly be expected to provide a meaningful check on parolee 

criminality. Another 52 percent of supervision was over parolees in the “Control Service” 

classification; these parolees see a parole officer twice every three months. This level of 

supervision is perhaps not quite as remote as that provided in Minimum Service 

supervision, but is still unlikely to give a parolee a particularly strong sense that the state 

is paying attention to his or her actions. 

“Minimum Supervision” and “Controlled Service”—in which relatively little supervision 

is allotted to parolees—accounted for 76 percent of the total supervision applied to 

parolees in 2003-4. Given that these offenders are initially placed in low-risk categories 

because they are not expected to be likely recidivists, one cannot help but wonder 

whether the effort expended to provide cursory oversight to so many former inmates is an 

effective use of resources. 

Characteristics of parole agents vary in several measurable ways. During 2003-4, 35 

percent of parole supervision was done by white parole agents, 32 percent by black 

agents, 25 percent by Hispanic agents, and the rest by Asian agents and those from other 

racial categories. In terms of agent age, 30 percent of supervision during 2003-4 was 

done by agents under 40 years of age, 61 percent by agents between the ages of 40 and 

55, and 9 percent by agents over 56 years of age. In terms of gender, 71 percent of parole 

supervision was done by male agents. 

The majority of parole supervision during the study period was performed by agents with 

less than ten years on the job; 48 percent of parole supervision was done by agents with 

three years or less of job tenure as parole agents; 32 percent by agents with three to ten 

years of job tenure; and 20 percent by agents with greater than ten years of job tenure. 

Agents who previously worked in CDCR correctional institutions were responsible for 83 

percent of parole supervision during the study period. 

62


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 4.4: Characteristics of Parole Supervision in California during 2003 and 2004 

Percent 

Supervision Type 

Min Supervision 24.1 

Controlled Service 51.7 

High Control 11.7 

High Service 0.9 

High Risk Caseload 11.7 

Parole Region 

Region 1—Central Valley 21.1 

Region 2—Central and North Coast 19.6 

Region 3—Los Angeles County 32.2 

Region 4—San Diego and Southeastern Counties 27.1 

Parole Agent Points 

0-160 2.3 

161-277 (Mean) 59.2 

277+ (Above Mean) 38.5 

Parole Agent Race/Ethnicity 

Black 31.5 

Hispanic 26.1 

Asian 5.6 

White 34.6 

Other Race 2.2 

Parole Agent Age 

26-39 31.3 

40-55 60.6 

56-72 8.2 

Parole Agent Tenure 

3 Years or Less 47.6 

3-10 Years 32.9 

10+ Years 19.5 

Previous Prison Employment 82.6 

This chapter has described the characteristics of California parolees and the nature of 

their supervision. The description illustrates and highlights a key point made in Chapter 

III. Parolees in California include both individuals with very serious and sometimes 

violent criminal offending histories and a much larger group of individuals who are prone 

toward less serious drug and property offending. The groups are also stratified by the 

degree to which offenders “churn,” committing new crimes and parole violations, and 

cycling in and out of prisons for years. Thus, the seriousness of a parolee’s past offending 

and the risk they pose for committing new crimes and violations represent two separate 

dimensions of the parole population and both dimensions need to be considered in the 

creation of parole policy. Overlaying this population is an overstretched supervision 

system in which large proportions of parolees are supervised at minimal or moderate 

levels and where the focus of attention privileges the seriousness of past offending over 

the risk of new crime. Moreover, parole agents vary along several dimensions that may 

indicate differences in the ways they respond to violations. These two concerns—how to 

63


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
conceptualize which kinds of offenders who pose the greatest risk to reoffend and how to 

ration and match supervision to those offenders who need it the most—are further 

developed in Chapter V. 

64


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER V: WHAT FACTORS PREDICT PAROLE VIOLATIONS?


As we discussed in the previous chapters, California parolees vary in their criminal 

backgrounds and personal characteristics, the kinds of communities to which they return, 

and the systems of law enforcement and parole supervision to which they are subject. 

Throughout this report, we combine these three dimensions to form a triangulated view of 

parole outcomes. The extent to which individual, community, and organizational factors 

lead to variation in reported parole violations is the subject of the present chapter. 

Although most parole violations in California do not result in revocation, parole 

violations represent the starting point of the revocation process. Officially recorded 

violations are the most proximate measure of parolee misbehavior and failure, much 

more sensitive, for example, than re-arrest, reconviction, or reincarceration data. Since 

many violations are technical violations of the conditions of parole, rather than criminal 

in nature, violation reports are not necessarily as serious as the aforementioned outcomes. 

Nonetheless, the largest share of violations is, in fact, alleged criminal behavior, which 

can range from relatively minor misdemeanor offenses to violent felonies. How 

violations are handled is a subject that has garnered a significant amount of policy 

attention in the midst of the broader movement to reform the parole system in California. 

Specifically, concerns have been raised about whether technical parole violators are being 

return to prison at an unnecessarily high rate; whether similar violations are treated 

similarly across offenders and across the state; whether the mandatory referral of certain 

violations to the parole board for consideration of revocation is a necessary or desirable 

policy; and whether violations might be better confronted with a range of intermediate 

sanctions, as opposed to the simple binary choice of returning to prison or continuation 

on parole. On top of these concerns, policymakers are interested in whether or not the 

current methods of supervision are, in fact, in alignment with the kinds of offenders who 

pose the greatest risk to public safety. In other words, do parole supervision practices 

match offender risks? 

In this chapter, we briefly review the research literature relevant to the topic: “what 

predicts parole violations?” Then we provide a general description of parole violations in 

California, noting the distribution of violations across different types of violations and the 

basic temporal patterns of violations. This section is followed by a discussion of the data 

and methods of analysis we used to examine the causes of different types of parole 

violations. Then we describe the findings of our multivariate analysis, focusing on the 

role of individual, organizational, and community factors in predicting violations. A short 

conclusion summarizes the chapter and provides a prelude to our analysis of revocations. 

65


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
PAST RESEARCH ON PAROLE VIOLATIONS: INDIVIDUAL, COMMUNITY,


AND ORGANIZATION FACTORS 

There are several research literatures that provide some insight into the question “what 

predicts violations?” To start, there is a decades-old literature on parole prediction 

instruments. Such instruments have been used in American parole since the 1930s to 

forecast the likelihood of recidivism among parolees (see review in Harcourt 2007). 

Prediction instruments typically rely on a range of predictors, from “static” factors, like 

personal characteristics (i.e., age, race, gender) and past and current criminal offending 

experiences, as well as “dynamic” factors like substance abuse, mental health problems, 

cognitive orientations favorable to offending, employment, and marital status.

51 Such 

factors have emerged as the lynchpins of conventional wisdom about what predicts parole 

violations, especially criminal violations. The static factors inform the selection of the 

individual-level variables we employ below.

52 

However, there is reason to suspect that individual factors are not the only relevant 

considerations in an analysis of violations. Criminologists have long devoted attention to 

the community dynamics that shape the emergence of criminal behavior, and thus point 

to the importance of the community environment a parolee returns to as a potential factor 

shaping violations. The “social disorganization” perspective is the oldest and most 

consistently supported approach (Bursik and Grasmick 1993, Sampson, Raudenbush, and 

Earls 1997, Shaw and McKay 1942). This perspective focuses on three dimensions of 

communities that lead to a weakening of informal social control and, in theory, an 

increase in criminal activity: residential turnover, ethnic heterogeneity, and poverty. High 

levels of residential turnover, ethnic heterogeneity, and economic disadvantage combine 

to produce a “criminogenic” environment which both increases the attractiveness of 

involvement in criminal behavior and reduces the chances that neighborhood residents 

will work collaboratively to manage the deviant behavior of its members through 

informal social controls. While no study has explicitly tested this idea on parolees, 

Kubrin and Stewart (2006) recently found economic disadvantage, one of the three key 

measures of social disorganization theory, to be correlated with the risk of parolee 

recidivism in Multnomah County, Oregon. 

However, attention to the criminogenic aspects of communities needs to be balanced with 

attention to aspects of communities that may actually aid parolee reintegration. 

Institutional buffers against the anomic conditions—the absence of strong common 

values in a community—produced by economic marginality and stress is a central theme 

of criminologists Messner and Rosenfeld’s (1994) institutional anomie theory. Moreover, 

the focus on developing community-level activities and partnerships to support reentry 

has become a major thrust of recent work in the practitioner literature in community 

For a description of a current application of this practice, see literature related to the Proactive 

Community Supervision model (Sachwald, Eley and Taxman 2006; Taxman, Yancey and Bilanin 2006). 

52 Beyond mental health designations, the CDCR did not capture other data relevant to assessing dynamic 

risk factors during the period of our study. 

66


51 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
corrections (Petersilia 2003; Taxman et al. 2002). But there is little empirical research 

that specifically addresses whether communities with more abundant social supports 

experience better success with parolees than those with fewer supports. Below we 

examine whether violation risks are lower for parolees residing in communities that are 

richer in social services (e.g, welfare, substance abuse, and mental health treatment), have 

stronger religious institutions, and whose residents have expressed greater support for 

prisoner rehabilitation ballot measures. 

In addition to individual risk factors and community conditions, the ways that the 

institution of parole is organized may shape the violations process. Research on 

supervision practices has convincingly shown that the more intensively parolees are 

supervised, the more likely they will be cited for violating parole. Petersilia and Turner’s 

(1992) research on the Intensive Supervision Program (ISP) experiments revealed that 

parolees given intensive supervision, but little by way of services and treatment, 

generated the highest rates of violations. The general lesson was that the more closely 

parolees are watched, the more misbehavior will be detected. The broader implication for 

our study is that there may, in fact, be aspects of how supervision is organized that lead to 

lower or higher violation risk. Building on the ISP research, in the present study we 

measure the supervision categories into which parolees are placed and thereby estimate 

the effects of greater or lesser supervision intensity on violations, holding constant the 

risk factors described above. 

53 

We also explore other organizational aspects of the supervision system, such as variation 

in parole agent caseloads, posing the question: All other things being equal, do parolees 

assigned to agents with higher caseloads have lower rates of reported violations? In 

addition, a common conclusion of qualitative research on parole agents suggests that 

agents vary in terms of the amount of tolerance they show for less serious violations. This 

argument was also given by the CDCR parole agents and officials with whom we 

discussed the research, who told us that agents that are older and who have not worked in 

the prison system as guards are more likely to see “shades of gray,” and thus tolerate 

some parolee behavior that other agents would violate. Along these same lines we were 

also told by parole officials that Region 3 (i.e., Los Angeles County) was more tolerant of 

parole violations because they “have bigger fish to fry” and are so overburdened by the 

sheer scale and concentration of the parole population that they pay less attention to 

minor violations. The crux of these arguments is the idea that the chance that a parolee 

53 Similarly, the individual risk factors measured in the parole prediction instruments discussed above often 

emerge as salient factors in how officials determine how blameworthy a particular offender is, as well as 

the level of risk a particular offender poses to public safety. This implies that some attributes and 

background experiences of offenders, such as whether they have been convicted of a violent or sexual 

offense, or have a history of mental problems, might cause an agent to intensify supervision. That agents 

put certain categories of offenders “on a shorter leash” is clear from the qualitative research on parole 

agents (Lynch 2000). The implication is that the categories of “violent offender,” “sex offender,” or 

“offender with mental illness” are not merely reflections of the inherent risk an offender poses to violate, 

they are also measures of the intensity of supervision. The interaction between agents conceptions of who is 

risky, how they supervise such persons differently, and the actual inherent risk a parolee possess is not 

typically recognized in parole prediction research. Moreover, it is impossible to definitively say whether a 

given parole violation resulted more from a parolee’s inherent risk or whether it resulted from the fact that 

they were watched more closely and given less tolerance. This issue is discussed further below. 

67


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
will be violated may depend upon agent characteristics and the region that they happen to 

reside in. 

VIOLATIONS: PATTERNS AND PROCESSES 

Before discussing the factors that affect the risk of violations, it is important to describe 

some of the data we collected on different types of violations. Data on violations were 

culled from three CDCR databases. The Statewide Parolee Database (SPDB) captures 

violations recorded by parole agents and includes many violations that were not 

subsequently recommended for a revocation hearing. SPDB provides information on the 

timing of violations, as well as violation seriousness. The Revocation Scheduling and 

Tracking System (RSTS) is a jointly managed data system used by the CDCR parole 

division and the parole board to track revocation cases. It contains every violation that the 

board considers for revocation and includes details about all of the violations a parolee is 

alleged to have committed. The third data system is the Offender Based Information 

System, which records parole absconding in its data warehouse known as PALTERMS. 

PALTERMS records when parolees abscond, as well as when they resurface. A 

comprehensive picture of violations was only possible by merging information from all 

three systems. 

During 2003 and 2004 there were 254,468 individuals under parole supervision. These 

parolees were responsible for 296,958 violations. Forty-nine percent of parolees violated 

parole during 2003 and 2004 at least once and 24 percent had multiple instances of parole 

violation. CDCR tracks 247 different types of prohibited parolee behavior, ranging from 

violations of the parole process, usually referred to as “technical violations,” which 

involve failure to report to your parole agent or having access to weapons, to serious and 

violent criminal offenses like robbery, assault with deadly weapons, and homicide. 

Violations can be aggregated into the categories listed in Table 5.1. Technical violations 

include noncriminal administrative violations of the parole process. Two-thirds of 

technical violations were for absconding. The others include weapons access, 

psychological endangerment, and various violations of the parole process, such as 

violations of special conditions of parole imposed by a parole agent or deputy 

commissioner, failure to report to the parole division, failure to follow parole agent 

instructions, and failure to attend an outpatient clinic for mental health services. Criminal 

violations can be subdivided into three levels of seriousness. Type I criminal violations 

are the most frequent of all violations and consist of the least serious behaviors, which 

includes drug possession, drug use, and miscellaneous violations of law—the most 

common of which are “failure to register under the Health and Safety code 11590” 

(controlled substance offender registration), “under the influence of a controlled 

substance,” “false identification to a police officer,” and “driving with a suspended 

license.” Forty-five percent of Type I criminal violations involve methamphetamine use 

or possession, not including possession for sale. Another 20 percent are for possession 

and use of cocaine and another eight percent are for possession and use of heroin. 

Combined methamphetamine, heroin, and cocaine use and possession make up 75 

percent of Type I criminal offenses, 44 percent of criminal violations, and 29 percent of 

68


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
all violations. As a whole, Type I criminal offenses constitute 40 percent of all violations 

and 60 percent of criminal violations. 

Table 5.1. Violations by Type, 2003 and 2004 

Violation Category Description Frequency Percent 

Total Violations All noncriminal and criminal behavior 

resulting in a law enforcement/parole 

agent arrest or a parole violation report 

Technical Violations Violations that are not criminal in 

nature, stemming instead from violations 

of the conditions of parole 

Absconding Escape from parole supervision 

Other Technical Violations Includes psychological endangerment, 

weapons access and failure to report or 

comply with parole conditions, such as 

changing residences without notification, 

travel beyond 50 miles from residence, 

failure to report to parole agent, to 

follow instructions, to attend mental 

health services. 

Criminal Violations Behavior alleged to violate California 

Penal Code. 

Type I—Least Serious Drug use, possession, and miscellaneous 

violations of law, including failure to 

register as per health and safety code 

11590 (controlled substance offender 

registry), false identification to a police 

officer, under the influence of controlled 

substance, driving with a suspended 

license, drunk in public, etc. 

Type II—Moderately Serious Sale and possession for sale of 

controlled substance, battery without 

serious injury, petty theft, 2nd degree 

burglary (noninhabited building), failure 

to register as per 290, resisting arrest, 

other nonviolent crimes, etc. 

Type II—Sexual Violations Failure to register under the sex offender 

registry law, consensual sexual behavior 

in jail, indecent exposure, statutory rape, 

pimping/pandering, and other nonaggressive sexual offenses. not involving 

minors 

Type III—Most Serious Robbery, 1st degree burglary, battery of 

spouse or child, criminal threats, murder, 

rape, etc. 

Type III—Violent Violations Murder, rape, aggravated assault, and 

296,958 

103,524 

68,824 

34,700 

100% 

35% 

23% 

12% 

193,434 

115,838 

65% 

39% 

48,692 16% 

3,380 1% 

28,904 

13,152 

10% 

4% 

69


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
robbery 

Type III—Sexual Violations	 Rape, attempted rape, child molestation, 1,094 .3% 

and sexual assaults. 

Type II criminal violations include theft and forgery, miscellaneous non-violent crimes, 

minor drug sales/trafficking, burglary, minor assault and battery, and sexual offenses not 

involving rape or sexual assault. Type II violations are 25.2 percent of criminal violations 

and 16.4 percent of all violations. Type III violations include homicide, robbery, rape and 

sexual assaults, major battery and assault, major burglary, major drug violations, major 

driving violations, and miscellaneous violent crimes. Type III violations are 14.9 percent 

of criminal violations and 9.7 percent of all violations. “Violent” is a category we devised 

to approximate the Uniform Crime Reports, Part I Violent Crimes, which include 

homicide, robbery, aggravated assaults, and forcible rape. Violent violations are 6.8 

percent of criminal violations and 4.4 percent of all violations. “Sexual violations” 

include Type II offenses, such as “Failure to Register per Penal Code Section 290” 

(California’s sex offender registry), consensual sexual behavior in jail, indecent exposure, 

statutory rape, pimping/pandering, and other non-aggressive sexual offenses not 

involving minors. Eighty-four percent of Type II sexual violations are for “Failure to 

Register.” Putting aside the “Failure to Register” violations, Type II Sexual Violations 

are 0.3 percent of criminal violations and 0.2 percent of all violations. Type III sexual 

violations include rape, attempted rape, child molestation, and sexual assaults. While 

very serious violations they are extremely rare. Type III Sexual Violations are 0.6 percent 

of criminal violations and 0.4 percent of all violations. 

The Timing of Parole Violations 

The risk of all kinds of violations is most intense during the first 180 days after release 

from prison, and declines thereafter. The reason the risk falls is that the most risk-prone 

parolees tend to be violated earlier and returned to custody. The remainder are more 

compliant, less likely to violate, and more likely to successfully complete their parole 

period. Indeed, after 360 days on parole, a surviving parolee’s risk of violation has 

dropped 70 percent from what it was during the first two months of parole. From 360 to 

900 days, a parolee’s risk will only drop another ten percent. In other words, after about 

360 days, a parole’s risk of violation—while not zero—has substantially leveled off. 

Table 5.2 presents parolee failure estimates based upon our data and illustrated with a 

hypothetical sample of 1,000 parolees. 

70


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 5.2: Failure within Selected Time Periods (per 1,000 parolees) 

Technical Type I 

Violations Criminal 

not Violations 

Days Since Any involving (Least Violent Sexual 

Release Violation Absconding Absconding Serious) Violations Violations 

0 to 10 45 9 10 20 1 0 

10 to 90 272 35 92 118 12 6 

90 to 180 170 29 58 92 13 4 

180 to 270 96 22 36 61 10 3 

270 to 360 62 18 24 44 8 2 

360 to 450 45 15 21 34 7 2 

450 to 540 33 13 16 28 6 2 

540 to 630 26 12 14 23 6 2 

630 to 720 21 11 12 19 4 1 

By day 720, or the end of the second year on parole, a total 770 parolees of the original 

1,000 will have experienced at least one violation. 440 of those will be for the Type I 

criminal violations—the least serious criminal violations, mostly consisting of drug use 

and possession. 283 parolees will have absconded. 165 will have a technical violation. 

Considerably rarer than these are violent and sexual violations. Only 67 of the parolees 

will have a violent violation, and twenty two will have a sexual violation (either Type II 

or Type III severity). 

Below we consider how the risk of violation varies across agents, units, neighborhoods, 

and counties. We discussed the individual, organizational, and community factors that we 

investigate previously in Chapters 2, 3, and 4. The specific measures of these factors are 

summarized in Appendix A. However, before turning to a discussion of how and why 

parole violations vary across individuals, organizational units, and communities, we 

briefly discuss the statistical approach and the terminology we use to convey our results. 

METHODOLOGY: COX MODELS OF PAROLE VIOLATIONS 

To examine the factors that influence parole violations we use a multivariate regression 

technique called survival analysis. There are several different types of survival models 

(Allison 1995). We use the Cox regression model, which is named for the English 

statistician Sir David Cox, and which combines a proportional hazards model with partial 

likelihood estimation (Cox 1972). Given the nature of our data, the fact that violations are 

repeatable events, that the risk of a violation is continuous rather than experienced only in 

discrete time periods, and given the left truncation in our data, Cox models are the most 

appropriate statistical technique. In fact, Cox models have become a standard approach in 

studies of recidivism and parolee behavior (e.g., Benda, Toombs, and Peacock 2002; 

DeJong 1997; Langton 2006; Hepburn and Albonetti 1994).

54 

54 For further information on Cox models and their interpretation, see Allison (1995) and Singer and Willett (2003).

71


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
MULTIVARIATE RESULTS: WHAT PREDICTS PAROLE VIOLATIONS? 

This section describes the results of our multivariate survival models predicting various 

types of parole violations. Detailed model results can be found in Appendices B 

(technical and criminal violations) and C (sexual violations). 

Offending History 

The best predictors of parole violations are an offender’s past and present offending 

experiences, which is consistent with existing research (Beck 1997, Langan and Levin 

2002). The single biggest predictor of violations is the number of prior California adult 

prison incarcerations. This effect is nonlinear, indicating that the biggest impact of 

returns to prison comes after the first, second, and third releases. The effect diminishes 

slightly with each additional incarceration and release. In other words, for all violations, 

an offender coming out on their second release from prison has 20 percent higher risk of 

violation than an offender on their first release. An offender on their third release has a 39 

percent higher risk of violation than an offender on their first release and an offender on 

there fourth release has a 56 percent higher risk of violation than an offender on their first 

release. By the ninth release, an offender has a 124 percent higher risk of violation than 

an offender on their first release (Figure 5.1). 

Figure 5.1: The effect of prior prison incarcerations on violation risk 

0 

50 

100 

150 

200 

250 

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 

Number of Returns 

% 

Differe

n

ce in 

Risk 

C

o

m

p

ared to 1st

R

ele

a

s

es 

All Violations 

Technicals Violations 

Criminal Violations 

Additionally, the effect of prior commitments varies across different violation types. 

Technical violations, including absconding, weapons access, psychological 

endangerment, and other violations of the parole process, are more greatly affected by the 

72


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
prior returns to prison than criminal violations. In other words, the relative increase in 

risk associated with each additional adult prison term is greater for technical violations 

than criminal violations. Both types of violations manifest evidence of the effects of prior 

incarceration, the effect is just greater for technical violations. Whether the effect is due 

to increased supervision, a criminogenic effect of repeat incarceration, a cognitive or 

behavioral proclivity on the part of parolees, or a combination of these factors, is 

impossible to say with the available data. 

Age at first adult commitment to California prison is a common component of risk 

assessment instruments and, as a measure of early onset of a criminal career, is thought to 

be a powerful predictor of future criminality. Here we find that it does indeed predict the 

most serious Type III criminal violations. For every additional year older a parolee was at 

their first commitment, their risk of a Type III violation decreases by 2.5 percent. 

However, we also find that parolees who are older when they are first committed to 

California prisons tend to have more technical violations and Type I criminal violations. 

For every additional year older a parolee was at their first commitment their risk of 

technical and Type I criminal violations increases by 1.6 to 1.9 percent. There is no age 

at first commitment effect on moderately serious Type II criminal violations. The 

differences across the violation types may be the result of differences in the offending 

careers who individuals who enter the prison system earlier rather than later in life. 

