The Impact of federal reentry funding on state-level variation in reentry success and failureThe Impact of Federal Reentry Funding on State-Level Variation in
Reentry Success and Failure.
Amer Michael Akthar
A Thesis Submitted to the Department of Sociology California State University Bakersfield In Partial Fulfillment for the Degree of
Masters of Art in Sociology
Spring 2014
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The Impact of Federal Reentry Funding on State-Level Variation in Reentry Success and Failure.
Abstract Successful reentry is essential to our country, as the economic and societal costs of high
incarceration and recidivism rates are significant. Though a large body of research examines the topics of recidivism and prisoner reentry, less research focuses on the role of social context in these processes. Indeed, most research focuses on individual programs; this research is among the first to examine the cumulative effects of federal reentry spending on reentry. This research contributes to the literature by examining state-level variation in reentry success. The current study examines the role of state-level structural conditions (like poverty rates and crime) and the role of federal reentry spending on reentry success. Utilizing data from the 2006 Annual Parole Survey, the 2005 American Community Survey, the Federal Bureau of Investigation’s “UCR Online Data Tool”, and USAspending.gov, the results of the current research indicate that states which receive higher level of reentry funding see greater successes in reentry.
Federal Reentry Spending 7
Chapter Three: Research Design 18
Data 18
Methods 21
Chapter Five: Conclusion – Summary of Results 28
Limitations 31
Table 1- Descriptive Statistics for Variables (N=31 States)
Table 2- Funding for all States from 2000 to 2005 with Social Context Variables
Table 3- The Correlations of the Different Variables with Spending
Table 4- The Correlations of the Different Variables with Failure Rate
Table 5- Coefficients of the Regression Model
Chapter 1: Introduction
In 2002, more than 600,000 individuals left state and federal prisons, four times as many
as were released in 1975 (Visher and Travis, 2003). According to national data, within 3 years
almost 7 in 10 will have been rearrested and half will be back in prison, either for a new crime or
for violating conditions of their release (Visher and Travis, 2003). Hanrahan, Gibbs and
Zimmerman (2005) studied those who had their parole revoked and were now in prison and they
found that parole failure is common. Petersilia (2004) notes that completed paroles have
declined from “70 percent in 1984 to 44 percent in 1996”. Given these figures, recidivism is
clearly a problem and efforts to promote the successful reentry of offenders into society are
important to consider. There is a prevailing sentiment that there is less emphasis placed on
parole supervision and more on building more prisons, which is seen as a better way of
protecting public safety (Brewer and Heitzeg, 2008). Yet there has been a resurgence of interest
in the topic of prisoner-reentry in recent years, pushed forth by the availability of federal funds
through programs like the Serious and Violent Offender Reentry Initiative, the Federal Prisoner
Initiative, and the Second Chance Act of 2007. While a sizable body of research has examined
the individual correlates of reentry success, scholars have noted a paucity of research examining
the role of context on reentry success (Kubrin and Stewart, 2006). The goal of this research is to
explain state-level variation in reentry success and failure, focusing on the social condtext of
states on efficacy of federal reentry funding programs.
The current study explores how some states are able to successful transition ex-offenders
back into society. Every individual coming out of the prison system faces the problem of
prisoner reentry, which I define as the process of leaving prison and returning to free society.
Reentry is a challenging process for many inmates because many have been institutionalized for
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long periods of time, are accustomed to prison life, lack translatable job skills, and face the
stigma of a felony record. Readjusting to the cultural differences of life outside prison and
finding employment are two major issues facing the ex-offenders as they attempt to successfully
reacclimate to society. A wide body of research has documented the difficulties that offenders
face as they reenter society, especially in regards to finding steady and gainful employment
(Pager, 2003; Visher and Travis, 2003; Petersilia, 2001). Given that employment is often a
condition of parole for many re-entering ex-offenders, it is not surprising that large numbers of
offenders fail to successfully reenter society. The current research, which focuses on state-level
variation in reentry success, makes at least two important contributions to the reentry literature.