Offenders with younger ages of first (adult) commitment to prison may be more likely to 

have careers characterized by serious offenses whereas those first committed at older 

ages may tend to commit less serious offenses, which take longer to accumulate to the 

extent that would warrant a prison sentence. However, on average, they have either less 

serious offense histories, or more slowly cumulating careers, resulting in later first adult 

commitments to prison. The latter group is probably largely composed of drug offenders 

that have substance dependence issues that drive their offending, and as a result of drug 

use, are prone to generating technical and Type I criminal violations, but are less likely to 

be involved in more serious criminal behavior. While we control for some aspects of 

parolees’ criminal histories, more detailed criminal career data is necessary to unpack the 

precise reasons for the relationship we observe. 

Commitment offense, which is the most serious offense of the most recent term for which 

an offender was committed to the state prison system, is a critical factor in several legal 

and parole policy matters. For example, commitment offense is used to determine the 

supervision category into which an offender is placed, including whether they are placed 

on a specialized caseload; it affects which types of offenders’ violations constitute 

mandatory referrals to the parole board; it affects whether or not a parolee can participate 

in certain rehabilitative programs, and when the parole can be reviewed for discharge 

from parole. 

However, commitment offense does not predict violations in the ways that many 

policymakers and parole policies assume. While parolees committed for violent and 

sexual offenses are often believed to pose the greatest recidivism risk, our analyses show 

that parolees with drug and property commitment offenses pose much greater risks to 

violate than parolees with violent or sexual commitment offenses (See Tables 5.3, 5.4, 

and 5.5). An offender with a violent commitment offense has a 26 percent lower risk of 

73


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
all kinds of violations than an offender with a drug commitment offense. Parolees with 

violent commitment offenses pose no greater risk than drug offenders to be cited for nonPAL technical violations, and pose 20 percent lower risk to be cited for absconding. They 

have 43 percent lower risk for Type I criminal violations and they have no lower or 

higher risks for moderately serious (Type II) criminal violations and the most serious 

(Type III) criminal violations. The only type of violation parolees with violent 

commitment offenses are at greater risk for are UCR Part I violent crimes (homicide, 

aggravated assault, rape, and robbery), which are very rare, constituting only 4.4 percent 

of all violations. 

Table 5.3: Relative Risk for Parole Violations, by Commitment Offense 

Technical 

violation (not 

Compared to drug Criminal incl. 

offenders Any violation violation Absconding) Absconding 

Property offenders No additional No additional risk 26% more risk No additional 

pose: risk risk 

Violent offenders 26% less risk 32% less risk No additional 20% less risk 

pose: risk 

Sex offenders pose:

55 37% less risk 47% less risk No additional 35% less risk 

risk 

"Other" offenders 15% less risk 18% less risk No additional 18% less risk 

pose: risk 

Table 5.4: Relative Risk for Criminal Parole Violations, by Commitment Offense 

Least serious Moderately Most serious 

(Type I) serious (Type (Type III) Violent 

criminal II) criminal criminal criminal 

Compared to drug offenders violations violations violations violations 

Property offenders pose: 18% less risk 38% more risk No additional 39% more risk 

risk 

Violent offenders pose: 43% less risk No additional No additional 46% more risk 

risk risk 

Sex offenders pose: 57% less risk No additional No additional No additional 

risk risk risk 

"Other" offenders pose: 30% less risk No additional No additional No additional 

risk risk risk 

55 “Sex offender”—indicating most recent prison commitment for a sexual offense—should not be confused with

“registered sex offender”—which indicates prior conviction for a more limited list of serious sexual crimes.

74 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 5.5: Relative Risk for Sexual Parole Violations, by Commitment Offense 

Most serious (Type III) sexual 

Compared to drug offenders Sexual criminal violations criminal violations 

Property offenders pose: 16% more risk No additional risk 

Violent offenders pose: No additional risk 29% more risk 

Sex offenders pose: 24% less risk No additional risk 

"Other" offenders pose: No additional risk 35% more risk 

Other indicators of offender seriousness are also related to violation risk, although not in 

the manner that many policymakers and parole policies assume (See Tables 5.6, 5.7, and 

5.8). Parolees with past commitments for “violent” criminal offenses, as defined by 

California Penal Code 667.5, do not have greater risks for moderately serious (Type II) 

criminal violations, the most serious (Type III) criminal violations, or UCR Part I violent 

violations. Parolees with one or more violent offenses are, however, more at risk for 

absconding. Second Strikers—offenders with two strikes under California Three Strikes 

law—have similar risks. They have a ten percent lower risk of any violation than nonSecond Strikers, 11 percent lower risk for Type I criminal violations, and the same risk 

for technical violations, Type II and III criminal violations, and UCR Part I violent 

violations as non-Second Strikers. 

Table 5.6: Relative Risk for Parole Violations, by Indicators of Offender Seriousness 

Technical 

violations 

Each “violent” prior 

conviction adds: 

Any 

violations 

3% more risk 

(not 

including 

Absconding) 

No additional 

risk 

Absconding 

7% more risk 

Criminal 

violations 

No additional 

risk 

Parolees on their “second 10% less risk No additional No additional 9% less risk 

strike” pose: risk risk 

Registered sex offenders 

pose: 

18% less risk No additional 

risk 

29% less risk 16% less risk 

Sex offender registrants and offenders with sexual commitment offenses also pose 

significantly lower violation risks for violations than non-sex offenders for several types 

of violations. Sex offender registrants have 18 percent less risk for any violation than 

non-registrants. They have 29 percent lower risk than other offenders for absconding, and 

40 percent lower risk of Type I criminal violations. Sex offender registrants have no 

higher risks than other offenders of technical violations not involving absconding, and the 

most serious Type III criminal violations; They do have a higher risk for Type II criminal 

violations; however, 85 percent of Type II sexual violations are for “Failing to Register 

under California Penal Code section 290,” the sex offender registration requirement. Sex 

75


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
offender registrants are no more likely to commit the most violent violations than other 

offenders. 

Table 5.7: Relative Risk for Criminal Parole Violations, by Indicators of Offender 

Seriousness 

Least serious Moderately Most serious 

(Type I) serious (Type (Type III) Violent 

criminal II) criminal criminal criminal 

violations violations violations violations 

Each “violent” prior adds: No additional No additional No additional No additional 

risk risk risk risk 

Parolees on their “second 11% less risk No additional No additional No additional 

strike” pose: risk risk risk 

Registered sex offenders 40% less risk 67% more risk No additional No additional 

pose: risk risk 

Table 5.8: Relative Risk for Sexual Parole Violations, by Indicators of Offender 

Seriousness 

Most serious (Type III) sexual 

Sexual criminal violations criminal violations 

Each “violent” prior adds: No additional risk No additional risk 

Parolees on their “second No additional risk No additional risk 

strike” pose: 

Registered sex offenders 2,421% more risk 188% more risk 

pose: 

Sexual violations are very rare, constituting 1.5 percent of all violations, and about twothirds of them are victimless offenses by sex offenders for failing to register under 

California Penal Code section 290, as discussed above. Also, the majority of sexual 

violations, including the most serious violations involving rape, sexual assault, and child 

molestation, are done by parolees who are not registered sex offenders. Setting aside the 

failure to register violations (which are only relevant to sex offender registrants), of the 

1,528 sexual violations committed during 2003 and 2004, only 25 percent were 

committed by sex offender registrants. The vast majority of sexual violations, including 

78 percent of the most serious Type III sexual violations, are committed by non-sex 

offender registrants. The implication is that even if all sex offenders were rendered 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
completely incapable of committing sexual offenses, the percentage of sexual violations 

committed by parolees would only drop 22 percent. 

Sexual violations are rare events and the population of registered sex offenders is fairly 

small. (Registered sex offenders only comprise about 8 percent of the parolees in our 

data.) Nonetheless, our multivariate analyses show that sex offender registrants do, in 

fact, pose significantly higher risks of sexually-oriented violations, especially the most 

serious types of violations. Specifically, they have a nearly three and half times higher 

risk of the most serious Type III Sexual violations than parolees who are not sex offender 

registrants. 

A parolee’s offending history is an important predictor of violations. Moreover, of the 

different facets of a parolee’s offending background, the most important is the sheer 

number of returns to prison a parolee has experienced as an adult. Parolees with more 

repeat visits to prison have increased risks for violations of all kinds. A second key 

finding about parolee background is that the emphasis placed by policy and statute on 

commitment offense and the various offense flags, such as serious and violent, sex 

offender, and second striker, is not particularly useful for identifying parolees with 

greater risks to violate. Offenders with violent or sexual commitment offenses, or with 

flags for past violent or sexual offenses, generally do not pose greater risks to public 

safety than other kinds of offenders. The only exceptions are that parolees with a violent 

commitment offense have higher risks of the most violent, but fortunately rarest, violent 

crimes involving homicide, rape, robbery, and aggravated assault, and parolees who are 

sex offender registrants have higher risks of the most serious, but again rare, sexual 

violations. 

Personal Characteristics 

Several personal characteristics of adult parolees affect their risk of violations (See 

Tables 5.9 and 5.10). Younger parolees, aged 18-30, pose the greatest risk of all kinds of 

violations, except the least serious Type I criminal violations. Compared with parolees 

aged 31 to 45, parolees aged 18-30 have 28 percent higher risk of absconding and 53 

percent higher risk of other technical violations not involving absconding. They have 29 

percent higher risk of the moderately serious Type II criminal violations and 42 percent 

higher risk for violent violations involving homicide, rape, robbery, and serious assault. 

Older parolees, over age 45, pose the lowest risk of all kinds of violations. 

Male parolees pose significantly higher risk for all types of violations except absconding. 

The effect of gender is most pronounced in the most serious and violent criminal 

violations. Compared to females, males have 66 percent higher risk of the moderately 

serious Type II criminal violations, 128 percent higher risk for the most serious Type III 

criminal violations, and 166 percent higher risk for violent violations involving homicide, 

rape, robbery, and serious assault. Also, not surprisingly, males are more than 25 times 

more likely to commit a serious Type III sexual violation. 

Table 5.9: Relative Risk for Parole Violations, by Parolees’ Personal Characteristics 

77


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Technical 

violations 

(not 

Any including Criminal 

violations Absconding) Absconding violations 

Compared to parolees aged 24% more risk 53% more risk 28% more risk 20% more risk 

31-44, those aged 18-30 

(the youngest) pose: 

Compared to parolees aged 26% less risk 36% less risk 24% less risk 27% less risk 

31-44, parolees aged 45 

and above (the oldest) 

pose: 

Compared to female 26% more risk 42% more risk No additional 33% more risk 

parolees, male parolees risk 

pose: 

Compared to non-black No additional No additional No additional No additional 

parolees, black parolees risk risk risk risk 

pose: 

Compared to parolees 36% more risk 70% more risk 41% more risk 32% more risk 

without documented 

mental health problems, 

those with such problems 

pose: 

Black parolees pose the same risks as nonblack parolees for technical violations. 

Compared to all other racial groups, blacks have 11 percent lower risk for the least 

serious Type I criminal violations, suggesting that controlling for other factors black 

parolees are less likely to be cited for drug use and possession violations. However, they 

have 19 percent higher risk for Type II criminal violations, 36 percent higher risk of the 

most serious Type III criminal violations, and 43 percent higher risk of violent violations. 

In other words, black parolees pose much greater risks than parolees with other racial 

backgrounds for most serious and violent violations. 

Parolees with a record of mental health problems have higher risks for all violations and 

they have particularly elevated risks for the most violent criminal violations and the 

technical violations. Individuals who are designated as “CCCMS” (Correctional Clinical 

Case Management Services) and “EOP” (Enhanced Outpatient), which are different 

levels of mental health services, have 36 percent higher risk of all kinds of violations. 

They have 41 percent higher risk of absconding, 70 percent higher risk of technical 

violations other than absconding, 32 percent higher risk of criminal violations, and 52 

percent higher risk of the most serious violent violations. These findings highlight the 

78


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
difficulties faced by parolees with mental issues in adjusting to supervision and to the 

community environment.

56 

Table 5.10: Relative Risk for Criminal Parole Violations, by Parolees’ Personal 

Characteristics 

Most 

Least Moderatel Most serious 

serious y serious serious (Type III) 

(Type I) (Type II) (Type III) Violent Sexual sexual 

criminal criminal criminal criminal criminal criminal 

violations violations violations violations violations violations 

Compared to parolees No 29% more No 42% more 92% more 50% more 

aged 31-44, those additional risk additional risk risk risk 

aged 18-30 (the risk risk 

youngest) pose: 

Compared to parolees 29% less No 40% less 48% less 42% less 38% less 

aged 31-44, parolees risk additional risk risk risk risk 

aged 45 and above risk 

(the oldest) pose: 

Compared to female 14% more 66% more 128% 166% 310% 2,689% 

parolees, male risk risk more risk more risk more risk more risk 

parolees pose: 

Compared to non­ 10% less 19% more 36% more 43% more 56% more 54% more 

black parolees, black risk risk risk risk risk risk 

parolees pose: 

56 Our qualitative field research indicates that parole agents treat parolees with mental illness differently 

than others. Specifically, because mentally ill parolees are perceived to be more unpredictable and because 

the standards for their revocation are broader, parole agents appear to have less tolerance for their 

violations. In an excellent review of the multiplicity of issues mentally ill prisoners face within CDCR, 

David Ball (2007) notes that while some of California’s programs have shown promising results for the 

mentally ill parolees, such programs fail to reach many offenders who need them. Mentally ill parolees 

often return home without the needed medication, treatment, and supervision required to reduce their 

recidivism. He writes that “too many mentally ill parolees are returning to prison, and too many of those 

are returning for reasons unrelated to the commission of new crimes.” (2007:25). As Ball explains, parolees 

can obviously be sent back to prison for committing new crimes, but those who decompensate to the point 

where their illness is acute can also have their parole revoked: as the standard form for conditions of parole 

states, “When the Board of Prison Terms determinates, based upon psychiatric reasons, that you pose a 

danger to yourself or others, the Board may, if necessary for psychiatric treatment, order your placement in 

a community treatment facility or state prison or may revoke your parole and order your return to prison.” 

(California State Prisoners Handbook, at app. 10-A (Supp. 2004). Parole officers are required to report to 

the Parole Board if a parolee’s mental condition deteriorates “such that the parolee is likely to engage in 

future criminal behavior.” Cal.Code Regs. Tit. 15 §2605© (2006). As Ball notes, “parolees must then be 

returned to prison upon a finding of future criminal behavior. Finally, parolees an be returned to prison if 

they have a mental disorder “which substantially impairs his or her ability to maintain himself or herself in 

the community” and “necessary psychiatric treatment cannot be obtained in the community.” (p. 27). These 

regulations are much broader than those for parolees without mental illness, and importantly include 

predictions about future behavior and are influenced by the lack of available mental health treatment 

services in the community. These factors are likely explaining the empirical results shown in our analysis. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Compared to parolees 26% more 48% more 35% more 52% more 150% 161% 

without documented risk risk risk risk more risk more risk 

mental health 

problems, those with 

such problems pose: 

Personal characteristics like age, gender, race, and mental health status all contribute to 

violation behavior and reporting. While, in general, these findings are consistent with 

prior research on recidivism, it is important to note that the effects of personal 

characteristics can vary quite a bit across violation type. As mentioned above, very little 

research on parole violation and recidivism breaks apart violations in the detailed way we 

do in the present analysis. The impacts of age, race, gender, and mental health status can 

be greater or lesser and can sometimes be in a different direction altogether, depending 

upon whether the outcome of interest is absconding, another technical violation, or a 

more or less serious criminal violation. The next question is: beyond offending history 

and personal characteristics, what other factors affect the risks of violations? 

Supervision 

The second dimension of our tripartite focus on individual, organizational, and 

community predictors of violations includes aspects of the parole supervision system. We 

examined various aspects of supervision, such as how intensively parolees were 

supervised, to see if more intensity led to greater detection or deterrence of violations. 

We also measured the workload of a parolee’s parole agent to see if greater workloads 

led to lower rates of detection and reporting of violations. We compared parolees across 

parole regions to test the departmental folklore that different administrative units have 

different cultures of tolerance relative to parole violations. We explored the effect of 

parole agent characteristics to see whether the race, age, job tenure, or prior employment 

in the prison system had effects on the detection and reporting of violations. And we 

examined whether parole policies announced from headquarters had any impact on 

violations. 

Consistent with prior research (Petersilia and Turner 1992), more intensive supervision 

increases the risk of all violations, holding constant the offender’s personal attributes and 

offense background, as well as their community conditions, and other aspects of 

supervision to which they are subject. The biggest differences in the effects of 

supervision are found in the contrast between active supervision and Minimum 

Supervision. Parolees who are on Minimum Supervision, which involves only one faceto-face or collateral contact every three months, monthly mail correspondence, and no 

narcotics testing, have significantly lower risks of all kinds of violations than parolees 

who a more actively supervised. The differences in risk of violations between active and 

Minimum Supervision parolees are most pronounced among the most discretionary 

violations—technical violations not involving absconding and Type I criminal violations. 

Compared to Minimum Supervision parolees, actively supervised parolees have between 

two and three times the risk of drug use and possession, miscellaneous misdemeanor 

violations of law, and technical violations of the parole process (not including 

80


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
absconding). This is likely the result of the fact that, in addition to having less contact 

with their parole agents, Minimum Supervision parolees are not subjected to many of the 

same demands as other parolees. They do not have extensive parole process requirements 

or special conditions of parole and they are not routinely tested for drugs. As a result, 

they are subject to fewer formal requirements and fewer opportunities to detect and report 

their bad behavior. Thus, they generate fewer technical and drug related criminal 

violations. 

Minimum Supervision parolees also have consistently lower risks of absconding, Type II, 

III, and violent violations, although the difference is not as great as with the more 

discretionary violations discussed above. What is clear from the contrast between active 

and minimum supervision is that more closely supervised parolees are not deterred from 

violations, as many parole officials would like to believe, since the more intensively a 

parolee is supervised the greater their violation risk. 

There is also evidence to suggest that gradients of active supervision matter specifically 

for technical violations. As described in Chapter III, the California parole system has a 

category of supervision called Controlled Service, which represents a medium level of 

supervision and consists of one face-to-face meeting with a parole agent every two 

months, two drug tests per quarter, and one collateral contact every three months. In 

addition, the system has three categories of “high” supervision, called High Control, High 

Services, and High Risk Specialized or non-Specialized caseloads. The latter consist of 

sex offenders, second strikers, gang members, or parolees with serious mental health 

problems. With respect to technical violations, individuals placed into one of the high 

level supervision categories pose consistently higher risks to violate than individuals 

placed in the lower supervision intensity category, Controlled Service. In other words, 

higher gradients of supervision result specifically in more detection of technical 

violations, both absconding and the other technical violations not involving absconding. 

With respect to the criminal violations, the medium level of supervision, Controlled 

Service, have lower risks than the High Control parolees, but is roughly similar to or even 

a bit higher than the risks of parolees who are High Service or High Risk Caseloads. In 

other words, gradients of supervision matter less for the detection and reporting of 

criminal violations. In the analysis of the most serious Type III criminal violations and 

violent violations there is evidence that the High Services parolees actually have risks 

that are not statistically different from Minimum Supervision parolees. This might be 

taken to mean that parolees on High Service caseloads are actually deterred from the 

most serious violations by the type of supervision to which they are subjected. However, 

some caution is warranted given that the statistical significance is inversely correlated 

with both the event frequency and the small numbers of parolees who occupy these 

categories. In other words, there are small numbers of parolees on High Service caseloads 

(.9%), and the Type III and violent events we are trying to predict are rare (only 9.7% of 

total violations). The combination makes it hard to have as much confidence as we do 

about the other findings. However, we can conclude that the other kinds of high 

supervision categories, High Control and High Risk Caseloads, have large and significant 

differences from the Minimum Supervision category. 

81


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Supervision intensity does, in fact, matter for the detection and reporting of violations. 

The biggest impact of intensity is evident when Minimum Supervision and active 

supervision are compared; however, there are also differences between gradations of 

active supervision in the reporting and detection of technical violations. However, 

supervision intensity is only one aspect of the supervision system that may affect 

violations. Next we consider differences across parole regions. 

Regional Differences 

The California parole system is subdivided into four Regions. Region 1 stretches from 

northern to southern California, covering counties in the central valley and on the state’s 

mountainous eastern side. Region 2 includes the Bay Area, as well as coastal counties 

north to the Oregon border and south to Ventura County. Region 3 is entirely composed 

of Los Angeles County, and Region 4 includes counties east of Los Angeles and adjacent 

to San Diego County. Regional differences in parole supervision are part of the folklore 

of the department, and many parole agents identified this issue during the project’s field 

research. The regions are understood to have differences in the types of parolees they 

supervise, the kinds of communities their parolees reside in, and the organizational 

culture of agents and administrators. The uniqueness of Region 3 on these dimensions is 

the most commonly noted difference. There is a perception that Region 3 supervises 

parolees who have more extensive criminal histories and who tend to return to more 

socially disorganized neighborhoods, with more gangs and drugs. Region 3 is also 

perceived within the parole division as the most overstretched and harried part of the 

parole system. As a result, it is believed that a distinctive organizational culture has arisen 

in Region 3 where there is lower reporting of the least serious violations. However, 

having controlled for the differences in the parolee population and the characteristics of 

their communities, we find limited support for the notion that Region 3 differs from the 

other regions in a way that would confirm the importance of the organizational culture 

argument. Region 3 does report fewer drug use and possession violations—the low 

seriousness Type I criminal violations—but agents in Region 3 are the same as those in 

other regions or even higher (compared to Region 2) in their reporting of technical 

violations—both the absconding and the violations of the parole process violations. 

Moreover, the risk that a parolee in Region 3 will be cited for a moderately serious 

criminal Type II violation or the most serious criminal Type III violations is no different 

than other regions. The implication of these findings is that the organizational culture of 

Region 3 is the least important of the differences between regions. What are more 

important are the types of parolees supervised, and the community environments to 

which parolees return, which we have statistically controlled in our models. 

Agent Workload 

There has been much discussion nationally about the desirability of reducing parole agent 

workload, so that they can devote more time each case (Petersilia 2003). While California 

parole agents’ workload is defined in their labor union contract to be no more than 160 

points they routinely have many more points. Points are based on each parolee’s 

supervision level. A Minimum Supervision parole is worth one point. A Controlled 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Service parolee is worth 2 points, and high control and high service parolees are worth 3 

points. High Risk caseloads are set at 40:1 ratio, indicating that each parole is equivalent 

to 4 points. Despite the concern about workload, the amount of points a parole agent 

carries appears to have little impact on parole violation outcomes. We compared parolees 

whose agents have under 160 points with those who carried between 160 and the mean 

(277), and those who carried over 277. These large differences in workload did not lead 

to differences in parolees’ violation risks. Of course, these are essentially comparisons 

across agents, many of whom may find ways of adapting to higher or lower workloads in 

ways that do not affect their violation decisions. The findings should not be used to draw 

inferences about whether increasing or decreasing workload across the board would have 

an effect on violation reports. 

Agent Personal Characteristics 

The ideological orientation of agents toward parole violations has been the focus of much 

of the research literature on parole agents (McCleary 1978, Lynch 2000). Although there 

are several typologies in the literature, parole agents have been described as favoring a 

more social work orientation or a more legalistic orientation. To the extent that parole 

agents bring a social work orientation to their job, they may be expected to prefer 

handling less serious violations informally, using their discretion to avoid initiating the 

revocation process. More legalistically-oriented agents, on the other hand, are expected to 

bring a more “black and white” approach to violations, focusing on finding and officially 

recording each violation. These differences in orientations may not be reflected in the 

handling of every case, but an assessment of aggregate patterns of decision-making may 

reveal some differences. While we do not have data specifically on parole agent attitudes, 

we can explore the degree to which differences in violations are traceable to personal 

characteristics that may be associated with particular kinds of orientations. Female 

agents might be expected, on average, to bring more of social work orientation to their 

jobs. We find that there are gender differences between male and female agents, but only 

with regard to absconding and the least serious Type I Criminal violations. Parolees 

supervised by female agents have 10 percent higher risk of absconding, as compared to 

those supervised by male agents. Parolees supervised by female agents have 11 percent 

lower risk for the least serious Type I criminal violations. This provides some support for 

the notion that female agents tend to exercise discretion in ways that are more forgiving 

toward lower-end drug use violators. Male agents, on the other hand, appear to adopt a 

more lenient approach toward absconding than female agents. No gender differences are 

found in the reporting of the more serious Type II and III criminal violations. 

We also expected that, as a group, black agents might have more tolerance for less 

serious violations. Black agents, like blacks in the rest of American society, are more 

likely to have friends, acquaintances, or family members who have had significant 

contact with the criminal justice system. Thus, we expected that they might be more 

sensitive to the social situations that breed criminal behavior and more suspicious of the 

operation of the criminal justice system, of which they are a part, in delivering justice 

(Wilson and Dunham 2001). Therefore, black agents may exercise their discretion to be 

more lenient, specifically, with regard to less serious violations (i.e., they may ignore 

violations they are aware of). The results bear this argument out. Parolees with black 

83


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
agents have 18 percent lower risk of technical violations not involving absconding and 8 

percent lower risk of the least serious Type I criminal violations than parolees with agents 

who are not black. Parolees with black agents are no different than other parolees in 

terms of their risk of absconding violations, the more serious Type II and III criminal 

violations, or violent criminal violations. 

Many of the parole agents and officials with whom we discussed this research suggested 

that certain types of parole agents were more or less tolerant of parolee behavior. 

Informants told us that parole agents who had previously worked inside of a prison, 

younger parole agents, and those with less job tenure are generally known for their more 

legalistic “black and white” attitude toward violations and, in general, are understood to 

violate quicker and more often than those that have not served inside prisons, older 

agents, and those with longer job tenures. These hypotheses were presented to us as based 

upon parole officials’ practical experiences working in parole, rather than empirically 

validated knowledge about what works in changing parolee behavior. 

We found mixed support for these ideas. For example, parolees with agents who have 

less than three years of job tenure have nine percent higher risk of the least serious Type I 

criminal violations than parolees with agents with between three and ten years job tenure. 

However, parolees assigned to agents with greater than ten years job tenure have the 

same risks as those with less than three years. Thus, with respect to the least serious Type 

I criminal violations, agents with very long job tenure do not appear to differ in the way 

they handle violations from agents with the least amount of job tenure. Moreover, we 

found no other job tenure effects with respect to any other type of criminal or technical 

violations. 

In addition, we did not find support for the effects of having an agent that previously 

worked in a prison. Contrary to expectations, parolees assigned to agents with prior 

employment experience in a prison actually have an eight percent lower risk of the least 

serious Type I criminal violations than parolees assigned to agents with no prior prison 

employment. Prior employment in a prison did not affect any other type of criminal of 

technical violations. Moreover, parole agent age also had no effects on any type of 

criminal or technical violation. 

Parole Policies 

The California parole system is highly decentralized, with 187 parole units operating 

largely independent of one another. Parole units are organized into 23 parole districts that 

oversee various administrative functions. Districts in turn are organized into four parole 

regions. Official policies are instituted from headquarters and typically contain mandates 

for the entire system. The folklore of the department is that “street-level” parole agents 

either pay little attention to policy pronouncements emanating from headquarters or view 

them as attempts to meddle in their decision-making. Two major policies were adopted 

during 2003 and 2004 that may have affected how parole agents handle violations. The 

first related to search and seizure compliance and the second was the announcement of a 

“New Parole Model,” which, among other things, proposed the use of intermediate 

sanctions for parole violators and a violation matrix to standardize the handling of 

84


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
violations. The New Parole Model was a source of major tension between the 

correctional officers union and the department because parole agents felt it reflected a 

reduction in their discretion and a softening of the approach to violations. Agents also 

expressed frustration about the model because it appeared to them to reflect an endemic 

mismanagement of the parole system by CDCR executives—mainly because it 

recommended the use of intermediate sanctions before the programs were actually up and 

running. 

The other policy related to a lawsuit brought in U.S. District Court. The case, U.S. v. 

Crawford (323 F.3d 700 [9th Cir. 2003]), centered on the necessity of parole agent 

compliance with federal search and seizure rules in the case of parolee searches. The 

initial court in Crawford ruled that parolees can only be searched if there is reasonable 

suspicion that they are involved in criminal activity. The case was subsequently 

reconsidered the following year and overturned. During the period when the 9th Circuit 

Court was reconsidering the ruling, the parole division announced a policy that while the 

Crawford decision was pending parole agents were to use a “reasonable suspicion” 

standard as a basis for searches of parolees. This policy altered the longstanding rules 

used in parole that limited appropriate searches to those that were “nonarbitrary, noncapricious, and non-harassing.” Once Crawford was overturned, the parole division 

retracted its policy requiring the higher standard of suspicion, and reverted back to their 

original policy. We hypothesized that this policy might impact the ability of parole agents 

to detect some kinds of criminal violations, particularly Type II and III criminal 

violations. We expected to see the policy have little effect on technical violations and the 

drug-related Type I criminal violations, since neither of these kinds of violations would 

be greatly impacted by changes in search standards. 

Table 5.11. Major Parole Policy Announcements, 2003-2004 

Date Title Info 

2/6/2004 Policies and procedures for the Discusses agreement between 

community correctional reentry CCPOA and state regarding new 

centers/halfway back program parole 

Will u

and D

agreem

model and reentry centers. 

se violation matrix (only US 

A use until workload 

ent reached). Change in 

9/9/2003 Impact of US vs. Crawford regarding 

missio

parole

duties 

Until f

n of CCRCS from inmates to 

e needs. Memo outlines all 

of all players in process. 

inal ruling, P&CSD will 

parole compliance searches perfor

reason

activit

m parole searches based on 

able suspicion of criminal 

y or parole violations. 

7/30/2004 Crawford decision overturned 

Defined here 

Reasonable suspicion not required 

for search and seizure of CA 

parolee. 

85


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Neither policy had the hypothesized effect, which may suggest that policies created at 

headquarters typically have little impact on decision-making and case processing at the 

street-level. 

Despite the weak policy effects, the general implication is that the way supervision is 

organized can impact violations. The most consequential aspect of supervision is clearly 

intensity. More intensively supervised parolees are routinely found to be at greater risk 

for almost all types of violations. However, we also found some evidence to support the 

idea that parole agent tolerance, as measure by their personal characteristics, can 

influence some types of violations, but not typically the most serious kinds. These 

findings call out for a further investigation that uses more precise measures of parole 

agent ideological orientation. Finally, there appears to be little support in our data for the 

effects of workload and policy changes on how parole agents handle violations. 

Next we consider the third dimension of our analytic framework—community factors. 

Community Factors 

The characteristics of communities in which parolees reside form a third aspect of our 

analysis—with individual and organizational factors making up the first two levels. We 

begin with the assumption that community characteristics can have criminogenic or 

reintegrative impacts on parolee behavior. In other words, neighborhood factors can 

either promote or guard against illicit activities. Following this logic, we substantively 

divide community characteristics into two subcategories—criminogenic contexts and 

reentry environments. 

Criminogenic contexts refer to neighborhood factors that foster an environment that is 

more conducive to crime and illicit activity. We derive these factors from social 

disorganization theory, which argues that certain neighborhood conditions facilitate 

criminal activity through the breakdown of local social controls (Shaw and McKay 1942; 

Sampson, Raudenbush, and Earls 1997). According to this approach, the critical sources 

of disorganization are concentrated socioeconomic disadvantage, ethnic heterogeneity 

and residential turnover. Concentrated disadvantage affects crime through the inability of 

communities to invest in appropriate community control measures. Ethnic heterogeneity 

(i.e., diversity) is thought to foster isolation among different ethnic groups, thereby 

creating an atmosphere of difference and conflict. Residential turnover is associated with 

crime because residents are thought to invest less in neighborhoods where they do not 

plan to establish permanent or long-term residence. 

We find modest support for the criminogenic contexts/social disorganization hypotheses 

as they relate to an understanding of parole violations in California. Concentrated 

disadvantage is a combined factor measure that accounts for the following community 

characteristics: percent of households in poverty, percent of adults who are unemployed, 

median household income, percent of children living with unmarried parents and percent 

of residents who are black. Parolees who live in neighborhoods that score highly on 

concentrated disadvantage are at greater risk to abscond than parolees who live in less 

disadvantaged environments. However, parolees residing disadvantaged neighborhoods 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
do not pose a greater risk to commit other kinds of violations than those from less 

disadvantaged neighborhoods. Parolees who live in neighborhoods characterized by high 

residential turnover have greater risks of technical violations other than absconding (i.e., 

violations of the parole process and weapons access). However, there is no effect of 

social disorganization variables on any other kind of criminal violations. Thus, support 

for the notion that parolees in more socially disorganized communities are more crimeprone is not consistently supported by these analyses. 

The effects of reentry environments are similarly rather weak. Neither public assistance 

generosity, measured as a ratio of public assistance expenditures to public assistance 

recipients, nor the percent of the population who are church adherents have any effect on 

any type of technical or criminal violations. Punitiveness, as measured by voting results 

on correctional ballot measures and the percent republican in a community, decreases the 

risk of absconding, but does not affect any other type of technical or criminal violation. 

This finding is actually the opposite of what we had hypothesized. 

The availability of substance abuse and mental health (SAMSHA) services affects both 

the risk of technical violations and the least serious Type I criminal violations. This 

suggests that parolees situated in more “resource rich” environments have lower risks of 

technical violations (not including absconding), as well as drug use and possession 

violations. This may be partly attributable to the effectiveness of these programs with 

respect to curtailing lower seriousness violations, but it may also be a “parole agent 

effect,” such that parole agents are less likely to violate parolees for lower level 

violations when they perceive that there are service opportunities that pose an alternative 

to initiating the formal violation and revocation process. The effects of the concentration 

of SAMSHA services is not present in the analyses of the other types of technical and 

criminal violations. 

SUMMARY OF VIOLATIONS ANALYSIS 

Although we began our investigation with a set of hypotheses about the individual, 

organizational, and community factors affecting parole violations, our findings indicate 

that individual and organizational factors are the most critical. Individual characteristics, 

such as prior offending history, matter a lot, but mainly in terms of the frequency of 

offending—the number of times an offender has been incarcerated. The type of offender 

also matters, although not in ways many people presume. Offenders who have committed 

serious or violent offenses or are sexual offenders generally pose less risk than drug and 

property offenders. The current laws and policies in California focus heavily on violent 

and sex offenders and thus our results suggest that such attention may be misplaced—if 

the goal is to reduce recidivism. These categories are used to determine how parolees are 

supervised, what programs they can access, and what will happen to the parolee if they 

violate parole. These policies rely on a set of designations that mark particular categories 

of offenders as “sex offender registrants,” “Second Strikers,” and “serious” and “violent” 

offenders. Arguably, these categories serve dual purposes. On the one hand, the 

categories are meant to identify individuals who are the least deserving of leniency and 

“the benefit of the doubt” both formally and informally in the parole supervision and 

revocation system. They are, in effect, categories through which the “just deserts” aspect 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
of punishment is extended into and enacted during parole supervision phase of a felon’s 

sanction. On the other hand, they are frequently understood to designate individuals who, 

by virtue of their past behavior, pose elevated threats to the public safety. In regards to 

this latter point, our research shows that these categories do not function well as 

indicators of the potential for future deviant behavior. 

These findings reveal that the heavy emphasis on offender categories like Sex Offender, 

Second Striker, and other methods of denoting an offender as “serious” or “violent” in 

California law and policy needs to be tempered with a more nuanced conception of risk— 

if the goal is to spend scarce supervision resources on the offenders most likely to 

reoffend. In other words, being designated as a particular kind of “bad” offender draws 

attention away from the offenders who are responsible for the vast bulk of criminal 

violations. In this regard, the department’s policies and practices could benefit from a 

greater appreciation of the “risk principle”—that supervision should be concentrated on 

the individuals who are estimated to pose the greatest risk and away from the individuals 

who pose lesser risks. While the department has recently begun to conduct risk 

assessment based upon an actuarial risk instrument, it does not link the assessment of risk 

to actual supervision practice. 

Drug and property offenders, on the other hand, tend to be seen as “low-level” offenders, 

posing less risk, and deserving of less attention. However, we show that such offenders 

are more likely to pose higher risks for the most types of criminal violations. Conversely, 

violent and sexual offenders, with a few exceptions noted, do not appear to pose greater 

risks of committing the most serious and violent kinds of violations. Drug and property 

offenders are also particularly prone toward accumulating violations that involve drug 

use and drug possession, which constitute the largest proportion of all violations. The 

pervasiveness of such violations indicates the scale of the drug problem among the 

parolee population and illustrates the need for expanded use of treatment as a 

programmatic response. The lack of service provision is also evident in the 

extraordinarily high rates of all kinds of violations posed by individuals with diagnosed 

mental illness. Expanding opportunities and participation in such programs could produce 

desirable outcomes. Our evidence suggests that creating service opportunities can reduce 

the chances of some types of violations. 

System responses are critical in another regard, as well. It is important to recognize that 

reports of a parole violation are a joint production between individual behaviors and 

organizational attention. In other words, it depends on what the parolee does and how the 

system is structured and how it responds. It is instructive to think of parole violations as 

an iceberg, with the detected and reported violations representing the observable tip. 

Which violations get reported depends upon what the parolee does, but also who they are 

and how they are supervised. We found that supervision intensity matters for whether or 

not violations are detected and reported. This is true for all kinds of violations, even the 

most serious. 

One of the distinctive features of our analysis is our ability to break violations into 

various types. We found different factors at work among different types of violations. 

With regard to some violations, like technical violations and Type I criminal violations, 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
agents’ personal characteristics have effects, but not for other kinds of violations. 

Supervision intensity effects are also more pronounced for technical violations and Type 

I criminal violations. The same is true of regional differences. The implication is that 

among the more discretionary violations, organizational dynamics matter more than for 

more serious violations. It also means that there is more uniformity in the ways serious 

violations are handled. 

Many of these individual and organizational processes also operate with respect to 

revocations—the subject we turn to next. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER VI: WHAT FACTORS PREDICT PAROLE REVOCATIONS


AND RETURNS TO PRISON?


Having described the basic patterns of parole violations and the individual, 

organizational, and community factors that do and do not affect them, we now turn to the 

second key decision point in the career of a parolee—the determination of whether the 

parolee should be returned to custody for their violations. It is critical to understand the 

revocation process because, as noted earlier, a large proportion of the standing state 

prison population is comprised of parole violators who have had their parole revoked, 

and because they are often returned to custody for relatively short periods, violators make 

up an even larger share of annual prison admissions. At the end of 2005, 36 percent of the 

California prison population was comprised of parolees who had been re-incarcerated, 

and parole revocations accounted for 62 percent of all admissions during that same year 

(CDCR 2006). Therefore, any examination of prison crowding in California must account 

for the role of parole revocation in contributing to the problem. Indeed, recent research by 

correctional scholars has shown that reforming the revocation process can be a promising 

way to control prison population growth (Burke and Tonry 2006; Petersilia 2003; 

Jacobson 2005). 

Understanding revocation decisions is also important because of the questionable 

effectiveness of California’s current system of sanctioning, which relies heavily on brief 

custodial spells as punishment for parole violations. The vast bulk of returns to prison 

come not through criminal courts, but by decision of the parole board, which uses a more 

lenient standard than criminal courts in determining guilt, and is only able to return 

parolees to custody for a maximum term of 12 months. Parolees charged with criminal 

violations first have their cases assessed by the court, and if the court is unable or 

unwilling to prosecute the case, it is then referred to the parole board. Violation cases 

processed through parole board can return parolees to prison when the evidence in their 

criminal cases is too weak to warrant a court conviction or when the sentence obtained 

via the court is no greater than what the board can give. As some have pointed out, 

revocation for criminal offenses by the parole board raises procedural justice concerns 

(Petersilia 2006; Travis 2003). On the one hand, parolees who could not be successfully 

returned to prison in a criminal court are returned nonetheless via the parole board. On 

the other hand, parolees accused of quite serious offenses are returned by the parole 

board for shorter sentences than they would receive had their cases been prosecuted in 

court. 

Returns via the parole board are also notoriously short. While a brief prison stay will 

certainly incapacitate a parole violator for a short period of time, it can also sever that 

parolee’s ties to employment, family support and social services, which may lead to 

further violation behavior upon release. Revoked parolees spend all or the majority of 

their time incarcerated in a reception center, which typically has fewer program 

opportunities than a prison. Moreover, even if those programs did exist, a short 

revocation spell would not provide sufficient time for completion. Thus, because 

California’s system of revoking parole for short prison returns provides both minimal 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
incapacitation and rehabilitative benefits, and because it potentially disrupts prosocial 

networks, it likely has, at best, neutral and, at worst, negative impacts on public safety. 

In this chapter, we continue to examine parolee outcomes by considering the individual, 

organizational, and community factors that shape revocation decisions. We are concerned 

with two central questions: What factors affect the sorting of violation cases through the 

courts versus through the parole board and, once in front of the parole board, what affects 

the chances that a parolee will be returned to custody, as opposed to being continued on 

parole? Before turning to these questions we begin with a brief overview of prior research 

on parole revocation. 

RESEARCH ON PAROLE REVOCATION 

The existing research literature about parole revocations is quite limited, but there are a 

few studies that have generated findings that are relevant to our analyses. Kassebaum 

(1999) examined parole revocation patterns in Hawaii, tracking released prisoners for two 

to three years and identifying factors associated with parole failure. He found those who 

were not being released for the first time, drug users, and unemployed parolees to be 

more likely than others to experience revocation. Race/ethnicity was not a predictive 

factor in the Kassebaum study. A follow-up study (Kassebaum and Davidson-Corondo 

2001) found only criminal history and participation in a “conventional lifestyle” to be 

associated with revocation. Hughes, Wilson and Beck (2001) looked at national data on 

parole failure between 1990 and 2000 and identified a number of demographic and legal 

characteristics that were associated with failure. These included male gender, nonHispanic ethnicity, young age, prison commitment for a property offense, and, in contrast 

to Kassebaum (1999), first release to parole. 

In perhaps the most methodologically sophisticated analysis of parole revocation to date, 

Steen and Opsal (2007) identified individual-level factors that were predictive of parole 

revocation decisions in four states.

57 Legal factors, unsurprisingly, were significantly 

predictive of these decisions. Offenders who had prior felonies on record and property 

offenders were the most likely to experience revocation. Steen and Opsal also identified 

demographic characteristics that increased the likelihood of revocation. Male parolees, 

younger parolees, and black parolees were all more likely to have parole revoked. 

Importantly, the degree of difference across demographic categories was greater for 

technical violations than for criminal violations. That is, the penalty for being black, for 

example, increased the chances of revocation on a technical violation more than it 

increased the chances of revocation on a criminal violation. This suggests that the 

influence of extra-legal factors is greater among cases in which more discretion can be 

exercised by decision-makers, and because of this, Steen and Opsal recommend 

investigating the sanctioning of technical and criminal violations as distinct phenomena. 

Our study extends this existing body of research in two major ways. First, as Steen and 

Opsal propose, we examine revocation decisions about criminal and technical violations 

separately. In fact, we conduct separate analyses for criminal violations, technical 

57 The states were New York, Kentucky, Michigan and Utah (Steen and Opsal 2007). 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
violations, and absconding. We also analyze criminal violations according to their level 

of seriousness; there are three main severity categorizations (Type I, II and III) and we 

run separate models to predict the sanctioning of violations within each category. Second, 

we are able to include measures in our analyses that better proxy the discretionary 

elements of revocation decisions in California. While the studies discussed above are able 

to draw some conclusions about discretion relating to individual factors (e.g., racial 

inequality and gender bias), they do not account for organizational and environmental 

conditions that may also affect revocation patterns. In other words, differential 

sanctioning can occur because decision-makers subtly penalize certain parolee groups in 

evaluating their cases, but it can also occur because of organizational pressures and 

because of the perceptions of decision-makers about the neighborhoods that parolees will 

return to. 

Organizational and community factors, in terms of their impact on parole revocation 

decisions, have received almost no research attention. However, criminological theory 

suggests that they can play an important role in driving these decisions. Organizationally, 

workload and population pressures may affect sanctioning patterns because decisionmakers are expected to pay less attention to “low level” cases as their workloads increase 

and as sanctioning opportunities (e.g., jail and prison space) become scarcer. Community 

conditions are expected to affect revocation rates in a couple of different ways. First, 

parolees from more disadvantaged neighborhoods may, in the minds of decision-makers, 

be stigmatized by their environments, and thus experience harsher treatment. Second, 

decision-makers may believe that disadvantaged neighborhoods provide fewer resources 

for facilitating legitimate parolee reintegration, or more opportunities for criminal 

behavior, and thus be more reluctant to re-release parolees to those areas. These 

considerations are important to understand because the inclusion of organizational and 

community conditions as decision criteria indicate a certain amount of unwarranted 

discretion on the part of court and board actors. That is, sanctioning decisions may be 

influenced by factors far beyond the nature of the current parole violation and the legal 

history of the parole violator. 

To better understand the discretionary and non-discretionary elements of the revocation 

process, we draw on theoretical literature about the focal concerns of criminal justice 

decision-makers. Focal concerns theory begins with the assumption that criminal justice 

decision-makers are expected to make sanctioning and release decisions in an 

environment of organizational uncertainty, based on a limited knowledge of the offenders 

under scrutiny and within a larger institutional environment that prioritizes both 

efficiency and legitimacy (Albonetti 1991). To mitigate uncertainty, decision-makers rely 

on important cues that signal the probable consequences of their decisions, and utilize 

three critical dimensions as a framework for these decisions. The three dimensions of 

legal decision-making are: public safety, offender blameworthiness and practical 

constraints (see, for example, Huebner and Bynum 2006; Steffensmeier, Ulmer and 

Kramer 1998). Below, we explicate these dimensions. 

Concern for public safety is understood to be important to sanctioning decisions, and is 

expressed as the potential of applied sanctions to deter and incapacitate offenders, 

thereby reducing crime. The inclusion of blameworthiness as an object of inquiry is 

92


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
rooted in the belief that punishment must be appropriate to the offense and to the 

offender, and that offenders should get the sanctions that they deserve (i.e., “just 

deserts”). The blameworthiness of parole violators, as well as their perceived threat to 

public safety, is signaled by the nature of parole violations, as well as by the offender’s 

legal record. The consideration of community conditions by decision-makers also fits 

with these principles. Court and board actors may feel that parolees from particularly 

disadvantaged communities are somehow representative of these places, and therefore 

more likely to re-offend because they embody the criminogenic characteristics of their 

neighborhoods (blameworthiness). These actors may also penalize parole violators from 

bad communities because they feel that criminal offending is more likely in 

disadvantaged environments that lack legitimate opportunities (public safety). 

The practical constraints dimension of focal concerns theory suggests that decision 

makers must also consider logistical factors such as available agency resources and 

correctional crowding. As time and resources diminish, decision-makers may consciously 

or unconsciously shift their working thresholds for punishment, showing increased 

leniency toward less serious cases. Although one study found that parole board actors did 

not think that prison overcrowding affected their decisions (Burns, Kinkade, Leone and 

Phillips 1999), these dynamics could be operating subconsciously. For this reason, we 

examine the influence of workload pressures and available custodial space on parole 

revocation decisions. 

REVOCATIONS: PATTERNS AND PROCESSES 

There are two ways to experience revocation: through county criminal courts and through 

the parole board. Courts only handle criminal violations—those that result from an 

arrest.