First, the current study addresses the role of state-level context on reentry. Reentry scholars have
noted that context is an area that has been sorely understudied in reentry scholarship (Kubrin and
Stewart, 2006). Secondly, this research describes the distribution of federal reentry funds and
evaluates their effectiveness. The federal government spends a substantial amount of money on
reentry efforts. Given the general cost of maintaining the prison system and the current budget
woes facing the United States today, it is important to know which states are receiving this
funding and to examine the degree to which federal spending influences measurable outcomes.
Given the magnitude of the reentry issue, it is unsurprising that a sizable body of research
examines the factors that predict reentry success (Anderson-Facile, 2009). Much of this research
focuses on individual-level factors and tries to explain why certain individuals fail or succeed at
reentry (Petersilia, 2001). This research indicates that factors like community cohesion and
social disorganization, work and economic well-being, family matters, mental and physical
health, political alienation, and housing and homelessness are important individual-level
determinants of reentry success (Petersilia, 2001). However, research has also shown that
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community outreach programs, either religious or social in nature, can have a positive impact on
breaking the cycle of recidivism (Visher and Travis, 2003). Although there are varying levels of
success among reentry programs, some programs have been shown to be very successful for
offenders in keeping them from reoffending and becoming reintegrated members of their
community and society. For example, research shows that programs that incorporate an aftercare
component in which ex-offenders gradually transition back into society after they have been
released are often helpful at reducing the risk of recidivism (Kurylchek and Kempinen, 2006;
Wexler, 2003). Therefore, while the picture for many inmates is bleak, there is evidence that
some factors and programs can increase the likelihood of reentry success.
While it is important to study individual and program specific outcomes, there has been
less research focusing on the role of social context on reentry success. It is possible that certain
contexts are more or less conducive to reentry success. Here, I examine state-level variation in
parole success. My primary research goal is to identify the characteristics of states that are more
and less successful at reentry efforts. To this end, I focus on two general factors: the social
conditions within a state and the availability of federal funds to address reentry. The state is a
useful level of analysis here as many federal reentry dollars have been allocated to state-level
correctional and public safety departments. Moreover, parole is typically a state-level process in
which a state Parole Board establishes the conditions of release for a given inmate and for which
a state-level agency is typically charged with overseeing.
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Chapter II: Literature Review
Scholars suggest that post prison reintegration and adjustment depends on four sets of
factors: The individual’s peers, family, the community they are released to, and state-level
policies (Visher and Travis, 2003). At the individual-level, the reentry process of those returning
home from prison are shaped by their offending and substance-abuse histories, their work skills
and job histories, their mental and physical health, their prison experiences, and their attitudes,
beliefs, and personality traits (Visher and Travis, 2003).
Offenders face many barriers to reentry. A criminal past has a great negative effect on
the individual ex-offender. Ex-offenders face not only the social stigma of a criminal conviction,
but also tremendous legal obstacles in terms of ineligibility for public and government-assisted
housing, public benefits and various forms of employment, as well as civic exclusions such as
ineligibility for jury service and disenfranchisement (Pinard, 2010). Ex-offenders must confront
many barriers preventing them from finding employment (Pager, 2003), reuniting with their
families, or securing stable housing. Employment is of specific concern, as employment at a
decent wage is strongly correlated with lower rates of reoffending (Aukerman, 2003). This is
unsurprising as ex-offenders can be given “technical violations” for failing to gain or remain
employed which can result in parole revocation. In addition to the stigma against hiring felons,
ex-offenders may also be barred from numerous professions based on their status as felons, like
health care occupations, occupations that help children, occupations that serve the elderly or
adults with special needs and any job that is related to the ex-offender’s conviction. On the
individual level, in order to maximize occupational opportunities and minimize recidivism, ex-
offenders should be aware of the limited employment rights that ex-offenders do have, the
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encourage the hiring of ex-offenders (Aukerman, 2003).