58 The parole board, the Board of Parole Hearings (BPH), handles technical 

violation cases, as well as criminal violation cases that county courts do not successfully 

prosecute. The process by which cases are sorted through one channel versus the other, as 

well as the reasons that some parole violators are revoked while others are allowed to 

return to the community, are not well-understood. How exactly does the revocation 

process work in each venue? Again, returns through the criminal courts all result from 

arrest. If district attorneys (DAs) choose to prosecute these cases, they remain in the 

courts. Parolees returned because of court convictions are called “parole violators with 

new terms” (PVWNTs) and can be re-imprisoned for any length of time that is 

appropriate to their crimes. Those criminal violation cases that DAs decline to prosecute, 

or that are dismissed from court for other reasons, are subsequently referred to the board, 

where they may result in a return to custody. Parolees returned to custody through the 

parole board are referred to as “parole violators returned to custody” (PVRTCs). Those 

that return to the community are “continued on parole” (COP).

59 The board also hears 

technical violation cases, including those involving absconding from supervision, other 

58 The arrest can be made by a police officer or a parole agent. 59 Cases returned through the parole board can be subsequently successfully prosecuted by a local criminal court. When 

this happens the parolee shifts from being a “parole violator returned to custody (PV-RTC)” to a “parole violator with 

new term (PV-WNT)” without ever leaving prison. Because the court “trumps” the parole board in terms of the amount 

of return time, as well as the effect on the offender’s record and parole term, we treat such cases as being returned by 

the court rather than the board. 

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This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
violations of the parole process, access to weapons, and psychiatric endangerment. Since 

these violations involve no legal transgressions—only violations of parole conditions— 

they cannot be evaluated by criminal courts. 

There are two key differences between revocation cases that are tried in court and those 

that are heard by the parole board. First, the two venues use different legal standards 

regarding evidence. In court, a parolee must be found guilty beyond a reasonable doubt 

before a sentence can be imposed. The board, however, must only find a parolee guilty 

according to the preponderance of evidence—a much more lenient legal standard— 

before issuing a sanction. Thus, because parolees charged with criminal violations who 

have their cases dismissed in court must then have their cases heard by the board, they 

essentially endure a legal form of double jeopardy in which they are first tried according 

to a strict standard of evidence, and then a more lenient one. Parolees charged with 

technical violations will stand in front of the board and their cases will also be decided 

according to the more lenient standard. 

The second key difference between the two venues involves the degree of punishment 

that can be issued. When the court finds a parolee guilty of a new crime, it can impose 

any custodial sentence appropriate to that crime. On the other hand, if the board finds a 

parolee guilty of a new crime or a technical violation, it can only impose a return to 

custody of up to one year. The two venues are distinguished by different priorities: 

certainty versus severity. In court, punishment is less certain because of the stricter 

standard of evidence, but when guilt is established, the severity of punishment can be 

very high. The board, using a more lenient standard of evidence, guarantees greater 

certainty of punishment, but the severity of punishment is limited, as returns to custody 

through the board cannot exceed one year. The decision to revoke parole may be 

contingent upon the ability or will of local court officials to proceed with a criminal case 

that could lead to a new term. Some cases may appear to district attorneys as either too 

difficult to prosecute or not sufficiently serious to warrant their attention. In these 

circumstances, they may defer to the parole board, which can move more quickly and 

will more likely force the reincarceration of the parolee, even if it is for less time than a 

criminal conviction from the court. In effect, district attorneys may be weighing the 

certainty of return against the severity of the potential sentence that a parolee is likely to 

receive. 

The dynamics of violation case sorting and the ultimate outcomes of these cases are 

reflected in the data we collected for this study. Figure 6.1 below displays the flow of 

parole violation cases through criminal courts and the parole board, along with their 

outcomes. Among the 151,750 total parole violations reported in 2003 and 2004, 84 

percent (127,742) were criminal violations. Of these criminal violation cases, 31,417— 

25 percent of all criminal violations tried in criminal courts—resulted in a new prison 

term. The other 96,325 cases (75 percent of all criminal violations) were referred to the 

parole board. 

In addition to the criminal cases referred from courts, the parole board also heard 24,008 

technical violation cases (16 percent of all cases), so there were 120,333 total violation 

cases heard by the board during this period. Among these cases, 86,945 (57 percent of all 

94


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
cases) resulted in a return to custody, 28,379 (19 percent of all cases) resulted in 

continuation on parole, and 5,009 cases (three percent of all cases) resulted in another 

outcome. 

Violations Case sorting Case outcomes 

127,742 arrests/criminal 

violations 

(84.2% of all violations) 

24,008 non-criminal 

“technical” violations 

(incl. absconding) 

(15.8% of all violations) 

Criminal courts heard 

127,742 criminal 

violation cases. 

Parole board (BPH) 

heard 120,333 total 

violation cases. 

(96,325 criminal 

violation cases + 

24,008 technical 

violation cases) 

96,325 criminal 

violation cases were 

referred to BPH from 

criminal courts. 

31,417 cases were 

returned from court with 

new terms (PVWNTs). 

(20.7% of all violation 

cases) 

86,945 cases were 

returned to custody 

through BPH (PVRTCs). 

(57.3% of all violation 

cases) 

28,379 cases were 

continued on parole by 

BPH (COPs). 

(18.7% of all violation 

cases) 

5,009 cases resulted in 

an unknown outcome. 

(3.3% of all violation 

cases) 

Figure 6.1: Flow of Violation Cases through the Courts and Board, 2003-2004 

As discussed earlier in this chapter, criminal violations and technical violations are quite 

different, and thus, it is useful to examine each violation type separately. Table 6.1 below 

therefore presents descriptive statistics on the outcomes of criminal violation cases that 

went through the courts and the board during our study period. 

Table 6.1: Revocation Outcomes of Criminal Violation Cases, 2003-2004 

95


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Venue Outcome Number Percent 

Court WNT (court return) 31,417 24.6 

Board RTC (board return) 67,361 52.7 

Board COP (board declines to return) 24,901 19.5 

Board Other 4,063 3.2 

Total 127,742 100.0 

Among criminal violation cases in 2003 and 2004, about 25 percent resulted in a new 

prison term delivered by a criminal court. More than half (53 percent) resulted in a return 

to custody through the parole board, while another 20 percent resulted in continuation on 

parole. Thus, among criminal violation cases, almost four out of five result in some form 

of prison return, either through the courts or through the board. 

Technical violation cases heard by the parole board exhibited a similar rate of prison 

return as criminal violation cases. Over 80 percent of technical violation cases resulted in 

a return to custody. It is important to keep in mind, however, that criminal violation 

returns were issued through both the courts and the board, while technical violation 

returns were only issued through the board. See Table 6.2 below. 

Table 6.2: Parole Board Revocation Outcomes of Technical Violation Cases, 2003 ­

2004 

Outcome Number Percent 

RTC (board return) 19,584 81.6 

COP (board declines to return) 3,478 14.5 

Other 946 3.9 

Total 24,008 100.0 

While court cases center exclusively on criminal charges, revocation cases heard by the 

board can be comprised of any number of criminal, technical and absconding charges. To 

further explore the dynamics of prison return through the parole board, we break down 

board return rates, by the specific composition of charges, in Table 6.3 below. We have 

excluded 5,009 cases in which violation details and outcomes were unknown. 

Overall, the board returned three-quarters of all violation cases heard. Unsurprisingly, the 

highest rate of prison return among board cases was among those cases containing all 

three charge types (criminal, technical and absconding). These cases resulted in return to 

prison 95 percent of the time. The lowest rate of return was among those cases involving 

only criminal charges; these cases resulted in reincarceration only 49 percent of the time. 

We believe that this low return rate among “criminal only” violation cases is related to 

the fact that county courts had already successfully prosecuted those cases that were most 

likely to result in custodial sentences. Thus, in a sense, the parole board receives a 

96


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
“watered down” roster of criminal cases from the court.

60 However, the board is 

substantially more punitive towards those criminal violation cases that have technical or 

absconding charges attached to them. When the board heard cases involving criminal 

charges alongside technical and/or absconding charges, return rates ranged from 88 to 95 

percent. 

Table 6.3: Parole Board Return Rates, by Violation Type, 2003-2004 

Total Percent 

cases returned 

Only criminal charges 37,081 48.5 

Only technical charges (not including absconding) 6,802 79.3 

Technical and absconding charges 5,955 90.9 

Only absconding charges 10,305 85.2 

Mix of criminal and technical (no absconding) 25,971 88.1 

Mix of criminal and absconding 16,501 87.5 

Mix of criminal, technical and absconding 12,709 95.0 

Total 115,324 75.4 

Those cases involving only technical charges, only absconding charges, or a combination 

of these two types also experienced a high rate of return—ranging from 79 to 91 percent. 

This may be the result of a selection bias on the part of parole agents and units. That is, 

parole agents may only choose to report “technical only” cases to their unit supervisors 

when charges accumulate to such an extent that they can no longer be ignored. Relatedly, 

among cases that do not require mandatory referral, units may “hold back” on technical 

violation cases that have not accumulated enough seriousness to result in a likely 

reincarceration. 

While many criminal violation cases heard by the board may be the “watered down” 

variety mentioned above, some others involve very serious charges. Travis (2003) was 

among the first to identify this phenomenon in his analysis of “back-end sentencing,” and 

our data corroborate his contention that the board occasionally assesses serious criminal 

cases. 

A comparison of some selected types of criminal offenses returned through the board and 

those returned by county courts in 2003 and 2004 is presented in Table 6.4. 

60 We find some evidence to support this hypothesis through an analysis of the specific types of offenses 

that comprise the “criminal only” category (criminal violation cases without technical or absconding 

charges attached), compared to other criminal cases heard by the board. Thirty-five percent of “criminal 

only” cases involve “drug use”—typically identified through a failed urinalysis and generally considered to 

be among the least serious types of violations. In comparison, only 19 percent of other criminal violation 

cases (i.e., those also involving technical or absconding charges) heard by the board involve “drug use.” 

97


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 6.4: Comparison of Returns to Prison by Offense Type and Return 

Mechanism, 2003-2004 

Offense Type Courts Board 

Homicide 288 246 

Robbery 1,269 1,006 

Assault and Battery 2,995 8,943 

Rape/Sexual Assault 315 691 

Burglary 2,762 2,132 

Theft/Forgery 5,610 5,509 

Drug Offenses 7,077 18,535 

A surprising number of violent crimes, such as homicide, robbery and rape, are processed 

through the parole board. These crimes carry lengthy prison terms when they are 

prosecuted in courts of law. However, when handled through the parole board, the 

maximum return time is capped at 12 months. Even though the proportion of homicide, 

robbery and rape cases constitute a very small share of the total number of criminal 

parole violations returned to custody through the board, the fact that such cases are 

pursued in this arena is telling. The board is clearly not a venue that exclusively deals 

with “small time” criminal cases. Even though minor offenses appear to be the norm, 

cases involving serious offenses are also heard in this venue. Furthermore, because the 

parole board decides cases under a more lenient standard of evidence than courts, parole 

violators who are factually innocent face an increased likelihood of being returned to 

custody. The fact that court prosecutors referred these serious criminal violation cases to 

the board suggests that there was insufficient evidence to prosecute the cases under a 

stricter standard of evidence. 

When serious criminal parole violations are evaluated by the board, they typically result 

in return to custody. Board cases involving the most serious types of criminal 

violations—Type III offenses, which include homicide, rape and serious assault—are 

returned at higher rates than cases involving less serious criminal activity. See Table 6.5 

below. Type III violation cases are returned to custody 88 percent of the time. Moderately 

serious criminal cases (Type II) result in return almost as frequently; these parole 

violators are returned 80 percent of the time. The least serious criminal cases (Type I) are 

only returned 52 percent of the time. Thus, when moderately serious and very serious 

criminal parole violations are evaluated by the board, the certainty of return is extremely 

high. The board appears to exercise greater discretion over cases involving Type I 

crimes—75 percent of which involve failed drug use and possession violations. 

98


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 6.5: Parole Board Return Rates for Criminal Violations, by Violation 

Severity, 2003-2004 

Criminal violation severity Total cases Percent returned 

Type I (least severe) 40,908 52.3 

Type II 34,702 80.2 

Type III (most severe) 20,651 87.7 

Total 96,31161 69.9 

It is critical to acknowledge the complexity of this issue. Parolees accused of Type III 

offenses may indeed be murderers, robbers, or rapists whose cases prosecutors did not, or 

felt they could not, successfully prosecute. Parole board officials must have concluded 

that these parolees truly posed a threat to public safety and that there was a 

preponderance of evidence sufficient to justify reincarceration. Parolees do not enjoy the 

same procedural rights as other citizens accused of criminal behavior. However, these 

cases deserve close scrutiny. Justice demands that individuals who have committed 

serious crimes should be punished relative to penalties indicated by the criminal law. 

When a parolee is returned for a serious crime by the parole board for a short stay in 

prison, released back into the community after a few months, justice is denied. 

Our multivariate models, presented later in this chapter, address some of the key issues in 

parole revocation. We investigate factors associated with decisions to return parolees 

through the court versus through the parole board. By focusing on the characteristics of 

cases and offenders, as well as organizational and community factors, that influence the 

sorting of cases through each venue, we are able to contribute to a more detailed 

understanding of the how back-end sentencing unfolds, as well as the consequences of 

how the process works. 

DATA AND DATA SOURCES 

As discussed in Chapter II, the data used in our analyses of parole revocations have been 

assembled from many sources. Most importantly, the characteristics of violation cases 

and parolees themselves are drawn from CDCR’s operational data systems—specifically, 

the Revocation Tracking and Scheduling System (RSTS) and the Offender Based 

Information System (OBIS). These sources contain measures indicating violation types 

and severities, as well as the details of parolees’ demographic and criminal-legal 

characteristics. 

We compiled measures of organizational pressure—which are expected to affect 

reincarceration decisions through variation in available sanctioning options and the 

workloads of decision-makers—from numerous publicly available datasets. Prison 

reception center occupancy was measured monthly and these data were drawn from 

CDCR’s annual population reports (e.g., CDCR 2005). County jail occupancy was 

measured quarterly and the data were obtained from California’s Corrections Standards 

Authority (e.g., California Board of Corrections 2004). Regarding criminal violation 

61 We excluded 14 cases in which violation details were unknown. 

99


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
cases heard in criminal courts, we hypothesized that the caseloads of district attorneys 

would affect their decisions to prosecute or refer cases, so we calculated a variable 

measuring the number of felony cases divided by the number of district attorneys 

annually in each county—a standardized measure of court workload pressure. Felony 

caseload data were taken from the Judicial Council of California’s annual Court Statistics 

Reports (Judicial Council of California 2004) and data about district attorneys was 

provided by the California Office of the Attorney General.

62 Felony caseload data were 

incomplete, or missing, for ten counties in 2003 and five counties in 2004. To fill in these 

values, we estimated felony court caseloads based on the number of felony arrests in the 

county for a given year.

63 

Our measures of community characteristics contain one variable measured at the countylevel and others at the census tract-level. Our county-level measure of “punitiveness” is a 

combined factor score based on voting on correctional rehabilitation-oriented ballot 

propositions. 

Census tract-level measures were downloaded from the U.S. Census’s website and reflect 

data from the 2000 census survey. To assess whether community socioeconomic 

conditions affect revocation decisions, we created a census tract-level factor score 

indicating “concentrated disadvantage”—a concept derived from criminological theories 

which posit that poor environmental conditions will spur criminal activity.

64 While 

concentrated disadvantage indicates potentially criminogenic conditions in a community, 

other factors measure community characteristics that may protect against criminal 

behavior. We thus include a tract-level measure of public assistance generosity, which is 

calculated as the percent of households in poverty that receive public assistance income. 

Similarly, we include a measure of available services in the community. From data 

provided by the federal Substance Abuse and Mental Health Services Administration 

(SAMHSA), we used Geographic Information Software to create a variable indicating the 

number of service providers within 50 miles of a given California census tract.

65 

Criminological theorists have contended that system decisions can also be affected by the 

degree of “racial threat” presented by a community; that is, communities with higher 

proportions of minority residents, and those with high minority unemployment rates, are 

expected to be more punitive in their responses to crime (Blalock 1967; Kent and Jacobs 

2005; Stolzenberg, D’Alessio and Eitle 2004). We thus include two census tract-level 

measures of racial threat: the percent of black residents and the percent of black residents 

that are unemployed. 

62 http://ag.ca.gov/cjsc/statisticsdatatabs/PersoCo.php
 63 We attempted a number of different solutions for this problem, including multivariate techniques, but


decided on a simple arrest-to-caseload ratio because this approach produced the most consistent and


realistic estimates.
 64 The specific measures included in this factor score were: percent of households under the poverty line,


percent of residents who were unemployed, median household income, percent of children living with


unmarried parents, and percent of residents who are black.
 65 To qualify, the provider must accept clients referred from criminal justice agencies.


100


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix D lists the independent variables included in our multivariate revocation 

analyses, sorting them by conceptual categories (i.e., case characteristics, individual 

characteristics, organizational factors and community characteristics).

66 

METHODOLOGY: LOGISTIC REGRESSION ANALYSIS OF PAROLE


REVOCATIONS


We estimate two sets of multivariate logistic regression models predicting revocation 

outcomes. Logistic regression is a statistical approach that is commonly used to predict 

the probability than an event will occur, and is therefore appropriate for the analyses we 

present in this chapter, which predict “either/or” outcomes—specifically, whether a 

violation case results in court conviction, and whether the board decides to return a parole 

violator to custody. The models produce, for each independent (predictor) variable, a 

standardized “odds ratio” that indicates the effect of a one-unit change in that variable on 

the outcome of interest. So, for example, in predicting board decisions to return to 

custody, if the odds ratio associated with the “male” variable (a dichotomous one) is 2.0, 

this result would indicate that males are twice as likely as females to be returned. The 

interpretation of odds ratios for continuous variables, such as the number of criminal 

charges associated with a violation case, works differently. In this situation, an odds ratio 

of 2.0 would indicate that each additional criminal charge doubled the chance of return to 

custody. For more detailed reviews of this statistical approach, see Allison (2001), 

Hosmer and Lemeshow (2000), and Kleinbaum and Klein (2005). 

Our first set of analyses is concerned with identifying the factors that that affect whether 

criminal violations are handled by criminal courts or by the parole board—what we refer 

to as the “case sorting” process. Regarding case sorting, we are primarily concerned with 

the characteristics of parolees and communities that are associated with criminal 

violations that are returned to custody though the courts, as opposed to being referred to 

the parole board. We also focus on organizational factors, such as court caseloads and jail 

overcrowding, which may influence these dynamics. 

Our second set of analyses are focused on criminal and technical violations handled by 

the parole board, and designed to identify parolee characteristics, organizational factors 

and community characteristics that are likely to lead to returns to custody. We analyze six 

different dependent variables: all criminal violations, Type I (least serious), Type II 

(moderately serious), and Type III (most serious) criminal violations, and two types of 

technical violations—absconding and technical violations other than absconding (i.e., 

psychological endangerment, weapons access, and violations of the parole process). 

We have chosen to model criminal, absconding and technical violations separately 

because, as Steen and Opsal (2007) suggest, the rationales by which different types of 

66 Appendix D also reports descriptive statistics about parole violation/revocation cases that were heard in 

court and by the board during the study period. In addition, certain variables are excluded from certain 

statistical models. We exclude independent measures when there is no logical reason for them to be related 

to the outcome of interest. For example, the felony caseloads of district attorneys are not expected to relate 

to board revocation decisions, so this measure is excluded from our board return models. Further details on 

many of the measures are included in Chapter V on the analysis of parole violations. 

101


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
violations are sanctioned may be unique to each type. We further break criminal violation 

cases into three subgroups reflecting case seriousness because the board may utilize 

different reasoning in dealing with criminal violations of different severities. Type I 

violations, 75 percent of which involve drug use and possession violations, are likely to 

receive different treatment than Type III criminal violations, which involve serious 

offenses like homicide, rape and assault. 

THE SORTING OF CRIMINAL VIOLATION CASES BETWEEN COURTS AND 

THE PAROLE BOARD: MULTIVARIATE RESULTS 

In our first multivariate regression model, we are primarily concerned with identifying 

factors associated with courts’ decisions to return parolees to prison for criminal parole 

violations, as opposed to having these cases referred to the parole board. Independent 

(predictor) variables measure the characteristics of parolees’ cases, parolees themselves, 

time- and place-specific institutional pressures, and characteristics of parolees’ 

communities. Detailed results are available in Appendix E. 

The cases that are included for analysis are approximately 128,000 criminal parole 

violations that occurred in 2003 and 2004—all of the criminal violation cases that were 

processed by local courts and the parole board. The dependent variable is whether a 

parolee’s violation case was returned to prison through the court or handled by the 

parole board.

67 This variable effectively measures the successful prosecution of criminal 

parole violations in court. 

Case and Individual Characteristics 

As with violations, the most decisive factors determining court returns are individual and 

case characteristics. The number and severity of criminal charges are mainly included as 

control variables. While the number of criminal charges associated with a criminal 

violation case is not predictive of successful court prosecution, charge severity does 

predict return by the court. Cases with higher criminal severity scores—those involving 

more serious charges—are more likely to be successfully prosecuted in court, suggesting 

that court actors tend to pursue cases involving more serious criminal activity. 

In terms of parolee characteristics, those with more previous returns to prison, counted as 

the number of previous returns by either the parole board or by court conviction, are more 

likely to be returned through the court. Each additional California adult prison stay on a 

parolee’s record increases the likelihood of reincarceration through the court by roughly 7 

percent. Parolees’ present commitment offenses are also significantly related to returns to 

custody through the court. Those who had originally been imprisoned for property and 

“other”

68 offenses are the most likely to be returned through the court, followed by those 

67 Cases that were handled by the parole board include cases where “good cause” is found but rather than 

being returned to prison, the parolee is continued on parole. Cases that were referred to the board and then 

“dismissed” without good cause were excluded from the analysis. In our data, about 4.5% of criminal 

violation cases were dismissed. 68 Other offenses are mostly weapons possession (46%), driving under the influence (17%) and literally 

“other offenses” (32%). 

102


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
who had been imprisoned for drug crimes. Parolees who had been committed for violent 

and sexual offenses are the least likely to be returned to prison by the court, and the most 

likely to have their cases referred to the board (Table 6.6). 

Table 6.6: Ranked likelihood of court return, by original commitment offense 

Original commitment offense 

Most likely to be returned by the court “Other” 

Property 

Drug 

Sexual 

Least likely to be returned by the court Violent 

Similarly, offenders whose previous offending history has resulted in them being labeled 

as “serious” or “violent” are actually about 17 percent less likely to be returned through 

the court. Also, registered sex offenders are about 23 percent less likely to be returned 

through the court. These patterns may be due, at least in part, to the relative strength of 

evidence in and/or the seriousness of the criminal violation cases of different parolee 

subgroups, but they may also be attributable to perceived notions of dangerousness. 

Serious and violent offenders, as well as registered sex offenders, may be considered 

particularly likely to reoffend in the absence of immediate incapacitation, and court 

actors may tend to refer their cases to the board, where the certainty of return is higher. 

The one exception to the conclusion that violent offenders are less likely than other 

offenders to be returned through the court is in regard to “Second Strikers.” Holding 

constant other factors, Second Strikers are 45 percent more likely than others to be 

returned to prison by the court, as opposed to having their cases referred to the board. 

This may be due to concerns about public safety or blameworthiness, with Second 

Strikers perceived as particularly dangerous offenders, and thus in need of the long 

periods of incarceration that only court sentences can provide. This finding may also be 

interpreted as a “labeling” effect. Those parolees who have been “labeled” as Second 

Strikers appear to arouse more concern from the court, and are more likely to be returned 

to prison by court actors. A final explanation may be that Second Strikers’ violation cases 

are more appealing to prosecutors because the threat of a third strike gives them more 

leverage in plea bargaining. 

While the characteristics of cases and the offending histories of parole violators may be 

legitimately considered in making prosecution and referral decisions, other factors should 

not be germane to criminal violation case outcomes in court and indicate a certain amount 

of unwarranted discretion in these decisions. We find that over and above the 

characteristics of cases and histories of offending, the demographic and psychological 

characteristics of criminal parole violators also have some influence on court prosecution 

and referral decisions. While gender does not impact these outcomes, race does. Black 

parole violators are 15 percent less likely than whites to experience successful court 

prosecution, while Hispanic parolees are 4 percent more likely than whites to be 

prosecuted in court. Asian parolees and those of “other” racial groups are the most likely 

to be successfully prosecuted in court (24 and 14 percent more likely than whites, 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
respectively). In terms of age, the youngest parolees (ages 18-30) are 17 percent more 

likely than others to be returned to prison through the courts. Finally, parolees with 

officially recognized mental health conditions are 6 percent less likely than parolees 

without such conditions to experience court return. Thus, our results indicate that race, 

age and mental health conditions can be important considerations to district attorneys and 

judges in criminal courts. Like indicators of criminal seriousness, demographic and 

psychological characteristics may indicate different aspects of perceived threat to public 

safety. Court decision-makers may—consciously or unconsciously—consider some 

parolees (e.g., black parolees, those with mental health conditions) to be in need of 

immediate incarceration, and tend to refer these cases to the board, where the certainty of 

return is higher. On the other hand, court actors may feel that the youngest parole 

violators are so dangerous that longer court-ordered sentences must be pursued. 

Organizational factors 

Regional and other organizational factors also affect court prosecution and referral 

decisions. Specifically, decision-making discretion can be identified in the geographic 

variation of case outcomes and in the relationship between workload pressures and 

prosecution decisions. This implies that “like cases may not be treated alike” and 

questions the consistency of this decision across venues in different places, and under 

variable organizational conditions. 

Holding constant all other included measures, Los Angeles County (Parole Region 3) is 

82 percent more likely to return criminal parole violators to custody through the court 

system, compared to other regions. There can be a number of explanations for this 

finding. There may be something unique about the organizational culture of criminal 

courts in Los Angeles County, such that they are more inclined than other county courts 

to pursue the reincarceration of criminal parole violators. Or, criminal parole violators in 

Los Angeles may exhibit unmeasured traits that are predictive of court return. For 

example, they may have less stable employment or housing, on average, than other 

California parolees; they may be more likely to be members of gangs; or local officials 

may simply believe that they are somehow more inclined toward dangerous behavior. 

Another possibility is that the police in Los Angeles are more effective in assembling 

evidence, so that criminal courts find these cases more prosecutable. 

We also find evidence that institutional population and workload pressures can influence 

the treatment of criminal parole violations in court. When prison reception centers are 

crowded, courts are less likely to return parolees to prison, and more likely to refer 

criminal parole violations to the board. As populations increase in California prison 

reception centers, court prosecutions go down slightly. Conversely, as populations 

increase in county jails, court prosecutions go up slightly. The caseloads of district 

attorneys are also related to the likelihood of court return. As prosecutorial caseloads 

increase, the likelihood of court return decreases, and the likelihood of board referral 

increases. Thus, over and above the characteristics of cases and offenders, organizational 

factors appear to influence court actors in their prosecution and referral decisions. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Community factors 

Finally, some community characteristics are associated with an increased likelihood of 

successful prosecution of criminal violation cases in court. This suggests inconsistencies 

rooted in decision-makers’ perceptions of parolees’ communities, or in the value systems 

of decision-makers from different areas. 

Court decisions can reflect the values of the communities in which the courts are located. 

For example, communities that score higher on punitiveness—as measured by ballot 

initiative voting outcomes and political party affiliation—are more likely to retain their 

criminal violation cases in court. That is, communities with more punitive attitudes 

toward crime punish parole violators more harshly. 

Variation in court revocation decisions may also be due to the fact that parolees from 

certain communities exhibit characteristics that courts “penalize,” or that parolees are 

actually stigmatized by the conditions of their home neighborhoods. That is, decisionmakers may believe that the criminogenic conditions and the lack of services in certain 

neighborhoods may inhibit successful reintegration. Communities that rate highly on 

“concentrated disadvantage”—a combined factor measure that includes measures of 

poverty, unemployment, family stability and minority residency—are more likely to 

return parole violators through court. Communities that score higher on racial threat— 

those that have larger black populations and higher black unemployment rates—are also 

more likely to pursue violation cases in court. An increase of one percent in a census 

tract’s black population is found to be associated with a three percent increase in the 

likelihood of court return to custody. An increase of one percent in a census tract’s black 

unemployment rate is associated with a one percent increase in the likelihood of court 

return. 

PAROLE BOARD DECISIONS TO RETURN PAROLEES TO CUSTODY:


MULTIVARIATE RESULTS


The analysis described above describes the factors affecting whether violation cases are 

processed through the court or the parole board. Next, we examine decision-making by 

the parole board. Our second set of revocation models examine only parole violation 

cases heard by the board. These include criminal violation cases referred to the board 

from criminal courts, as well as absconding and noncriminal “technical” violation cases 

referred to the board directly from statewide parole units. We ask: What case-specific, 

individual, organizational and community characteristics are associated with board 

decisions to return parolees to custody? 

To determine whether, and to what extent, different measures are predictive of prison 

return for different violation types, we estimate separate models for all violations, 

criminal violations, absconding, and other technical violations not involving absconding 

(i.e., violations of the parole process, psychological endangerment, and weapons access). 

We also estimate separate models for Type I, II and III criminal violations (i.e., violations 

of different criminal severities). 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The dependent variable of interest is return to custody through the parole board versus 

board decisions to “continue on parole.” The dependent variable is dichotomous, with a 

value of “1” indicating return to custody through the board and a value of “0” indicating 

continuation on parole (i.e., release to the community). The models therefore assess the 

ability of each independent variable to predict board decisions to return parolees to 

custody among the violation cases of interest. 

We include the same independent variables from the previous “sorting” model as 

predictors in our board return models, with certain key differences. First, the variable 

measuring district attorneys’ felony court caseloads is excluded from the board return 

models because it is not theoretically connected to board members’ return decisions. 

While higher prosecutorial caseloads may cause courts to refer more criminal violation 

cases to the board because of increased workload pressures, they should not have any 

impact on board returns, which are decided outside of courtrooms. The second key 

difference relates to the fact that different violation types (criminal, absconding, other 

technical not involving absconding) can be combined into the same case. Most violation 

cases contain multiple violations. Moreover, cases frequently include multiple types of 

violations. As such, for each violation type model, we control for other types of 

violations that may exist alongside the specified violation type. For criminal violations, 

we include independent control variables that indicate the number of absconding (PAL) 

and other technical violations contained in a particular case. For absconding violations, 

we include independent variables indicating the number of criminal charges in the case 

and the number of non-PAL technical violation charges. For non-PAL technical 

violations, we include independent variables that indicate the number of criminal charges 

and the number of PAL violations in the case. Thus, independent variable effects on case 

outcomes control for other violation types that may exist within that case. Detailed model 

results can be found in Appendix F. 

Case and Individual Characteristics 

As with the sorting models described above, case characteristics are significantly 

predictive of returns to custody among parole violation cases heard by the parole board. 

Effects are fairly large and generally operate in expected directions. Cases with higher 

severity scores—the summed seriousness of all charges associated with the case—are 

more likely to result in reincarceration. The severity of technical charges is generally 

more predictive of returns to custody than the severity of criminal charges—with the 

exception of cases involving absconding. In absconding cases, only criminal severity is 

associated with the likelihood of return to custody. 

The number of charges involved in a violation case is also associated with the likelihood 

of reincarceration. Cases containing more criminal charges, absconding violations and 

technical violations not involving absconding are, for the most part, more likely to result 

in decisions to return parolees to custody. In general, the effects of added criminal, 

absconding, and other technical violation charges are greatest for criminal violation cases 

heard by the board. Among these criminal violation cases, each additional criminal 

charge increases the likelihood of reincarceration by 14 percent; each additional technical 

violation not involving absconding increases the likelihood of reincarceration by 89 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
percent; and each additional absconding charge increases the likelihood of reincarceration 

by 255 percent. 

However, our models predicting criminal violations of different severities show that there 

is substantial variation in the ways that these effects play out across levels of criminal 

seriousness. Additional criminal charges provide the largest penalty in the most serious 

criminal violation cases (Type III); each additional criminal charge increases the 

likelihood of reincarceration by 18 percent among these cases. Strangely, additional 

criminal charges are actually negatively associated with the likelihood of return among 

Type I and II (less serious) criminal violations. The presence of absconding and other 

technical violations have a greater effect on cases involving less serious criminal offenses 

(Types I and II). Among the most serious (Type III) cases, the presence of technical 

violations has no impact on the likelihood of reincarceration, and the presence of 

absconding charges has a more modest effect than it does on lesser criminal cases. Thus, 

it appears that among the most serious criminal violation cases, board members are 

highly concerned with the presence of additional criminal charges, but in lesser criminal 

cases, additional criminal charges matter less and technical charges matter more. Board 

decisions about the most serious criminal violation cases, therefore, center on the 

criminal offenses under consideration, while decisions about less serious criminal 

violation cases allow for the increased influence of technical and absconding charges. 

Additional charges are also associated with higher reincarceration likelihoods in cases 

involving technical violations not involving absconding. In such cases, each included 

criminal charge increases the likelihood of reincarceration by 10 percent and each 

included absconding violation charge increases the likelihood by 78 percent. Absconding 

cases appear to proceed slightly differently. In such cases, each additional criminal 

charge is actually associated with a 7 percent lower chance of reincarceration. This may 

be due to the fact that among absconding cases involving substantial numbers of criminal 

charges, the seriousness of each charge is fairly low. Each additional technical charge not 

involving absconding in an absconding case, however, is associated with a 61 percent 

higher likelihood of return to custody. 

Absconding violations have large and significant effects on board violation cases 

involving other types of violation charges, increasing the likelihood of reincarceration in 

criminal violation cases by 255 percent and technical violation cases by 78 percent. The 

coefficients associated with absconding violation charges are among the largest in the 

models. In other words, an added absconding charge presents one of the largest penalties 

for a parolee facing a board hearing on a criminal or technical violation, as added 

absconding violations increase the likelihood of reincarceration more than any other case 

or individual characteristic. Board members may be especially wary of releasing parolees 

who have demonstrated a willingness to abscond from supervision.

69 

69 Here, evidence of absconding can operate in at least a couple of different ways. For example, homeless parolees may be

charged with absconding because they have trouble complying with reporting requirements. Other parolees may evade

supervision because they intend to engage in criminal behavior. Whatever the reasons behind absconding, it is clear that

board members penalize those parolees who engage in it.

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
While case characteristics have, as expected, a large effect on board revocation hearing 

outcomes, a parolee’s criminal history is also highly predictive of board decisions to 

return parolees to custody, net of all other measured factors. Criminal history is, for the 

most part, statistically significant in terms of its relationships to case outcomes and they 

are predictive in expected directions. For example, parolees’ most recent commitment 

offenses are significantly related to violation case outcomes. Across all three of our main 

regression models (criminal, absconding, technical), net of other measured factors, 

parolees who had been committed for sex offenses and violent offenses are the most 

likely to be returned to custody by the parole board. Drug and property offenders are the 

least likely (Table 6.7). Recall that criminal courts are more likely to successfully 

prosecute the criminal violation cases of property and drug offenders. The board, on the 

other hand, is focused on returning sexual and violent offenders. Holding constant the 

seriousness and multiplicity of violations committed, criminal history and personal 

characteristics, sexual and violent offenders are significantly more likely to be returned to 

custody by the board than drug and property offenders. 

Table 6.7: Ranked likelihood of reincarceration, by original commitment offense 

Likelihood of Criminal Absconding Technical 

return violations violations, Not 

involving 

Absconding 

Most likely Sexual Sexual Sexual 

Violent Violent Violent 

Other Other Other 

Property Property Property 

Least likely Drug Drug Drug 

Parolees with a sexual commitment offense are 49 percent more likely than drug 

offenders—the reference category group—to be returned for criminal violations, 17 

percent more likely to be returned for absconding, and 33 percent more likely to be 

returned for technical violations. Similarly, parolees with violent commitment offenses 

are about 45 percent more likely than drug offenders to be returned for criminal 

violations, 16 percent more likely to be returned for absconding violations, and 29 

percent more likely to be returned for technical violations not involving absconding. 

Among the most serious criminal violation cases heard by the board (Type III), 

commitment offense has little impact on the likelihood of return. The only types of 

violations that are not affected by commitment offense are Type III criminal violations. 

In such cases, what a parolee has done to earn his or her most recent commitment fades in 

importance relative to other factors. 

Indicators of parolees’ criminal “seriousness” are related to decisions to return them to 

custody; in most instances, relationships appear strongest among criminal violation cases 

heard by the board, particularly the least serious cases (Type I). The more prior adult 

prison spells that a parolee has served in California, the more likely that that parolee will 

be returned to custody. Each additional prison term on record increases the likelihood of 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
return among board violation cases by about 4 percent, regardless of violation type 

(criminal, absconding, technical). Second strikers are 15 percent more likely than others 

to be returned by the board on a criminal violation, although it must be noted that this 

effect is really only true for the least serious criminal violation cases; they are no more 

likely than others to be returned on Type II or III criminal violations. Second strikers are 

also no more likely than others to be returned on an absconding violation or a technical 

violation not involving absconding. Similarly, parolees with serious and/or violent 

offense histories are 28 percent more likely to be returned for the least serious criminal 

parole violations, but no more likely than others to be returned on Type II or III criminal 

violations, 

70 absconding or other technical violations not involving absconding. 

Registered sex offender status is a powerful predictor of return. This status doubles the 

chances of reincarceration in criminal violation cases, and increases the likelihood of 

reincarceration in absconding cases by 43 percent and in technical violation not involving 

absconding cases by 28 percent. Among criminal violation cases heard by the board, 

registered sex offender status has the greatest effect on the lowest level cases, increasing 

the likelihood of reincarceration by five times. They are about 35 percent more likely to 

be returned for the most serious criminal violations (Type III), but 17 percent less likely 

to be returned for Type II criminal violations. As noted in the previous chapter, this 

finding is likely due to the fact that, among registered sex offenders, a large share of these 

Type II violations are for “failing to register,” and not for criminal activity involving a 

victim. 

In terms of their impact on the likelihood of reincarceration, demographics and other 

personal characteristics matter to a limited degree. Age has no relationship to case 

outcomes for any violation type. Gender only has an effect on absconding cases and the 

most serious criminal violations. Women are 13 percent more likely than men to be 

returned to custody by the board for absconding. Men are 27 percent more likely than 

women to be returned for Type III criminal violations. Race matters only in criminal 

violation cases. White and Asian parolees have the lowest likelihoods of return. Black 

parolees are 9 percent more likely than whites to be re-incarcerated; Hispanic parolees 

are 19 percent more likely than whites; and parolees of “other” races are 25 percent more 

likely than whites. Thus, parolees of color, with the exception of Asians, appear to be 

“penalized” in criminal violation cases. 

Parolees’ official mental health statuses have little effect on board decisions to return to 

custody. While parolees with such statuses are 9 percent more likely than others to be 

returned to custody for the lowest level criminal violations (Type I), they are no more 

likely to be re-incarcerated for more serious criminal violations, absconding, or technical 

violations. 

Organizational factors 

Regional and organizational factors are also related to board case outcomes. As with 

court decisions, the contribution of these factors to the likelihood of return by the board 

70 Serious and violent offenders are actually 14% less likely to be returned than others for the most serious 

criminal violations (Type III). 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
suggests decision-making inconsistency based on geography and variable institutional 

conditions. In other words, like cases may not be treated alike in different places, or 

during different times. 

As in the previous court/board case sorting model, Los Angeles appears to be unique in 

its treatment of parole violations—but only non-criminal violations. Holding constant 

other factors, technical violation cases not involving absconding are 46 percent more 

likely to result in reincarceration. The effect is reversed for absconding cases; these cases 

are 20 percent less likely to result in reincarceration in Los Angeles. There may be a 

couple of explanations for these findings. First, as parole officials have indicated, Los 

Angeles may possess a distinct organizational culture that feeds the differential treatment 

of technical violations. Or, parolees accused of technical violations in Los Angeles may 

exhibit unmeasured characteristics that affect revocation decisions (e.g., employability, 

addiction). Or, both may be true. 

Institutional population pressures also appear to have an effect on board returns to 

custody. As state prison reception centers become more crowded, the board is less likely 

to return parole violators to custody, regardless of the type of case under consideration. 

For each one percent increase in reception center occupation, there is a corresponding one 

percent decrease in the likelihood of reincarceration for a criminal violation, a two 

percent decrease in the likelihood of reincarceration for an absconding violation, and a 

one percent decrease in the likelihood of reincarceration for a technical violation not 

involving absconding. These findings suggest that decisions by parole board actors can 

be influenced by available prison bed space, and confirm the impact of broader 

organizational circumstances on the adjudication of individual cases, 

Community Factors 

Finally, parolees’ community characteristics affect violation case outcomes, implying 

that decision-makers vary in their orientations about correctional practices across 

different geographic areas, and/or that their decisions are affected by their perceptions of 

parolees’ communities. 

The “punitiveness” of communities—as measured by their ballot proposition voting 

patterns—is strongly predictive of return to custody in all violation case types, with more 

punitive communities electing to return parolees at greater rates. This effect is larger for 

absconding and technical violations not involving absconding than for criminal 

violations. Measures of community racial threat are also linked to case outcomes. For 

each one percent increase in a community’s proportion of black residents, there is a one 

percent increase in the likelihood of prison return for a criminal violation. For each one 

percent increase in a community’s black unemployment rate, there is a two percent 

increase in the likelihood of reincarceration for a criminal violation, a four percent 

increase in the likelihood of reincarceration for an absconding violation, and a two 

percent increase in the likelihood of reincarceration for a technical violation not involving 

absconding. Finally, higher concentrations of mental health and substance abuse service 

providers in a community are predictive of more lenient case outcomes. The more 

services that exist near a community, the less likely it is that a parolee from that 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
community will be returned to custody by the board for a criminal or a technical violation 

not involving absconding. For every ten services located within 50 miles of a parolee’s 

census tract,

71 the chance of reincarceration for a parolee from that tract with a criminal 

or a technical violation not involving absconding decreases by about two percent. 

(Service provider concentration is not related to the likelihood of reincarceration for 

absconding.) 

As compared to the community affects on violations themselves, described in Chapter V, 

the community findings show consistently more influence on revocation decision-making 

than they do on actual parolee behavior. They also suggest that revocation decisionmaking is subject to important extralegal factors not specifically relevant to individual 

cases. With these points in mind, we next look across all of the different analyses 

conducted in this chapter and summarize what we have found about revocations. 

SUMMARY AND DISCUSSION OF REVOCATIONS ANALYSIS 

Before turning to the policy implications that follow from these results, it is useful to 

recap our central findings with respect to revocations. First and foremost, case 

characteristics (number and severity of charges) appear to be a critical factor shaping 

whether or not cases go through a local criminal court or through the parole board. They 

also influence whether a case processed by the parole board winds up producing a return 

to custody. 

Beyond case characteristics, the results of our analyses indicate that parole revocation 

decisions can be understood through the examination of individual, institutional and 

community factors that affect these decisions. In terms of individual factors, parolees 

with longer, and more serious, histories of criminal behavior are also likely to be 

considered public safety risks by court and board decision-makers, and their cases are 

treated accordingly. Net of the seriousness of their current violations, parolees’ histories 

of imprisonment, for example, are significantly predictive of harsher treatment by both 

the court and the board. Second strikers are also significantly more likely to be returned 

through the court than parolees without such status, and when their cases are referred to 

the board, they are significantly more likely to be re-incarcerated in cases involving 

criminal violations. Statutorily-defined “serious” and “violent” offenders and registered 

sex offenders are actually less likely than others to experience court return to prison, but 

when their criminal violation cases are referred to the parole board, they are more likely 

to be returned to custody. 

One explanation for these findings is that the criminal violation cases of serious and 

violent offenders, and sex offender registrants, may be unappealing to court actors 

because they tend to lack compelling evidence. However, court actors may also tend to 

refer these cases because they feel that the board, using a lower standard of evidence, can 

act quickly and decisively to re-incarcerate parolees who are perceived as particularly 

threatening to public safety. The board penalizes these types of parolees especially 

severely in low level (Type I) criminal violation cases—the type allowing for the most 

71 Specifically, this measure counts substance abuse and mental health service providers located within 50 

miles of the center of a given census tract. 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
discretion in terms of decisions to return to custody. It appears that low level criminal 

activity, much of which is detected through parolee drug testing, is a crucial mechanism 

by which the parole board re-incarcerates “high profile” parole violators. Note that the 

courts could not legally impose very harsh sanctions for these low level crimes, and so 

they seem to opt, through case referral, for the greater certainty of punishment that the 

board is able, and willing, to provide. Indeed, parole officials have told us that courts 

frequently refer these cases to the board because court sentences would not exceed those 

that the board could impose, so it does not make sense to draw on court resources to 

prosecute them. 

Parolees’ “original” commitment offenses are also predictive of violation case outcomes, 

but these relationships are complex and seem to operate differently in courts and the 

parole board. Courts are inclined to retain and prosecute parolees who had originally been 

committed for property and “other” offenses—most of which are weapons offenses and 

driving under the influence. Court actors appear to desire longer prison terms for those 

who are in the practice of stealing from others, those who have been found to possess 

weapons, and those who make state motorways unsafe.

72 Since these types of offenses 

tend to be more repetitive than violent and sexual offenses, they might be considered 

indicators of the probable frequency or likelihood of offending. The board, on the other 

hand, appears more concerned with the potential severity of parolees’ offending— 

penalizing violent and sex offenders the most in its decisions to re-incarcerate. This idea 

is further echoed in the finding, mentioned in the previous paragraph, that serious and 

violent offenders, as well as registered sex offenders, are less likely to be retained in 

court, but they are significantly more likely to be returned to custody when their cases are 

heard by the board. Again, courts may elect to refer cases involving serious parolee types 

to the board because the board can re-incarcerate with greater certainty, under a more 

lenient standard of evidence. This appears to be particularly true for low level criminal 

violations that would not result in very long court sentences anyway. 

Demographic characteristics are also somewhat predictive of case outcomes. Parolee age 

affects criminal court decisions, but not board decisions. Courts are inclined to prosecute 

the criminal violation cases of the youngest parolees (ages 18-30). Black parolees are 

more likely to have their cases referred to the board—the more discretionary venue—and 

when their cases are heard by the board, they are more likely to be incarcerated for 

criminal violations. Asian and Hispanic parolees are the most likely to be successfully 

prosecuted in court, and Hispanics are further penalized in front of the board, where they 

are among the most likely to be returned to custody in criminal violation cases. White 

parolees, who have the lowest likelihood of court conviction, also have the lowest 

likelihood of return through the board for criminal violation cases (although they are 

among the most likely to be returned when they abscond). These findings suggest that 

there may be observable or unobservable traits associated with parolees of different 

demographic groups that affect their case outcomes. 

72 However, court decisions to prosecute are also based on considerations related to the strength of 

available evidence in criminal cases. Some amount of the court’s proclivity to prosecute property and 

“other” offenders may be related to the relative strength of evidence in their cases, as opposed to the cases 

of other parolee types. 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Over and above case- and parolee-specific characteristics, organizational factors also 

affect decisions in court and by the board. Los Angeles County (Region 3) appears 

distinct in its treatment of parole violators. Criminal violations in Los Angeles are more 

likely to result in reincarceration through the court. Board decisions are also uniquely 

patterned in Los Angeles. Technical parole violators are more likely to be returned to 

custody in this area, while absconders are less likely to be returned. These findings could 

be due to many factors: differences in organizational culture across parole regions, 

unobserved variation in the local parolee population that affect sanctioning decisions 

(e.g., addiction and employability), or the effectiveness of policing practices. Regardless, 

the fact that geographic sanctioning variation can be statistically identified is reason 

enough to call for a closer examination of organizational issues around the treatment of 

parole violations. 