Research clearly demonstrates that individual-level characteristics and experiences affect
the reentry process (Visher and Travis, 2003). Yet, the reentry process does not occur in an
individualized vacuum. Parolees are released into communities and interact with peer groups
and family members. To successfully reenter society, individuals must be interconnected with
various entities from community groups, peer groups, family and peer mentor programs. It has
been shown that community outreach programs, either religious or social in nature, have a
positive impact on breaking the cycle of recidivism (Johnson, 2004). Reentry programs
available upon release, along with the environment where an ex-offender is released, can
potentially influence success. These findings are supportive of the idea that the context in which
ex-inmates are released is an important factor in determining how well they do post release.
In addition to these individual and environmental characteristics, state policy influences
individual transitions from prison to community. Parolees may have their parole revoked due to
violating technical conditions or parole, which are typically established at the state-level, ordered
by a state-level parole board, and typically enforced by a state-level agency. Different states
have different parole guidelines which will affect reentry success for individuals differently
depending on the state where they live. Moreover, the availability of jobs and social support
programs varies from state to state, which may also influence reentry success.
Though most research focuses on individual-level characteristics or on specific reentry
programs, some researchers have noted the importance of state-level policies on reentry success.
For example, research focusing on Kentucky examined their state-level efforts to lower prison
and community corrections costs (Richards, Austin, and Jones, 2002). Here, the researchers
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described a “perpetual incarceration machine” in Kentucky, where prisoners are recycled from
prison to parole and back to prison (Richards et al., 2002). These scholars suggest that reentry
trends and incarceration rates are a large concern at the state level and provide a useful case
study focusing on Kentucky and how Kentucky politicians and prison administrators have
developed state-specific strategies. This suggests that state-level policies and decisions may
greatly shape the face of prisoner reentry.
Richards et al. (2002) go on to note that along with this incarceration cycle, Kentucky
and many other states face the problems of a continuing growing prison population and parole
failure. The case study of the Kentucky prison system offers many promising reforms to curb
the growing prison population and rate of parole failure. The first recommendation of Richards
et al. (2002) is to restrict parole admissions for technical parole violations; they suggest that
overall, states should be less stringent on the violators for petty offenses and misdemeanors.
Next, states need to reorganize parole services and change the mission and goals of parole
services. Here, they argue that parole officers should act more like parole workers, and emulate
social or child care workers. Altogether, these suggestions drive home the message that the
system should help the individual succeed and should not be focused purely on the punitive
functions of parole (Richards et al., 2002). One important take away message from this research
is that many of these potentially fruitful adjustments to the reentry process are state-level
matters, highlighting the importance of the state as a unit of analysis.
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Federal Reentry Spending
While research has examined the importance of specific reentry programs and initiatives,
I am aware of no research which has examined the link between reentry investments and reentry
success overall. This is an important area for study both because it can help determine if federal
reentry dollars are well spent and because the availability of federal reentry funds shape the
context of reentry for released offenders. Federal grants to assist reentry efforts have been in
place for several years. The Serious and Violent Offender Reentry Initiative (SVORI) is often
viewed as the modern origin of the Federal government’s reentry efforts. SVORI began in 2002
and was a $300 million collaborative effort among Department of Justice, Department of Labor,
Department of Health and Human Services and the Departments of Education and Housing and
Urban Development. SVORI aimed to reduce recidivism among high-risk offenders including
those who faced multiple challenges upon returning to the community from incarceration (GAO,
2012). SVORI concluded in 2005, but its goals were continued through the federal Prisoner
Reentry Initiative (PRI) which was announced by President Bush in 2004. The PRI grant
program focused on reducing recidivism by helping former inmates find work and providing
them access to other critical services in their communities (GAO, 2012). The PRI concluded in
2008 when its appropriation expired. Newer programs and efforts continue today across the
country including the Second Chance Act of 2007.