Practical constraints on decision-making also appear to play a role in violation case 

outcomes. A key practical constraint is available custodial space. Research suggests that 

criminal justice institutions will divert offenders from custody when institutional 

crowding increases, and we find support for this hypothesis. When available space in 

prison reception centers decreases, for example, courts are more likely to refer cases to 

the board and the board is more likely to continue cases on parole, as opposed to 

returning parolees to custody. Moreover, in courts, workload pressures are linked to an 

increased likelihood of case referral to the board. As felony court caseloads increase, 

courts are inclined to refer more criminal parole violation cases to the parole board. 

This is not to say that court and board actors are always consciously making case 

decisions in response to institutional and workload pressures. Rather, these pressures are 

probably related to decisions in a variety of ways. Some decisions may indeed be 

conscious responses to correctional crowding and court caseloads, but others may be 

subconscious reactions. Still others may simply be due to the redistribution of human and 

organizational resources as a result of these pressures. Increasing court caseloads may 

leave less time for district attorneys to evaluate evidence and pursue cases, and they may 

therefore tend to refer less serious (or more work intensive) criminal parole violation 

cases to the board because they do not have the time or staff to address them. Finally, 

there may be some sort of organizational feedback mechanism at work. That is, as prisons 

and reception centers become more crowded, decision-makers in court and on the parole 

board may become aware of this crowding through personal and professional contacts, or 

through the media, and adjust their decision-making logic in subtle ways. 

The relationship between community characteristics and sanctioning decisions is 

hypothesized from criminological literatures such as social disorganization theory and the 

racial threat perspective. Indeed, our statistical models show that, net of all other 

measured factors, some characteristics of parolees’ communities are related to the 

treatment of parole violations in court and before the parole board. However, the 

characteristics of parolees’ communities can be related to court and board revocation 

decisions in complex ways. 

First, certain community characteristics are indicative of the attitudes of the public and 

the decision-makers that represent the public. For example, the preexisting “punitiveness” 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
of certain communities is itself predictive of the aggregate treatment of parole violation 

cases. Counties that score higher on punitiveness—as measured by political party 

affiliation and electoral ballot voting outcomes—are more likely to return criminal parole 

violators through the court, and in violation cases heard by the board, these counties are 

more likely to return parolees to custody, regardless of whether the case involves a 

criminal, absconding or other technical violations. The concept of community 

punitiveness involves a number of factors—the actual amount of crime in a community, 

residents’ political and moral beliefs about right and wrong, the processes of election and 

political appointment, and media coverage of crime, among other things—but our 

analyses show that punitiveness is measurable in a way that can be empirically linked to 

revocation case outcomes (and perhaps other criminal justice system phenomena as well). 

Second, community characteristics can serve as cues to decision-makers which reflect 

something about individual parolees themselves. The extent of “racial threat” in a 

community is illustrative of this point. Census tracts with higher proportions of black 

residents, and those with higher black unemployment rates, may be perceived as 

particularly unstable or crime-ridden, and parolees that live in these communities may be 

penalized by decision-makers because they come from, and are therefore representative 

of, these disadvantaged environments. In our models, parolees who come from 

communities that have more black residents, and higher black unemployment, are more 

likely to be sentenced in court; when their cases are heard by the parole board, these 

parolees are generally more likely to be returned to custody, especially for criminal 

violations. 

However, while community characteristics can have a stigmatizing effect on case 

outcomes, they can also have the opposite effect. For example, census tracts with more 

mental health and substance abuse services in close proximity are associated with more 

lenient outcomes among criminal and the technical violation cases not involving 

absconding decided by the parole board. This may be due to the fact that decision-makers 

have more treatment options in these communities, and therefore more opportunities to 

keep parole violators out of prison, or that parolees from service-rich communities 

somehow appear less threatening than parolees from communities that lack services. 

A central implication of our analyses of revocations is that the response of criminal 

justice institutions does not totally derive from, and is not necessarily proportionate to, 

the extent of parolees’ illicit behavior, as is often assumed by policymakers, government 

officials, and the public. While case characteristics matter in terms of court and board 

outcomes, so too do the characteristics of the individual, the organizations handling that 

individual’s case, and the community that the person comes from. In the final chapter, we 

put these findings together with those from our analyses of violations in order to draw 

some broad implications for the parole system in California and specific implications for 

policies currently under consideration by the CDCR. 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
CHAPTER VII: CONCLUSIONS AND POLICY IMPLICATIONS


Parole violations and revocations represent a critical issue for California. As we have 

shown in the preceding chapters, the state has an extraordinarily high rate and volume of 

both violations and revocations. California possesses a parole system that contributes to 

the prison overcrowding crisis and is extremely costly. And yet it does not appear to do 

all that it can to enhance public safety. For many offenders, parole supervision fails to 

disrupt the cycle of crime and imprisonment and offers little hope for behavior change. In 

response to these stark facts there have been repeated calls for reform and policy change. 

Indeed, the department has made several halting steps toward reform. The department has 

reduced it parolee-at-large abscond rate from 18 percent in 2003 to 15 percent in 2008. 

CDCR and its parole division have embraced the mantra of, although not entirely 

implemented, “evidence-based” programs, which are correctional practices shown by 

research to be effective in reducing parolee recidivism. The department has begun using 

the Correctional Offender Management Profiling Alternative Sanctions (COMPAS) 

assessment tool at all its reception centers and in reentry preparation interviews, although 

it has not yet integrated it well into its prison or parole supervision practices. The 

department is also developing a parole violation decision-making instrument to improve 

consistency at the agent and supervisor level when faced with a violation in terms and 

conditions or parole or the commission of a new crime. The Division of Adult Parole 

Operations (DAPO) will train parole agents and field test the instrument in Fall 2008. An 

important aspect of the instrument is the development of a validated tool to assess a 

parolee’s risk for recidivism. CDCR recently completed the California Static Risk 

Assessment, the state’s first validated risk to re-offend tool. Thus, there is clear evidence 

of significant progress and a willingness of California correctional leaders to reform the 

system, but there are substantial organizational, political, and structural impediments to 

doing so. 

For example, implementation of evidence-based practices is dependent upon 

organizational capacity and the capacity of the wider community environment. Just as 

overcrowding is an impediment to implementing such programs in the prison, the 

overcrowding in parole has resulted in a system where relatively modest supervision 

resources are spread across an enormous population. The response to these conditions is 

that “catch and release” has become the modus operandi for the parole system, with a 

heavy reliance on drug testing and other surveillance technologies that intensify 

supervision, make violations easy to evidence and detect, and allow parole agents to carry 

overly large caseloads. With primary attention given to surveillance and violation 

detection, program development and implementation remain a weakness for the 

department. The department lacks the experience to develop such programs, typically 

outsourcing program development to external vendors, and communities lack experience 

and the resources to truly support programs. Moreover, it will take many years to develop 

and implement such programs on the massive scale needed, and several years beyond that 

to see positive recidivism-reduction benefits. 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
But these organizational capacity issues are really only part of the problem. As we 

described in Chapter III, there are structural factors that contribute to the problem of 

parole violations and revocations, principally determinate sentencing and mandatory 

parole. No amount of evidence-based practices will entirely make up for a structure of 

parole that virtually guarantees high rates of prison returns. Determinate sentencing laws 

have given California a parole population composed, in part, of many offenders who 

would not be released under a discretionary indeterminate sentencing system. These 

individuals, who pose a high risk to recidivate, are automatically and mandatorily 

released under California’s Determinate Sentencing Law. Moreover, they are released to 

a parole system that provides little in the way of supervision and little in the way of 

services to reduce their likelihood of recidivating. When they do violate parole, they are 

returned for very short stays in prison where they receive little or no services that would 

decrease their likelihood of further involvement in criminal behavior. 

Universal parole also means that low-risk individuals who likely would not be supervised 

in other states are placed on parole in California. Most other states directly discharge 

some non-violent, non-serious offenders once they serve their prison term. Direct 

discharge means that the offenders are not placed on parole supervision after they leave 

state prison. Our research in Chapter V confirms the results found in previous research: 

the more you supervise the more you detect. This is especially true of the large numbers 

of drug use violations, which result almost exclusively from drug testing. Over 80 percent 

of all California parolees are subjected to drug testing while on parole. Obviously, such 

tests are not applied to individuals who are not under community supervision. Thus, the 

inclusion of low-risk offenders in the parole population increases the overall number of 

violations detected. When enough of those drug use violations accumulate, those 

parolees, many of whom have substance abuse problems, are returned to prison where 

they receive little or no substance abuse treatment. California’s Expert Panel on 

Rehabilitation (2007) found that fewer than 10 percent of prison inmates participate in 

substance abuse treatment while in prison. After a short time period reimprisoned (the 

average is 4 months), they are returned back into exactly the same community 

environment, the same temptations, the same limited parole supervision system, the same 

social networks, and the same service environment they were in when they were using 

drugs previously. It is as if the justice system expects change to occur miraculously 

simply from the disruption provided by a brief imprisonment. 

In addition, as we described in Chapter III, DAPO estimates that 85 percent of all 

recorded violations require mandatory referral to the parole board and the parole board, in 

turn, returns to prison 80 percent of those cases. The percentage of cases being returned 

to prison by the Board of Parole Hearings (BPH) has been steadily increasing over the 

past decade, from around 60 percent in the 1980s to 80 percent today. Parole agents—the 

individuals who work closest to parolee and are most knowledgeable about community 

resources that might aid a parolee’s reintegration—often have little say in the ultimate 

response to a violation. In fact, parole agent discretion has significantly diminished in 

recent years in California as a result of several mandatory regulations covering caseload 

assignment, conditions of supervision, and the mandatory reporting of parole violations. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The parole board operates with a relatively low standard of evidence (“preponderance of 

the evidence”), fewer procedural protections, and bears the ultimate responsibility for a 

parolee who is allowed to remain in the community. The board has both the 

accountability for decisions gone bad and the discretion to re-imprison offenders. It 

should come as no surprise that it seemingly operates under the principle of “when in 

doubt—incarcerate,” even if it is for a short period. The parole board is also limited by a 

lack of intermediate or graduated sanctions—options other than prison for a given parole 

violator. However, this is another area where the department has made some positive 

steps, increasing its community drug treatment beds by 40 percent, to nearly 7,000 in 

2007. Unfortunately, they have thus far been unable to provide such options on the 

massive scale needed. In many cases, prison remains the first, last, and only response to 

violations. 

In addition, California has politicized its correctional laws and policies, which make 

structural change difficult. The punitive approach to corrections, ushered in with the 

determinant sentencing law, is highly resistant to change because it is built upon support 

from the public, politicians, and interest groups. Public fear of criminals is easily 

mobilized to support ever-more severe sanctions, routinely the subject of ballot measures 

in the state. Legislators on both the right and the left have found tough on crime stances 

politically attractive. Elected officials, including a Republican governor, who favor 

rehabilitation or a change in the existing system risk being labeled “soft on crime.” The 

correctional officers union often actively opposes changes that threaten jobs for prison 

guards and parole officers. In addition, parole board commissioners who manage the civil 

service deputy commissioners and who oversee most of the revocation cases, are political 

appointees. These factors mean that significant structural changes that could shrink parole 

and prison populations are often not politically possible. 

In this chapter, we put aside the organizational, structural, and political issues in favor 

discussing how our key findings relate to specific policy initiatives, including several that 

are currently under consideration or being implemented by the department. We describe 

specific policy issues that our findings directly or indirectly address. We conclude with 

some suggestions for future research that will build on the research presented in this 

report. 

Concentrate Supervision and Services on the First Six Months 

In Chapter V we showed that risks for all kinds of violations peaks within the first ninety 

days of parole and diminishes sharply until the 180th day (or the end of six months), 

where it begins to level off. The reason the risk falls is that the most risk-prone parolees 

tend to be violated earlier and returned to custody. The remainder are more compliant, 

less likely to violate, and more likely to successfully complete their parole period. While 

the data do not indicate a specific time threshold, 63% of the individuals who will violate 

have violated by the sixth month. The implication is that changing behavior through 

intensive supervision and provision of appropriate services in the first six months will 

have the biggest impact in reducing violations, which is in line with recent research by 

the National Research Council of the National Academies (2007). 

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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The first six months are a critical time and should generate the most intensive supervision 

and greatest emphasis on services designed to enhance reintegration. In accordance with 

the “risk” principle, the highest risk parolees, determined by a validated actuarial risk 

assessment instrument, programs should be targeted for the most intensive interventions 

and should be separated from lower risk parolees in programs. Substance abuse and 

mental health services are particularly important since both conditions involve 

considerable adjustment challenges for many parolees. For high-risk offenders whose 

criminogenic needs do not involve mental health and substance abuse issues the focus 

should be, first and foremost, a cognitive behavioral program designed to alter the 

patterns of thought and habits that lead them to criminal behavior and, secondarily, to 

programs that attend to employment skills and educational deficits. For high risk parolees 

who are resistant to participating in programming, motivational interviewing should be 

applied. 

Parolees who reach the 180th day with few or no violations should be “stepped down” in 

terms of supervision level—as they frequently are under the present system—or 

discharged (see below). If services are scarce, parolees who are beyond the 180th day 

should be de-prioritized in terms of service provision. 

Expand Use of Early and Earned Parole Discharge 

The same temporal pattern of violations that justifies the concentration of services and 

supervision within the first six months also justifies the expanded use of early or earned 

parole discharge. Parolees who perform well on parole for a year are currently eligible to 

be discharged, although only a small number of those eligible actually benefit from the 

policy (about 17,000 out of approximately 127,000 parolees discharge at their 13

th month 

each year, or 13 percent). Our findings suggest that there are many parolees who have 

performed well in the first year of parole and pose quite low risks to commit violations in 

the second and third years of parole. These parolees could be released without 

significantly increasing risk to the public safety and the savings accrued could be 

reallocated to more closely supervising high-risk parolees. Our findings suggest that it is 

possible to identify those individuals as early as six months to determine which parolees 

would be good bets to be violation-free at 12 months and thus could be discharged even 

earlier than the 13

th 

month. 

Ideally, the lowest risk parolees might not be assigned to parole supervision at all, 

although this may be politically difficult. Instead, there has been some discussion of 

implementing a form of parole called “summary parole” that would be for the lowest risk 

offenders or offenders who have surpassed the sixth or twelve month threshold with few 

or no violations. As it has been discussed by parole officials, summary parole involves 

even less supervision than “Minimum Supervision.” A parolee on summary parole would 

not be supervised by a parole agent, however, they would still be subject to parole search 

standards and if found to have committed a parole violation could be returned to prison 

by the parole board. California Penal Code § 3067 stipulates that all paroled felons must 

submit to unannounced searches and seizures by a parole agent or peace officer at any 

time. For this reason, law enforcement officials and legislators favor summary parole 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
instead of earned parole discharge. Moderate risk offenders might be assigned a year or 

two of parole, whereas high-risk offenders might serve two years or more, and very high 

risk might be assigned an indeterminate period, depending upon their risk. 

Align Parolee Risk and Supervision Levels 

Risk assessment is relatively easy to adopt, but more difficult to embed in the daily 

routines of parole supervision and treatment. During the period of our study, there was no 

actuarial risk assessment used in parole. Supervision levels were determined by the 

simplistic grid system described in Chapter III. Currently, COMPAS assessments are 

devised for many parolees, but they do not routinely drive supervision intensity and/or 

case management. In fact, the old assessment grids are still in use. As we showed in 

Chapter V, there is a misalignment between who is supervised intensively and who truly 

poses the greatest risks. To a large degree this is because of policies that deem certain 

categories of parolees (serious, violent, Sex Offender Registrants, Second Strikers) as 

most in need of supervision despite the fact that those categories are not predictive of 

higher risks of violations, even the most serious violations. An implication of our analysis 

is that misalignment of risks to supervision levels leads to an overreporting and detection 

of the violations of the least risky parolees and an underreporting of the violations of the 

most risky parolees. As many other states have done, California needs to use its risk 

assessments to drive supervision intensity and minimize circumstances where it 

oversupervises and undersupervises parolees relative to the risks they pose. 

In other words, parole services and surveillance should be primarily risk-based rather 

than offense-based. CDCR needs to assign parole caseloads and supervision levels so that 

offenders are “matched” to types of surveillance most appropriate for them. Supervision 

resources should be more heavily focused on higher-risk parolees, and very intensive 

(and expensive) supervision levels should be reserved for those whose risk profiles are 

the highest. 

Employ a Parole Violation Decision-making Matrix 

A central finding in Chapters V and VI is that violations and revocations vary across 

parole agents, organizational subunits, and communities. For example, Chapter V 

provided evidence that parole agent characteristics explain some of the variation in 

certain types of violations. Chapter VI showed that decisions by the parole board to 

return a parolee to prison are influenced by the regional and community factors and 

organizational pressures like how much crowding exists in the reception centers. These 

findings suggest that how a parolee is dealt with varies across location in the system and 

that the same parolee with the same background may receive different treatment for the 

same violation. One solution that is currently underdevelopment is to use a violation 

matrix, sometimes called a “sanctioning grid,” to render decision-making more uniform 

across different locations and levels within the system. 

The parole division will pilot such an instrument in September 2008. The instrument was 

developed in collaboration with the Center for Effective Public Policy (CEPP) in 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Washington D.C. Based on our research for this project, we participated in the early 

planning stages of the matrix and consulted with parole executives about its 

implementation. The proposed matrix is based on the idea that decisions about parole 

violations should be limited to two relevant criteria 1) how much risk the parolee poses to 

recidivate further and 2) the severity of the behavior involved in the violation. The risk is 

determined by an actuarial risk assessment instrument, developed by the University of 

California at Irvine’s Center for Evidence-Based Corrections and modeled after the 

Washington State Department of Corrections risk assessment instrument. For criminal 

offenses, the severity of the violation behavior, will be rooted in the FBI Uniform Crime 

Reporting system’s crime severity index. For noncriminal “technical” violations, based 

on our research, we recommended that the parole division undertake a study, like the 

present study, but one that could follow parolees who have committed technical 

violations for up to six or seven years. The purpose of the research would be to determine 

the predictiveness of committing any one of 22 noncriminal technical violations on 

criminal behavior. The research would be able to help determine which technical 

violations are and are not associated with future criminal violations. Technicals are 

understood to be problematic, not because they constitute threats to the public in and of 

themselves, but because they are predictors of future criminal behavior. This represents 

an empirically testable assumption and a research project with a long enough time frame 

and a large enough sample could help identify the technical offenses that predict criminal 

behavior. The findings could indicate one of three possibilities for a given type of 

violation: a) the violation does not predict future criminal involvement, b) it does predict 

violations, or c) it predicts some kinds of criminal violations but not others. As we have 

done in this study, we propose breaking violations into levels of seriousness. Depending 

upon the risk dimension, if a particular violation does not predict further criminal 

behavior than the grid would specify the lowest level sanction. If it predicted Type I 

criminal violations, most of which are drug use and drug possession violations, then a 

moderate level of sanctioning would be appropriate. If it predicted the most serious Type 

III criminal violations, then the highest level of sanctioning would be applied. This would 

build on what we have done in the present study and we have begun discussions about 

this project with the parole division. 

Thus far the violation matrix has been developed for use by parole agents and their 

supervisors. The parole board has not and is not planning to develop a similar decisionmaking instrument but their buy-in to DAPO’s decision-making matrix will be critical if 

it is to be used effectively to divert parole violators from prison, since they control the 

ultimate decision to retain a parole violator in the community rather than returning them 

to prison. Our research suggests that the effectiveness of such a tool will be limited if it is 

only applied by parole. As we discussed in Chapter VI, over 80 percent of parole 

violations are, by virtue of the administrative regulations (i.e., Robin Reagan rules), 

mandatorily referred to the parole board. This means that in the vast majority of instances 

in which the matrix is applied it will constitute only a recommendation, not an action. 

The action in mandatory referrals is the province of the parole board. This renders the 

matrix less of a decision tool and more of an advisory tool. Unless the parole board also 

adopts the instrument there will likely continue to be a heavy reliance on imprisonment, 

as opposed to intermediate sanctions. 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
If both parole and the parole board rely on the violation matrix and if decision-makers 

minimize departures from the matrix, there is significant promise that such a tool will 

reduce the variation that we observe in how violations are handled. This decision-making 

tool would allow responses to violations to be more fair and consistent throughout the 

agency, based on a common set of guidelines that provide a set of options appropriate to 

offender risk level and the seriousness of the violation. While each individual case must 

be assessed, responses to violations should be viewed as impartial and consistent with 

rules and shared logic. Similar decisions made for similar situations increases compliance 

of parolees, whereas dramatically different responses from officer to officer undermine 

trust and legitimacy of the system. Such a system also structures the efficient use of time, 

resources, and supports the agency working toward a common purpose. 

Expand Intermediate Sanctions Options 

A violation matrix, of course, depends upon the development, training, and 

implementation of a wider range of intermediate sanctions than are currently available to 

parole decision-makers. If the matrix contains only the options we examined in the 

present study—continue on standard parole supervision or reimprison—it will obviously 

have less impact on the volume of parole violators returning to prison. Thus, the CDCR 

must implement additional intermediate sanction programs (ISPs), which are mid-range 

punishments that lie somewhere between routine parole supervision and imprisonment 

with respect to their restrictions and costs. Current parole program offerings are simply 

inadequate to appropriately sanction the wide range of parole violations in California. For 

many parolees, prison is too severe a punishment whereas routine parole is often too 

lenient. We need program and penalty options that are mid-range (hence the term 

“intermediate”). The expansion of evidence-based intermediate sanctions, particularly for 

drug-involved parolees, should both reduce recidivism and save expensive prison beds 

for the most violent criminals. CDCR cannot do this alone, as the most effective reentry 

programs and intermediate sanctions require active community engagement and 

collaboration. 

The call for intermediate sanctions is not new. Beginning in the 1980s, a coalition 

emerged among academics and corrections officials, which argued that intermediate 

sanctions better served victims and the justice system than did indiscriminate 

imprisonment. Between the years 1985 and 1995, every state adopted some form of 

intermediate sanctions for adult and juvenile offenders, often with a great deal of 

ceremony. The most popular ISPs were day reporting centers, drug testing, electronic 

monitoring, house arrest, and intensive supervision. These programs were all designed to 

be community-based sanctions that were tougher than regular parole or probation but less 

stringent and expensive than prison (for a complete review, see Petersilia 1999). 

ISPs developed during this period reflected the conservative philosophy of the times. 

Rehabilitation had been discredited, and the nation had declared a war on drugs and 

crime. Intermediate punishments were proposed as sanctions that were tough on crime 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
and criminals, but without the costs of prisons. Most of the ISP programs implemented 

during this period emphasized stringent conditions and monitoring rather than treatment. 

Typical requirements for offenders in ISP programs were more frequent meetings with 

correctional agents, randomized and frequent urine tests, unannounced home visits, and 

verified employment. Theoretically, ISPs were based principally on notions of 

deterrence--that increased surveillance and the threat of reincarceration would convince 

offenders’ to stop their criminal activity. 

Many of these programs were evaluated and there now exists a substantial body of 

research on their impacts. MacKenzie (2006, p. 322) recently summarized this literature 

and concluded that: 

“A large body of research, including random assignment studies, consistently 

shows the failure of intensive supervision and electronic monitoring programs to 

lower recidivism. Restraining offenders in the community by increasing 

surveillance and control over their activities does not reduce their criminal 

activities. In general, program participants recidivate as often as their counterparts 

who receive less surveillance. The increased surveillance may actually increase 

the probability of detection and thus, result in more technical violations.” 