While recidivism has long been a topic of importance in criminology (Mandel, Collins,
Moran, Barron, Gelbmann, Gadbois and Kaminstein, 1965), correctional practices over the last
30 years have shied away from rehabilitation and toward other goals of incarceration, including
incapacitation, deterrence and retribution (McAlinden, 2011). It has only been recently that the
federal government began to re-direct specific efforts at reducing recidivism. As discussed
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above, these efforts focused on reducing recidivism and increasing the success of reentry begin
in the early 2000s with the SVORI and PRI efforts. The Federal PRI, in particular, was a strong
turning point in the amount of federal attention and money directed at the problem of recidivism.
This program, announced by then President Bush, was designed to assist ex-prisoners and the
communities to which they return (Bush, 2004). President Bush noted that:
“This year, some 600,000 inmates will be released from prison back into society. We
know from long experience that if they can’t find work, or a home, or help, they are much
more likely to commit more crimes and return to prison…. America is the land of the
second chance, and when the gates of the prison open, the path ahead should lead to a
better life (Bush, 2004).”
The Federal PRI focused on evidence-based assessment inmates and provided funding to
link offenders to faith-based and community institutions which would help ex-prisoners maintain
employment and avoid a return trip to prison. Since late 2007, there were 30 PRI grantees across
the country that were providing mentoring, employment and other transitional services to
thousands of ex-inmates. As of November, 2007, 10,361 PRI participants have been enrolled in
PRI sponsored programs and 6,035 participants have been placed into jobs (Bush, 2007). The
one-year post-release recidivism rate for PRI participants is less than half the national average
recidivism rate. This is indicative of the fact that federal reentry money can have a positive
effect on reentry outcomes. Through collaborative efforts of the U.S. Department of Labor, the
U.S. Department of Justice and other private foundations, The Prisoner Reentry Initiative has
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provided mentoring and other transition services for men and women returning home from
prison in tandem with faith-based and community organizations.
While the PRI focused on federal inmates, the federal reentry mandate characterized a
shift in attention and resources such that the federal government placed more attention toward
the issue of prisoner reentry. Following the PRI, large amounts of federal dollars were funneled
into state correctional departments by way of grants (H.R. 1593/S.1060). For example,
following the PRI, the Department of Justice awarded grants to 20 state-level Departments of
Corrections (Coffey, Holl, Kolovich and Belotti 2009). Though SVORI and PRI have
concluded, the United States federal government continues to direct resources and effort to the
problem of reentry. Upon the PRI’s conclusion, the Second Chance Act (SCA) of 2007 was
implemented to continue to provide support for reentry services at the state and local levels. The
SCA looks to reduce recidivism by administering grants to state and local government agencies
in partnership with stakeholders, service providers and nonprofit organizations to provide
employment assistance, substance abuse treatment, housing, mentoring and other services.
Successful reentry is essential to our country, as the economic and societal costs of high
incarceration rates are significant. Mass incarceration has a negative impact on not only the
incarcerated, but a debilitating effect on the family and community of that individual (Hagan and
Burch, 2010). Along with prison overcrowding, high rates of recidivism mean more crime, more
victims, and more pressure on an already overburdened and overcrowded criminal justice system
(GAO, 2012). As such, the federal government has directed large amounts of money toward this
issue. The scope of these efforts can be clearly demonstrated by examining the federal prison
system. The Department of Justice’s Federal Bureau of Prisons (BOP) is the sole agency
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responsible for the custody of more than 218,000 federal inmates, and considers the process of
reentry to begin the day the inmate is incarcerated (GAO, 2012). The BOP is involved in the
direct provision of reentry services, such as vocational training, faith-based programs, and
substance abuse treatment, which help prepare inmates for release. In 2012, BOP spent about 9
percent, or $604 million of its $6.6 billion operating budget, on reentry-related services. This
estimate is based on the costs of larger programs that specifically support reentry, such as
education and vocational training initiatives and drug treatment programs (GAO, 2012).
However, since reentry is a process and not a specific program, some initiatives that support
reentry would not be captured in this estimate, which would suggest that this estimate is, if
anything, an underestimate.