There was some evidence, however, that increased treatment of offenders in ISP may be 

related to significant reductions in rearrests. For example, Petersilia and Turner (1993) 

reported a 10-20 percent reduction in recidivism for those offenders who were most 

active in programs while they were in the community. The most important finding from 

the intermediate sanctions literature is that programs must deliver high “doses” of both 

treatment and surveillance to assure public safety and reduce recidivism. Treatment alone 

is not enough, nor is surveillance by itself adequate. 

MacKenzie (2006) also found that effective ISP programs focused on individual-level 

change. In contrast, she notes that the ineffective ISP programs focused solely on 

developing opportunities (e.g., life skills and work programs). She writes that the “what 

works” literature suggests that programs that attempt to increase opportunities must be 

preceded by programs focusing on changing the individual through cognitive change, 

education, or drug treatment. 

There is now sufficient evidence to design a second generation of evidence-based 

intermediate sanction options. We know what programs do and do not hold promise for 

reducing criminal activity. If we build those programs into California’s parole violation 

matrix, we have an important opportunity to target our scarce resources to program 

interventions that enhance both the lives of parolees and the public’s safety. 

Encourage Criminal Prosecution When New Parolee Felonies Are Alleged 

A key finding of Chapter VI was that there are several factors that affect whether a 

criminal violation case is handled by the parole board or a county court. Readers might be 

surprised to learn that a large number of very serious crimes were handled by the parole 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
board instead of processed in a criminal court. As explained in Chapter VI, California has 

a system quite unlike that in other states, in that it permits the parole board to handle the 

processing of new serious felonies by parolees through its informal revocation process. In 

most other states, parolee new crimes are handled primarily through the criminal courts, 

where the state’s criminal code and sentencing structure apply. The criminal court versus 

the parole board is particularly used if the alleged crime is quite serious. But in 

California, the parole board and the parole revocation process is used in lieu of criminal 

prosecution for thousands of offenders who parole officials believe have committed new 

and very serious crimes. As shown in Table 6.4, during 2003-2004, the parole board 

returned to prison 246 parolees who were alleged to have committed murder, 1,006 

alleged to have committed robbery, and 691 parolees for rape and serious sexual assault. 

California’s system allows some very serious criminals to evade the more severe criminal 

penalties that would have been imposed had their cases been criminally prosecuted as 

opposed to handled by the parole board, where the maximum term imposed was only 

twelve months. For example, parolees returned to prison by the parole board for the crime 

of homicide served an average of 9.9 months, whereas those convicted of homicide in the 

criminal courts served 91 months for homicide. Similarly, parole violators returned to 

prison for robbery served 9.6 months vs. 53 months served if convicted in criminal court 

of robbery, and parolees returned for alleged rape and sexual assaults served 8.6 months 

vs. 45 months served if convicted in criminal courts.

73 Of course, there is no way to 

“match” the seriousness of the crimes being processed through the different routes, but 

the resulting prison penalties are so different that the process deserves closer scrutiny. 

Jeremy Travis, one of the nation’s leading parole scholars, testified about this issue 

before California’s Little Hoover Commission. He asked the critical question: “Why were 

these cases classified as “homicide” handled through the revocation or parole process, 

with a maximum prison sentence of a year, rather than through the traditional prosecution 

route? Has California simply created a parallel system of criminal adjudication, with 

lower burdens of proof and lesser adversarial processes? Why should these criminal 

events be adjudicated in a process where the maximum prison term is one year?” (Travis 

2003) If they charged with such crimes, they should be prosecuted to the full extent of the 

law in criminal courts. If they cannot be criminally charged with the crime, then using 

parole revocation, with its lower standards of proof of guilt, may result in innocent 

parolees being returned to prison. 

Of course, we understand that there are many considerations that influence which 

criminal cases the district attorney chooses to prosecute, including the availability and 

credibility of witnesses, and whether the difference in prison time between a conviction 

and a revocation sentence is substantial enough to warrant the cost of prosecution. But in 

these more serious crimes, it appears that the resources and investment spent in case 

preparation may well result in a significantly longer prison term for serious criminals if 

the case is criminally prosecuted. We endorse the recommendations made by both the 

73 California Department of Corrections and Rehabilitation, California Prisoners and Parolees 2004, Table 

47A, “Total Felons, First Releases to Parole By Offense and Time Served,” 2005, Sacramento, CA. 

123


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Little Hoover Commission (2003) and the California Independent Review Panel (2004) 

that urge greater analysis of the reasons why so many serious crimes are being handled 

through the parole revocation process. It is our belief that if a parolee commits a new 

crime, he should be prosecuted for that crime if at all possible. In fact, if a parolee is 

convicted of a new crime, his or her penalty should be enhanced to reflect the fact that the 

crime was committed while on parole. “True” technical violations – which are violations 

of the condition of parole and do not involve criminal behavior – should be handled at the 

local level under a system of graduated, intermediate sanctions. California is again using 

its resources unwisely because it fails to sort offenders and crimes according to risk. 

California’s policies are simultaneous too harsh and too lenient. At the high end of the 

risk and offense seriousness continuum, parolees who commit serious crimes are often 

given a “discounted” sentence over what would be imposed for a criminal conviction. 

One parolee actually told one of us during an interview that, “It is a good time to commit 

crime if you are on parole. If I weren’t on parole, I would have to be prosecuted for a new 

crime. But since I am on parole, they usually just send me back to prison as a parole 

violator, where the term is a maximum of twelve months and I will do about half that— 

six months, tops. Being on parole is kind of like an insurance policy against being fully 

prosecuted.” California has created, de facto, a system that sometimes discounts rather 

than enhances, the new crimes of parolees. 

At the low-end of the seriousness continuum, California is probably too harsh. It 

continually violates parolees who have not adhered to the terms and conditions of their 

parole, and they serve almost the same number of months back in prison as parolees who 

are returned for new criminal violations (5.4 months for administrative criminal returns 

vs. 4.3 months for administrative non-criminal returns). While administrative violations 

must be taken seriously and the parolee should be held accountable, an expensive prison 

bed is not the only viable sanction. The state of Washington has enacted legislation 

limiting the amount of time a parolee can be revoked for a technical violation to 60 days. 

In addition, technical parole violators in that state are detained in county jails rather than 

in state prisons. Austin and Fabelo (2004) report on initiatives of paroling authorities in 

Connecticut, Kentucky, Maryland, New Mexico, and Texas, where—using research 

based tools—advances have been made in reducing admissions as a result of parole 

violations and reducing prison populations.

74 

Further, we found evidence that stresses on the capacity of California’s justice system— 

as measured by jail and prison overcrowding and district attorney caseloads—resulted in 

greater likelihoods that the parole board would handle criminal violation cases. While 

case and offender characteristics are more appropriate criteria for board referral 

decisions, system capacity should not affect these decisions. If parolees who commit 

serious new crimes were more frequently prosecuted in criminal courts whenever 

possible, this would also reduce the volume of cases that are handled by the parole board. 

Track Extra-legal Factors Affecting Revocation 

Austin, James and Tony Fabelo. 2004. The Diminishing Returns of Increased Incarceration: A 

Blueprint to Improve Public Safety and Reduce Costs. Washington, DC: The JFA Institute. 

124


74 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
In Chapter VI, we found that parole violators who were black were more likely to 

experience referral to the parole board, and more likely to be returned by the board for 

certain types of violations. Moreover, we found that parolees returning to more heavily 

black communities and communities with high black unemployment rates were also more 

likely to have their cases handled by the parole board and more likely to be returned to 

prison. Consistent with research literature on communities and crime we interpreted these 

factors as measures of community racial threat. For each one percent increase in a 

community’s proportion of black residents, there is a one percent increase in the 

likelihood of prison return for a criminal violation. For each one percent increase in a 

community’s black unemployment rate, there is a two percent increase in the likelihood 

of reincarceration for a criminal violation, a four percent increase in the likelihood of 

reincarceration for an absconding violation, and a two percent increase in the likelihood 

of reincarceration for a technical violation not involving absconding. 

In addition, we found that higher concentrations of mental health and substance abuse 

service providers in a community are predictive of more lenient case outcomes. The more 

services that exist near a community, the less likely it is that a parolee from that 

community will be returned to custody by the board for a criminal or a technical violation 

not involving absconding. This is good news in that it suggests that if communities are 

able to fund and implement intermediate sanctions, parole agents and other decisionmakers are willing to use them as alternatives to reincarceration. On the other hand, these 

results suggest that parolees from communities with relatively more services face a lower 

probability of being returned to prison, all other case and background characteristics held 

constant. 

While none of these findings is sufficient evidence of bias among decision-makers, which 

as our examples illustrate can operate both for and against the parolee, further 

investigation with different data would be necessary for that conclusion, it is something 

that should provoke concern. We recommend that the CDCR should develop better 

evaluation methods to reduce the influence of extra-legal factors—particularly parolee 

race—on violation case outcomes. The state must explore the causes and consequences of 

the influence of community and personal characteristics on sanctioning decisions. 

Expand Substance Abuse and Mental Health Programs 

As Chapter V shows a substantial amount of violations are drug use and possession. 

Combined methamphetamine, heroin, and cocaine use and possession make up 75 

percent of Type I criminal offenses (the most common type of violation), 44 percent of 

criminal violations, and 29 percent of all violations. This likely underestimates the 

pervasiveness of parolees with substance abuse issues because it doesn’t include violators 

caught for sales and trafficking violations and property offenses, who are highly likely to 

also have substance abuse problems. This is an enormous population whose violation 

behavior is unlikely influenced by “catch and release” policies. For them, parole has 

become a poorly functioning drug treatment agency, something that does not appear to be 

a core competence of the agents or the agency. These individuals could potentially be 

better served by an expansion of drug treatment, possibly overseen by a self-identified 

drug treatment agency. 

125


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
California has some recent positive experience with a program that has some of the 

elements that are needed. In the late 1990s, California legislators funded a statewide, 

community-based program intended to reduce parolee recidivism. Overseen by DAPO, 

the Preventing Parolee Crime Program (PPCP) program provided literacy training, 

employment services, housing assistance, and substance abuse treatment to tens of 

thousands of parolees. An external evaluation was conducted by Zhang and his 

colleagues (2006), and the results showed modest reductions in reincarceration and parole 

absconding. PPCP participants, as a whole, had a recidivism rate 8 percentage points 

lower than on-PPCP parolees (45% vs. 53%). Moreover, increasing levels of immersion 

in the PPCP services was associated with even lower return-to-prison rates. Multivariate 

logistic regression was used to control for preexisting differences between the PPCP 

participants and the non-PPCP control group, and the results still confirmed a statistically 

significant benefit from PPCP participation and reduced reincarceration and absconding 

(Zhang et al. 2006).

75 The researchers used these findings in a cost-benefit analysis and 

found that even with the relatively small differences in recidivism outcomes, the PPCP 

has created the potential for substantial long-term savings for California taxpayers. 

PPCP’s positive effects were strongest for parolees who completed their services. These 

positive results have been used to expand the program, tailoring more of the services to 

those with certain risk/need profiles. 

Similarly, parolees with mental health issues are much more at risk to commit violations. 

Individuals who are designated as “CCCMS” (Correctional Clinical Case Management 

Services) and “EOP” (Enhanced Outpatient), which are different levels of mental health 

services, have 36 percent higher risks of all kinds of violations. They have 41 percent 

higher risks of absconding, 70 percent higher risks of technical violations other than 

absconding, 32 percent higher risks of criminal violations, and 52 percent higher risk of 

the most serious violent violations. Moreover, these individuals make up about 20% of 

the parole population. Although some mentally ill parolees are placed on specialized 

caseloads with parole agents who become very knowledgeable about how to handle such 

cases, most parole agents are not specifically trained to deal with mental ill offenders. 

The lack of intermediate sanctions means that when mental ill offenders have their parole 

revoked they are removed from the community, disrupting any treatment they may be 

receiving. David Farabee at the UCLA’s Integrated Substance Abuse Programs research 

shows that parolees who sustain outpatient mental health treatment over a period of 

several months have significantly higher chances at succeeding on parole.

76 His research 

indicates that the Mental Health Transitional Case Management program, which manages 

the transition from prison to community clinics for mentally ill parolees, has had 

75 Zhang, Sheldon, Robert Roberts, and Valerie Callanan, Preventing Parolees From Returning to Prison 

Through Community-Based Reintegration, Crime & Delinquency, Vol. 52, No. 4, October 2006, 551-571. 

76 Farabee, David, Dave Bennett, David Garcia, Uma Warda, and Joy Yang. Third Annual Report of the 

Mental Health Services Continuum Program of the California Department of Corrections and 

Rehabilitation—Parole Division. Research Report Submitted to the California Department of Corrections 

and Rehabilitation—Parole Division., June 30, 2005. 

126


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
demonstrable successes, but that there are many more individuals who could benefit from 

it.

77 

Parolees with substance abuse issues and those with mental health issues account for the 

single largest segment of the parole population and, as our research indicates, an even 

larger segment of all violations. These are individuals that are particularly ill-served by 

catch and release policies. Reception centers don’t have the programs and the parolees 

returned by the board don’t have sufficient time in custody, even if the programs did 

exist. The alternative is to expand substance abuse and mental health program 

opportunities in the community and intensify the transitional case management that is 

necessary to keep parolees in such programs.

78 

Future Research Recommendations 

In the course of conducting this research, we have developed a number of ideas that can 

guide future research about parole. These ideas can be divided into two categories: 

improvements to future studies that are similar to ours, and ideas for related studies. In 

this section, we will address each of these categories in turn. 

Improvements to our design 

Our study was innovative in that we included predictive measures reflecting multiple 

“levels” of influence—case, individual, organizational, and community. This 

comprehensive approach went much further than prior research on violations and 

revocations, but some of the specific measures we utilized could be improved, and others 

could be added. 

We used a wide range of individual-level measures to predict violation and revocation 

patterns. Most of these reflected demographic and criminal-legal characteristics that, in 

theory, could predict these outcomes. However, our empirical analyses and discussions 

with correctional officials indicated that there were other factors, which we could not 

measure, that may have had major effects on the outcomes of interest. Substance abuse, 

for example, emerged as a potential factor that could affect success on parole. A 

substantial amount of evidence suggests that parolees with substance abuse issues are 

among the least likely to complete parole successfully. Since many parolees are subject to 

regular narcotics testing, failing drug tests is one of the main causes of violation and reincarceration. Parolees with more serious substance abuse problems are the most likely to 

fail these tests, and they may be more likely than others to commit certain types of drug 

and property crimes in order to support continuing drug use. At the revocation stage of 

sanctioning, those with more severe drug problems may be penalized by court and board 

decision makers, who may believe substance abusing parolees pose greater threats to 

77 Farabee, David (2006). An evaluation of California’s Mental Health Services Continuum Program for


parolees. Corrections Today, 68(7), 38-41.
 78 See also National Research Council of the National Academies (2007). Parole, desistance from crime,


and community integration. Washington, DC: The National Academies Press.


127


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
public safety, or to be less likely to be able to meet the standard requirements of parole 

supervision. 

A related issue is employability. We were unable to obtain data about parolees’ 

employability and vocational backgrounds, but these factors also likely relate to success 

on parole. Parolees with poor job skills have fewer opportunities for legitimate 

employment, and may be more likely to engage in further criminal activity. At the 

revocation stage, these parolees, like those addicted to drugs, may be penalized by 

decision makers for their poor prospects. Future studies of parole violation and 

revocation should therefore attempt to explore the link between vocational skill and 

parole failure. Measures of educational attainment can be used to supplement, or stand in 

for, vocational measures. 

Other measures of social attachment may also affect parole outcomes, and we encourage 

correctional researchers to explore these areas in their work. Parolees with more stable 

family lives (i.e., married, children), for example, may be more likely to pursue 

legitimate opportunities and avoid illicit ones. Parolees who regularly socialize with peers 

who are not involved in criminal activities may also experience more success on parole, 

whereas those who associate with criminals (e.g., gang members) may have a hard time 

avoiding further sanctioning. 

Many parolees are ordered to participate in programs or services as conditions of their 

release. We were not able to obtain reliable data on program participation for our study 

sample. However, it is clear that program noncompliance can lead to violation and reincarceration. Those parolees who fail to attend or engage in required programming will 

likely draw the ire of their parole agents. On the other hand, parolees who demonstrate a 

willingness to participate in programs may gain favor with their agents. Program 

participation may also lead to improvements in parolees’ lives that can suppress further 

illicit behavior. Successful engagement with a drug treatment program, for example, may 

help a parolee overcome addiction, and quell violation behaviors associated with 

continuing drug use. 

Information about individual characteristics such as substance abuse, employability, 

family stability and program engagement—otherwise known as dynamic risk factors—is 

becoming more available as a result of the increasingly widespread adoption of risk 

assessment instruments to make supervision and service referral decisions for 

correctional populations. As these data become more accessible to researchers, future 

studies will be better able to introduce dynamic risk factors into their analyses. 

In terms of organizational variables, future research might focus on collecting better data 

on the backgrounds of parole agents. We were able to obtain basic demographic 

information about agents, as well as some information about tenure on the job and prior 

experience working in prisons, but we would also have liked to know more about the 

vocational and educational backgrounds of these parole agents. As mentioned earlier in 

this report, some research suggests that agents with social work experience will be more 

forgiving of violation behavior, while agents with law enforcement backgrounds will be 

128


This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
less forgiving. Thus, it would be useful to know the types of degrees that agents possess, 

as well as their experiences working in therapeutic and/or enforcement-oriented 

occupations. Researchers might also attempt to use data drawn from interviews or 

surveys of parole agents to create measures reflecting therapeutic and punitive attitudes. 

Administrative data, at best, can be used to develop proxies for these attitudes, but simply 

asking the agents themselves would likely yield much better information. 

Future studies 

This study was designed to generate concrete policy recommendations for the state, and 

we have been able to generate findings that are pertinent to parole policies. Future studies 

might address parole policies more specifically. Our research has generated many 

insights that can inform certain policies, such as early discharge from parole, graduated 

sanctioning systems, and the timing of service delivery. As parole data systems and 

knowledge about parole outcomes improve, it should be easier to implement studies that 

focus specifically on the potential effectiveness of various policy choices. The 

effectiveness of early discharge policies, for example, can be tested by comparing the 

arrest patterns of discharged parolees to those of parolees who were not discharged. 

Graduated sanctioning policies can be assessed through evaluation studies of their 

implementation and outcomes. Researchers can explore appropriate service options 

through analyses of program participation data and the relationship between program 

engagement and violation behavior. Our study provides some guidance for these efforts, 

but lacks the targeted analytical focus that is needed to fully understand parole policy 

choices. 

We hope that this piece of research will provide guidance for future research efforts, as 

well as the important discussion that will be taking place over the next several years 

about parole in California and the United States. 

129


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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133


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
APPENDICES


134


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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix A. Mandatory Referral Policy for Parole Violations 

Mandatory Referral to Parole Board Behavior that MAY 

•	 Any conduct described in Penal Code section 667.5(c), or any conduct described in Penal Code • Any conduct w

section 1192.7(c), or any assaultive conduct resulting in serious injury to the victim. supervisor, or 

•	 Possession, control, use of, or access to any firearms, explosive or crossbow or possession or use of sufficiently ser

any weapon as specified in subdivision (a) of California Penal Code section 12020, or any knife whether the co

having a blade longer than two inches, except as provided in section 2512. in court. 

•	 Involvement in fraudulent schemes involving over $1,000. 

•	 Sale, transportation or distribution of any narcotic or other controlled substances as defined in


division 10 of the California Health and Safety Code.


•	 A parolee whose whereabouts are unknown and has been unavailable for contact for thirty days. 

•	 Any other conduct or pattern of conduct in violation of the conditions of parole deemed sufficiently


serious by the P&CSD staff, including repetitive parole violations and escalating criminal conduct.


•	 The refusal to sign any form required by the Department of Justice explaining the duty of the


person to register under Penal Code section 290.


•	 The failure to provide two blood specimens, a saliva sample, right thumb print impressions, and


full palm print impressions of each hand as provided in Penal Code sections 295 through 300.3,


requiring specified offenders to give samples before release.


•	 The failure to register as provided in Penal Code section 290, if the parolee is required to register. 

•	 The failure to sign conditions of parole. 

•	 Violation of the special condition prohibiting any active participation or assistance in, or promotion


or furtherance of, prison gang, disruptive group, or criminal street gang activity, as enumerated in


Penal Code section 186.22(e), if such condition was imposed.


•	 Violation of the special condition prohibiting any association with any member of a prison gang,


disruptive group or criminal street gang, as defined in s 2513(e), or the wearing or displaying of


any gang colors, signs, symbols, or paraphernalia associated with gang activity, if such condition


was imposed.


•	 Violation of the special condition requiring compliance with any gang-abatement injunction,


ordinance, or court order, if such condition was imposed.


•	 Conduct indicating that the parolee's mental condition has deteriorated such that the parolee is


likely to engage in future criminal behavior.


•	 Violation of the residency restrictions set forth in Penal Code section 3003.5 for parolees required


to register as provided in Penal Code section 290.


•	 In addition, for any parolee whose commitment offense is described in Penal Code section


1192.7(c), the P&CSD shall report to the board any such parolee who is reasonably believed to


have engaged in the following kinds of behavior: any of the behaviors listed above, any criminal


conduct, any violation of a condition to abstain from alcoholic beverages.


Source: California Code of Regulations (CCR), Title 15, Division 2, Section 2616(a) and 3901.19.2. 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix B. Data and measures for the analysis of parole violations (n=254,468) 

Measurement 

Variable Definition Level 

Past and Present Offense History 

Prior Number of Returns to Prison Count of the parolee’s previous episodes of imprisonment Individual Commitment Offense Most serious offense for which the parolee was most recently Individual 

incarcerated 

Drug Offense Crime involved use, possession, sales, or trafficking of illegal drugs Individual Violent Offense Crime involved violent behavior or the threat of violent behavior Individual Property Offense Crime involved taking or damage to property Individual Sex Offense Crime involved sexual behavior or threat of sexual behavior Individual Other Offense Miscellaneous other offenses including drunk driving and weapons Individual 

offenses 

Number of violent priors A parolee’s number of prior commitment offenses defined by Individual 

California Penal Code § 667.5 (c) as “violent offenses” 

Number of serious priors A parolee’s number of prior commitment offenses defined by Individual 

California Penal Code § 1192.7 (c) as “serious offenses” 

Sex Offender Flag Parolee has committed an offense defined under California Penal Code Individual 

§ 290 (a) (2) as a sexual offense requiring registration with the California Sex Offender Registry 

Second/Third Striker As per Proposition 184 (e.g., California Three Strikes law), denotes a Individual 

parolee who has accumulated two or more “serious” or “violent” felony convictions and who are eligible for a mandatory sentence of 25 years to life for their next felony conviction 

Personal Characteristics Attributes of the parole that may be associated with risk of violation 

Black Parolee is black Individual Male Parolee is male Individual Age Parolee is between in one of three age categories: 18-30, 30-45, and Individual 

over 45 

Age at First commitment Parolees age at the time of their first commitment to the California Individual 

prison system 

Mental Health Flag Parolee has been identified as having one of three levels of mental Individual 

illness 

Supervision Characteristics 

Presently Absconded Parolee is “at large” during the observed week Individual­ 

Week 

Supervision Level Type and intensity of parole supervision IndividualThis document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Minimum Service Level 

Controlled Service Level 

High Control Level 

High Services Level 

High Risk Spec/Non-Spec 

Parole Region 

Policy 

Crawford Search and Seizure 

The New Parole Model


Workload


Parole Agent Characteristics


Male


Black
Age


Job Tenure 

Prior Prison Employment 

Community Environment 

Social Disorganization 

Reentry Supports


Public Assistance


Parolee is under a minimum level of supervision; communication with 

parole agent is mainly via mail; no drug testing 

Parolee is under a moderate level of supervision and may need services 

for drug use, mental health problems, education or employment 

deficits 

Parolee is under a high level of supervision, with an emphasis on 

detecting or preventing the most serious criminal activity 

Parolee is under a high level of supervision in which their service 

needs are to be emphasized 

Parolee is under a high level of supervision and supervised by a parole 

agent whose caseload is composed entirely of high risk parolees 

Parolee is located within one of four parole regions 

Parole Division policies adopted during 2003 and 2004 

Policy elevated the search and seizure requirements to “reasonable 

suspicion,” adopted during the period in which the Crawford case was 

being adjudicated in federal court 

Policy announced the “New Parole Model” to field staff 

The number of caseload points carried by the parolee’s parole agent 

Personal characteristics of parole agent 

Parolee’s parole agent is male 

Parolee’s parole agent is black 

Parolee’s parole agent is one of three age categories: 26-39, 39-55, and 

over 55 

Number of years a parolee’s parole agent has been on the job broken 

into three categories: Less than 3 years, between 3 and 10, and more 

than 10 

The parolee’s parole agent previously worked in prison 

Parolee resides in more or less criminogenic environment as measured 

by concentrated disadvantage (poverty, unemployment, median 

income, single headed households, and percent black), ethnic 

heterogeneity, and residential turnover 

Parolee resides in community with a more or less generous public 

assistance system as measured by the ratio of pubic expenditures to the 

Week IndividualWeek 

IndividualWeek 

IndividualWeek 

IndividualWeek 

IndividualWeek 

IndividualWeek 

Week Week 

Week Agent-Week 

Agent Agent Agent Agent 

Agent 

Agent U.S. Census 

Tract 

County 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
number of public assistance recipients 

Punitiveness Parolee resides in a community that has more or less punitive attitudes County 

toward parolees as measured by voting on the 2000 Proposition 36 (drug treatment of offenders), the 2004 Proposition 66 (to limit Three strikes), and the percent Republican in community 

Religious Adherents Parolee resides in a community with greater or lesser numbers of 

religious adherents as measured by the Association of Religion Data 

County 

Archives’ Religious Congregations and Membership Study, 2000 

Substance Abuse and Mental Health Parolee resides in a community characterized by an abundance or U.S. Census Services scarcity of substance abuse and mental treatment programs as Tract 

measured by the number of the Substance Abuse and Mental Health Services Association treatment programs within fifty miles of the 

centroid of the parolee’s U.S. Census Tract 

*These measures are based upon factor analysis and other methods used to combine several variables into standardized sca

tendencies and distributions of these variables are not meaningful in and of themselves, although the measures do delineate 

are high or low on a given dimension. 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix C: Cox Regression models predicting parole violations (Hazard Ratios Reported) 

Technical 

Any Technical Violations-­ Any Criminal Crimin

Any Technical Violations-­ Other (non- Criminal Type I Type II Violations Violations Absconding PAL) Violations Violations Violati

Past and Present Offense History 

Number of Prior Returns to Prison 1.212** 1.268** 1.264** 1.279** 1.195** 1.192** 1.

(0.029) (0.021) (0.024) (0.032) (0.029) (0.030) (0

Number of Prior Returns to Prison2 0.992** 0.991** 0.991** 0.989** 0.992** 0.993** 0.

(0.001) (0.001) (0.001) (0.002) (0.001) (0.001) (0

Number of Prior Violent Commitments 1.034* 1.046* 1.067** 0.996 1.034 1.044 

(0.014) (0.024) (0.026) (0.046) (0.019) (0.023) (0

Number of Prior Serious Commitments 0.979 0.943 0.950 0.935 0.997 1.006 0

(0.023) (0.030) (0.037) (0.050) (0.027) (0.028) (0

Sex Offender Flag 0.821** 0.775** 0.708** 0.884 0.840* 0.602** 1.

(0.050) (0.074) (0.090) (0.131) (0.062) (0.063) (0

Second/Third Striker 0.903** 0.885* 0.899 0.861 0.906* 0.894* 

(0.032) (0.052) (0.060) (0.081) (0.038) (0.044) (0

Commitment Offense 

Violent 0.739** 0.857** 0.797** 0.982 0.681** 0.573** 

(0.024) (0.046) (0.053) (0.089) (0.028) (0.029) (0

Property 1.010 1.152** 1.101 1.263** 0.949 0.821** 1.

(0.029) (0.048) (0.056) (0.091) (0.031) (0.032) (0

Sex 0.631** 0.841 0.655* 1.123 0.526** 0.429** 

(0.049) (0.104) (0.113) (0.203) (0.052) (0.061) (0

Other 0.847** 0.903 0.822* 1.072 0.819** 0.696** 

(0.031) (0.057) (0.066) (0.110) (0.036) (0.039) (0

Personal Characteristics 

Black 1.036 1.068 1.083 1.043 1.017 0.897** 1.

(0.025) (0.044) (0.055) (0.073) (0.031) (0.036) (0

Male 1.256** 1.154* 1.039 1.416** 1.325** 1.137* 1.

(0.045) (0.066) (0.072) (0.145) (0.058) (0.061) (0

Age 18-30 Release 1.243** 1.362** 1.277** 1.529** 1.202** 1.125 1

(0.058) (0.078) (0.091) (0.146) (0.068) (0.072) (0

Age 45+ Release 0.742** 0.717** 0.761** 0.638** 0.732** 0.706** 

(0.034) (0.048) (0.063) (0.072) (0.039) (0.045) (0

Age at First commitment 1.010** 1.019** 1.014** 1.027** 1.006* 1.016** 

(0.002) (0.004) (0.005) (0.006) (0.003) (0.004) (0

Mental Health Flag 1.364** 1.504** 1.409** 1.697** 1.322** 1.261** 1.

(0.094) (0.082) (0.086) (0.128) (0.096) (0.090) (0

Supervision Characteristics 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
In PAL This Week 10.911 ----------- ----------- ----------- 12.480 6.932 23

(14.667) (16.762) (9.393) (30

Supervision Level 

Controlled Service Level 2.101** 2.002** 1.630** 2.954** 2.201** 2.794** 1.

(0.157) (0.143) (0.148) (0.332) (0.169) (0.301) (0

High Control Level 2.408** 2.854** 2.448** 3.845** 2.327** 2.938** 1.

(0.313) (0.251) (0.267) (0.518) (0.311) (0.465) (0

High Services Level 2.617** 2.900** 2.453** 3.979** 2.588** 2.922** 1

(0.303) (0.421) (0.441) (0.997) (0.356) (0.479) (0

High Risk Spec/Non-Spec 2.239** 2.582** 2.071** 3.886** 2.147** 3.058** 

(0.234) (0.225) (0.223) (0.536) (0.242) (0.382) (0

Parole Region 

Region 1--Central Valley 1.142* 0.812* 0.825 0.782 1.359** 1.511** 

(0.072) (0.085) (0.108) (0.137) (0.106) (0.149) (0

Region 2--Central and North Coast 1.141* 0.751** 0.779* 0.702* 1.408** 1.633** 

(0.059) (0.069) (0.088) (0.105) (0.091) (0.134) (0

Region 4--San Diego/Southeastern Counties 1.103 0.916 0.953 0.855 1.229** 1.368** 

(0.058) (0.081) (0.102) (0.124) (0.080) (0.115) (0

Workload 

PA Points 161-277 (Mean) 1.222* 1.272 1.506* 0.979 1.158 1.229 

(0.103) (0.199) (0.313) (0.234) (0.118) (0.167) (0

PA Points 277+ (Above Mean) 1.184* 1.236 1.488 0.920 1.115 1.173 

(0.101) (0.198) (0.312) (0.226) (0.115) (0.160) (0

Parole Agent Characteristics 

Male 1.028 0.902** 0.899* 0.904 1.104** 1.112** 

(0.029) (0.036) (0.044) (0.060) (0.038) (0.045) (0

Black 0.925** 0.893** 0.933 0.822** 0.943* 0.920* 

(0.021) (0.035) (0.044) (0.056) (0.027) (0.034) (0

Age 26-39 Yrs 1.055* 1.044 1.023 1.083 1.061 1.047 

(0.029) (0.043) (0.051) (0.075) (0.034) (0.040) (0

Age 56-72 Yrs 0.952 0.918 0.911 0.932 0.971 0.945 

(0.041) (0.063) (0.077) (0.108) (0.052) (0.062) (0

Tenure 3-10 Yrs 0.947* 0.964 0.956 0.978 0.936* 0.914* 

(0.025) (0.040) (0.049) (0.066) (0.029) (0.035) (0

Tenure 10+ Yrs 0.982 1.019 1.006 1.042 0.961 0.950 

(0.031) (0.052) (0.064) (0.089) (0.036) (0.045) (0

Prior Prison Employment 0.987 1.024 1.039 1.002 0.973 0.917* 

(0.032) (0.048) (0.061) (0.078) (0.038) (0.041) (0

Parole Policy 

Crawford Search and Seizure 1.045 0.957 0.933 1.002 1.093 1.130 

(0.104) (0.094) (0.092) (0.113) (0.113) (0.135) (0

The New Parole Model 1.160 1.300 1.326* 1.255 1.107 1.037 

(0.160) (0.176) (0.188) (0.173) (0.145) (0.137) (0

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Com

munity Environment 

Social Disorganization 

Ethnic Heterogeneity (std) 0.983 0.961 0.965 0.956 0.995 1.026 

(0.013) (0.020) (0.024) (0.032) (0.015) (0.019) (0

Concentrated Disadvantage (std) 1.024 1.051* 1.069** 1.010 1.011 1.026 

(0.015) (0.022) (0.028) (0.038) (0.018) (0.023) (0

Residential Stability (std) 1.024 1.045* 1.028 1.081* 1.014 1.012 

(0.015) (0.023) (0.027) (0.040) (0.018) (0.021) (-0

Reentry Support 

Public Assistance (std) 0.974 0.977 0.976 0.978 0.972 0.940** 

(0.013) (0.019) (0.024) (0.032) (0.016) (0.018) (0

Punitiveness (std) 1.004 0.956 0.904** 1.064 1.023 1.056* 

(0.018) (0.030) (0.035) (0.057) (0.022) (0.029) (0

% 

Church Attendance (std) 1.002 0.968 0.989 0.936 1.014 1.054 

(0.038) (0.041) (0.050) (0.054) (0.042) (0.044) (0

SA

MSA Services (std) 0.924** 0.931* 0.941 0.909* 0.917** 0.897** 

(0.018) (0.027) (0.033) (0.043) (0.021) (0.024) (0

Goodness-of-fit 

n parameters 42 41 41 41 42 42 

-2LL 133334 47844 31282 16442 86204 54527 

p (versus null model) <.01 <.01 <.01 <.01 <.01 <.01 

Standard errors in parentheses. 

* significant at 5%; ** significant at 1% 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix D: Cox Regression models predicting sexual parole violations (Hazard Ratios reported) 

Any Sex Sex Violations, Sex Violations, Violation Criminal Type II Criminal Type III 

Past and Present Offense History 

Number of Prior Returns to Prison 1.296** 1.306** 1.271** 

(0.018) (0.020) (0.039) 

Number of Prior Returns to Prison2 0.989** 0.990** 0.985** 

(0.001) (0.001) (0.003) 

Number of Prior Violent Commitments 0.991 0.999 0.941 

(0.018) (0.020) (0.048) 

Number of Prior Serious Commitments 1.000 1.001 0.994 

(0.027) (0.031) (0.054) 

Sex Offender Flag 25.216** 65.758** 2.880** 

(1.184) (4.318) (0.317) 

Second/Third Striker 1.082 1.046 1.138 

(0.046) (0.050) (0.104) 

Commitment Offense 

Violent 1.000 0.877* 1.292** 

(0.054) (0.058) (0.128) 

Property 1.156** 1.141* 1.191 

(0.055) (0.064) (0.108) 

Sex 0.760** 0.713** 1.208 

(0.039) (0.040) (0.172) 

Other 1.052 0.921 1.350* 

(0.071) (0.076) (0.159) 

Personal Characteristics 

Black 1.563** 1.555** 1.543** 

(0.055) (0.064) (0.108) 

Male 4.101** 1.814** 27.890** 

(0.618) (0.291) (14.002) 

Age 18-30 Release 1.921** 1.936** 1.499** 

(0.102) (0.122) (0.159) 

Age 45+ Release 0.585** 0.566** 0.620** 

(0.034) (0.037) (0.087) 

Age at First commitment 1.027** 1.034** 0.997 

(0.003) (0.003) (0.007) 

Mental Health Flag 2.504** 2.484** 2.614** 

(0.085) (0.098) (0.180) 

Supervision Characteristics 

In PAL This Week 5.057** 7.336** 1.300** 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
(0.179) (0.298) (0.112) 

Supervision Level 

Controlled Service Level 1.602** 1.789** 1.813** 

(0.133) (0.213) (0.210) 

High Control Level 2.914** 3.331** 2.469** 

(0.235) (0.373) (0.322) 

High Services Level 3.376** 4.092** 3.230** 

(0.551) (0.859) (0.861) 

High Risk Spec/Non-Spec 2.768** 3.288** 2.621** 

(0.230) (0.376) (0.348) 

Parole Region 

Region 1--Central Valley 1.440** 1.371** 1.798** 

(0.068) (0.075) (0.165) 

Region 2--Central and North Coast 1.325** 1.301** 1.496** 

(0.061) (0.069) (0.139) 

Region 4--San Diego/Southeastern Counties 1.281** 1.316** 1.219* 

(0.059) (0.069) (0.115) 

Goodness-of-fit 

n parameters 24 24 24 

-2LL 77358 53770 221693 p(versus null model) <.01 <.01 <.01 

Standardized coefficients reported. Standard errors in parentheses. 

* significant at 5%; ** significant at 1% 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix E: Independent variables in revocation models, with descriptive statistics (n=151,750) 

Category Case Case Case Case Case Case Case Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Individual 

Organizational 

Organizational 

Organizational 

Organizational 

Community (county) 

Community (tract) 

Community (tract) 

Community (tract) 

Variable 

Case contains non-PAL technical violation 

Case contains PAL violation 

Number of criminal charges in case 

Number of non-PAL technical violations in case 

Number of PAL violations in case 

Total criminal charge severity of case, divided by 100 

Total technical charge severity of case, divided by 100 

Number of lifetime prison spells 

Drug commitment offense 

Violent commitment offense 

Property commitment offense 

Sex commitment offense 

Other commitment offense 

Second/third striker 

Serious or violent offender 

Registered Sex Offender 

Male gender Race/ethnicity: White 

Race/ethnicity: Black 

Race/ethnicity: Hispanic 

Race/ethnicity: Asian 

Race/ethnicity: Other race 

Age 18-30 Age 31-45 Age over 45 Age at first commitment to California prison 

Officially documented mental health problem 

Case is in Los Angeles CDC reception center, percent occupied 

County jail population, percent occupied 

Felony court caseload divided by number of DAs 

“Punitiveness” factor 

“Concentrated disadvantage” factor 

Percent black residents in tract 

Percent black unemployment in tract 

Descriptive Statistic 

35.8% Perce

31.3% Perce

1.8 Mean 

0.7 Mean 

0.4 Mean 

6.1 Mean 

0.7 Mean 

3.4 Mean 

35.2% Perce

17.2% Perce

33.7% Perce

3.7% Perce

10.2% Perce

16.3% Perce

17.3% Perce

6.8% Perce

91.2% Perce

35.4% Perce

31.0% Perce

30.2% Perce

0.7% Perce

2.7% Perce

34.6% Perce

51.7% Perce

13.7% Perce

30.0 Mean 

32.7% Perce

22.1% Perce

236.9% Mean 

104.1% Mean 

80.1 Mean 

Based upon a factor score* Mean 

Based upon a factor score* Mean 

6.6% Mean 

7.0% Mean 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Community (tract) Percent of poor households receiving public assistance 5.9% Mean

Community (tract) Count of SAMHSA services within 50 miles of tract 83.6 Mean

*These measures are based upon factor analysis and other methods used to combine several variables into standardized sca

tendencies and distributions of these variables are not meaningful in and of themselves, although the measures do delineate 

are high or low on a given dimension. 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix F: Logistic regression model predicting return to custody from court (Odds Ratios reported) 

Return to prison from court (PVWNT) 

Violation Case Characteristics 

Number of Charges in Case 1.006 

(0.005) 

Total Criminal Charge Severity (/100) 1.083** 

(0.001) 

Past and Present Offense History 

Number of Prior Returns to Prison 1.068** 

(0.002) 

Commitment offense 

Violent 0.810** 

(0.023) 

Property 1.220** 

(0.021) 

Sex 0.837** 

(0.055) 

Other 1.242** 

(0.032) 

Second/Third Striker 1.451** 

(0.038) 

Serious/Violent Offender 0.829** 

(0.022) 

Sex Offender Flag 0.761** 

(0.025) 

Personal Characteristics 

Male 0.962 

(0.028) 

Race/Ethnicity 

Black 0.853** 

(0.017) 

Hispanic 1.039* 

(0.019) 

Asian 1.237* 

(0.126) 

Other race 1.143** 

(0.057) 

Age Group 

Age 18-30 at Release 1.172** 

(0.027) 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Age 45+ at Release 0.999 

(0.032) 

Age at First Commitment 0.998 

(0.002) 

Mental Health Flag 0.945** 

(0.017) 

Organizational Characteristics 

Case is in Los Angeles 1.822** 

(0.056) 

CDCR Reception Centers: % Occupied 0.996** 

(0.001) 

County Jails: % Over/Under Capacity 1.013** 

(0.001) 

Felony Court Caseload/ # DAs 0.997** 

(0.001) 

Community Environment 

Punitiveness (std) 1.346** 

(0.017) 

Concentrated Disadvantage (std) 0.969** 

(0.010) 

Percent Black Residents (std) 1.031** 

(0.003) 

Percent Black Unemployment (std) 1.011* 

(0.005) 

Public Assistance (std) 0.967* 

(0.014) 

SAMHSA Services (std) 1.008** 

(0.002) 

Goodness-of-fit 

n parameters 29 

-2LL 124,462 p (versus null model) <.01 

Observations 122,067 

Standard errors in parentheses. 

* significant at 5%; ** significant at 1% 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Appendix G: Logistic regression models predicting return to custody through the parole board (Odds Ratio

Criminal Criminal Criminal 

Criminal Violations, Violations, Violations, Abscond

All Violations violations Type I Type II Type III Violatio

Violation Case Characteristics 

Number of Criminal Charges in Case 0.956** 1.143** 0.130** 0.789** 1.183** 0

(0.011) (0.015) (0.010) (0.024) (0.033) (

Number of Non-PAL Technical Violations in Case 1.908** 1.889** 2.767** 1.555** 0.991 1

(0.078) (0.095) (0.257) (0.131) (0.097) (

Number of PAL Violations in Case 4.812** 3.550** 5.514** 2.892** 1.427** 

(0.214) (0.197) (0.567) (0.267) (0.158) 

Total Violation Criminal Charge Severity (/100) 1.224** 1.222** 5.604** 1.458** 1.018** 1

(0.004) (0.004) (0.280) (0.017) (0.006) (

Total Violation Technical Charge Severity (/100) 1.700** 1.823** 1.577** 2.023** 1.760** 

(0.098) (0.130) (0.215) (0.233) (0.230) (

Past and Present Offense History 

Number of Prior Returns to Prison 1.049** 1.043** 1.073** 1.006 0.999 1

(0.003) (0.004) (0.005) (0.006) (0.009) (

Commitment Offense 

Violent 1.414** 1.453** 1.904** 1.325** 0.921 1

(0.043) (0.050) (0.108) (0.078) (0.069) (

Property 1.080** 1.053* 1.040 1.115** 0.930 

(0.020) (0.023) (0.034) (0.044) (0.055) (

Sex 1.484** 1.493** 1.888** 1.441** 0.813 

(0.080) (0.087) (0.198) (0.153) (0.113) (

Other 1.292** 1.286** 1.512** 1.131* 0.918 

(0.039) (0.044) (0.084) (0.068) (0.071) (

Second/Third Striker 1.120** 1.147** 1.331** 1.046 0.973 

(0.031) (0.040) (0.068) (0.054) (0.065) (

Serious/Violent Offender 1.090** 1.098** 1.284** 1.083 0.855* 

(0.029) (0.036) (0.082) (0.060) (0.062) (

Sex Offender Flag 1.790** 2.003** 5.174** 0.828** 1.349** 1

(0.066) (0.083) (0.370) (0.050) (0.151) (

Personal Characteristics 

Male 0.996 1.041 1.015 0.957 1.268* 0

(0.030) (0.035) (0.048) (0.064) (0.129) (

Race/Ethnicity 

Black 1.058** 1.089** 1.035 1.028 0.816** 0

(0.023) (0.026) (0.040) (0.044) (0.050) (

Hispanic 1.146** 1.193** 1.235** 1.102* 1.084 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
(0.023) (0.027) (0.042) (0.047) (0.069) (

Asian 1.039 1.091 1.112 0.964 1.045 0

(0.117) (0.139) (0.244) (0.202) (0.321) (

Other Race 1.179** 1.245** 1.295* 1.225 0.955 

(0.068) (0.082) (0.132) (0.148) (0.152) (

Age Group 

Age 18-30 at Release 1.015 1.002 0.936 1.028 1.005 

(0.044) (0.045) (0.064) (0.062) (0.085) (

Age 45+ at Release 1.046 1.064 1.042 1.117 1.029 

(0.050) (0.058) (0.075) (0.089) (0.114) (

Age at First Com

mitment 0.996 0.996 0.996 0.994 0.999 

(0.003) (0.003) (0.005) (0.004) (0.005) (

Mental Health Flag 1.042 1.041 1.094* 1.021 0.975 

(0.028) (0.029) (0.044) (0.041) (0.057) (

Organizational Characteristics 

Case is in Los Angeles 0.990 1.010 0.999 0.819** 1.059 0

(0.030) (0.035) (0.053) (0.052) (0.094) (

C

D

CR 

Reception Centers: % 

Occupied 0.987** 0.987** 0.992** 0.976** 0.989** 0

(0.001) (0.002) (0.002) (0.002) (0.004) (

County Jails: % 

Over/Under Capacity 1.000 0.999 1.001 0.998 0.996 

(0.001) (0.001) (0.001) (0.001) (0.002) (

Com

munity Environment 

Punitiveness (std) 1.103** 1.081** 1.146** 1.145** 1.056 1

(0.012) (0.012) (0.021) (0.022) (0.031) (

Concentrated Disadvantage (std) 1.007 1.006 0.995 1.006 1.052 

(0.009) (0.010) (0.020) (0.018) (0.029) (

Percent Black Residents (std) 1.011** 1.014** 0.995 1.005 1.001 

(0.003) (0.003) (0.005) (0.005) (0.008) (

Percent Black Unemployment (std) 1.021** 1.020** 1.028** 1.026** 1.000 1

(0.004) (0.005) (0.007) (0.009) (0.014) (

Public Assistance (std) 1.006 1.002 1.015 1.008 1.015 

(0.014) (0.016) (0.021) (0.030) (0.044) (

SA

M

HSA Services (std) 0.987** 0.982** 0.974** 1.011* 0.986* 

(0.002) (0.002) (0.003) (0.004) (0.006) (

Goodness-of-fit 

n parameters 31 31 31 31 31 

-2LL 102,145 79,855 34,227 25,304 14,144 p (versus null model) <.01 <.01 <.01 <.01 <.01 

Observations 114,721 91,667 38,293 33,418 19,956 4

Standard errors in parentheses 

* significant at 5%; ** significant at 1% 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.