Despite the attention focused on reentry by the federal government and the substantial
monetary investment in prisoner reentry programs, there is little research examining the
effectiveness of federal reentry spending in general, though it should be noted individual grants
are assessed by the grantees and by the Department of Justice. As such, current grant evaluation
efforts focus on the efficacy of specific programs and policies, though these efforts have been
critiqued by the General Accounting Office (2012). The GAO (2012) suggests that a hyper
individualized assessment of reentry programs is, while important, of little value in examining
the broader reentry picture.
While the assessment of specific grant funding is important, the primary point here is to
note that far less attention has been placed on the overall cost effectiveness of federal reentry
spending more broadly. Based on information pulled from USAspending.gov, from 2000 to
2005, the Federal Government awarded over $149,160,121 in direct grant money to states to
address reentry concerns. This is a substantial sum of money and potentially a dramatic
undercount, given that this does not measure funds from other sources like subsidies, tax
incentives, foundations, states investments, charities, and other federal grants that were not
directly earmarked for reentry efforts and it is important to assess the degree to which it has been
effective.
Moreover, there is evidence that the raw amount of money spent on reentry has increased
since the 2005 figures. The Departments of Labor and Health and Human Services all
administer grant funding to state and local reentry service providers so that they may assist the
reentry population train for and find jobs, obtain substance abuse treatment, and locate housing
as needed (GAO, 2012). These three federal agencies were appropriated over $165 million in
2012 and nearly $185 million in 2011 for their respective reentry grant programs. These
programs are the Second Chance Act program, The Reintegration of Ex-Offenders program, and
the Offender Reentry Program, which support both the adult and juvenile reentry population
(GAO, 2012).
Given the large amount of money that has historically been directed and continues to be
funneled at the social problem of reentry, it is important that reentry spending be studied.
Though I am aware of no research which examines federal spending in reentry in general, federal
spending in other fields has resulted in tangible improvements. As such, it seems reasonable to
infer that federal spending on reentry might help reduce recidivism. The National Research
Council (NRC, 2012) for example, has demonstrated that Federal research dollars play an
important role in scientific development. Specifically, they describe a cyclical pattern in which
government support plays an integral role in the formation of new ideas brought about by the
private sector, which in the future leads to new companies and jobs. Seed research backed by
government agencies has led to breakthroughs in technology and in the fields of computing
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intelligence. Government-financed research has led to commercialization of multiple
burgeoning technologies and research totaling over $500 billion a year (Lohr, 2012).
More broadly, since World War II, government funded research has produced an
impressive record of scientific and medical advances (Frist, 2002). Biomedical research has
made extraordinary strides in recent years, due to an increase in government funding over time.
Improvements have been made in terms of HIV, AIDS, smallpox, hepatitis B, measles, and polio
through the introduction of federal grant money. Moreover, there are new treatments for cancer,
heart disease and mental illness. Government funding has been integral to these breakthroughs.
The rich connection of federally funded universities and industry research and development has
been established over time. Early basic research on human cell biology, on electronics, or on
radio waves has ended up producing genetic therapies, semiconductors and computers, or GPS
systems. Those early scientific studies didn’t predict such inventions, but the basic research,
funded by the government, allowed future researchers to start thinking about potential
applications (Clark and Llorens, 2012). Government backed research at universities and research
institutions pave the way for the revolutionary innovations we see emerging in our current
environment. Private entities are not likely to make a risky investment on unproven
technologies, yet the government funding establishes an environment which brings about
innovation.
Similar to the role that federal funding plays in basic scientific research, it is possible that
federal funding may play a transformative role in terms of criminal justice policy and criminal
justice outcomes. State governments and charitable foundations may be unlikely to invest large
sums of money into unproven reentry strategies, but may be more likely to invest following the
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seeding of federal dollars. Indeed, one of the primary criterion upon which new federal grant
applications are evaluated on is the development of a sustainability plan, which typically
involves continued state-level investment after the expenditure of federal grant funds.
In summary, it is clear that the federal research money can have measurable effects and
that the federal government is investing large sums of money in reentry efforts (moreover, a
substantial amount of this money is directed toward the states). It is reasonable therefore, to
examine the degree to which federal spending on reentry would create similar success in prisoner
reentry.
The Impact of Social Context
In addition to examining the efficacy of federal grant funding for reentry programs, the
current research also contributes to the field by providing an explicit focus on state-level social
context. While the individual-level characteristics of offenders and their offenses have been the
basis for almost all prior studies of recidivism, there are reasons to suspect that additional factors
matter. For example, there is reason to believe that the social context in which offenders are
released affects reentry success. The environment in which offenders are released is essential to
their success on parole. It has been found that poverty as a context or environment does matter,
because those ex-offenders who live in high poverty areas have a higher propensity to reoffend
(Kubrin and Stewart, 2006). Context and environment affect success on the state level of reentry
because those states with high poverty rates will have a higher rate of ex-offender recidivism.
The idea that social context affects behavior is not new to sociologists, nor is it new to the
study of crime specifically. Indeed, some of the earliest foundations of criminology were built
on the assertion that context was as, or more, important than individual factors (Shaw and
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McKay, 1942). Researchers have documented a broad range of “context effects” on criminal
behavior in general (for a thorough review of this literature, see Sampson, Morenoff and
Gannon-Rowley, 2002). For example, Blau and Blau (1982) suggest that it is important to not
simply focus on what kind of individuals tend to commit violent crimes, but to also examine the
types of social conditions conducive to crime. Their classic research indicates high rates of
criminal violence are the result of racial and economic inequalities. The research implies that if
there is a culture of violence, it is rooted in economic inequalities, especially if associated with
ascribed position. This research echoes the sentiment that social context has a deep impact on
success in reentry. More recently, it has been found that criminal activity is positively related to
unemployment; those less affluent cities characterized by chronic poverty have higher levels of
crime (Huang, Laing and Wang, 2004). Labor market opportunities have also been shown to
affect criminal behavior (Bellair, Roscigno and Mcnulty, 2003).
Given the history of focusing on the effects of context on criminal behavior, it is
surprising how little research has examined the role of context on reentry success. One notable
example is the research by Kubrin and Stewart (2006), which focused on the role of
neighborhood context. Here, they argued that it is important to analyze the extent to which
neighborhood socioeconomic status accounts for variation in the reoffending behavior of ex-
prisoners. They found that those who return to disadvantaged neighborhoods recidivate at a
greater rate while those who return to resource rich or affluent communities recidivate at a lesser
rate, even after controlling for individual-level factors (Kubrin and Stewart, 2006). Though
Kubrin and Stewart (2006) focus on neighborhoods, this study is important as it was the first to
provide a coherent argument for examining the role of context in recidivism and because it
frames prisoner reentry as a process that involves more than just the individual. More recently,
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Harding, Morenoff and Herbert (2013) presented research that supported the idea that
neighborhood context plays a critical role in successful reintegration. Based on this research, we
can conclude neighborhood characteristics affect individuals’ rates of offending. It follows,
therefore that other contexts, like the state, might also matter, as state-level economic conditions,
cultural traditions, and policies might also shape the experiences of inmates attempting to
reintegrate into society.
Altogether, there is a small, but important body of research which indicates that those
who return to disadvantaged communities recidivate more frequently than those who return to
relatively affluent communities, controlling for individual-level factors. The primary take away
point here is that context has an impact on recidivism above and beyond individual-level factors.
Put simply, it is not possible to understand reentry by focusing solely on the individual-level
characteristics of ex-offenders. Though Kubrin and Stewart (2006) focus on the importance of
neighborhoods for recidivism, I suggest that these same factors apply at the broader state-level.
When parolees are released to states with higher poverty levels, it is more likely that the
parolee will find themselves in an adverse situation in terms of recidivating. Moreover, the
availability of jobs and social services varies from state to state, thereby suggesting that state-
level context is likely to matter. Crime rates also vary from state to state; it is reasonable to infer
that states with more crime are less conductive to reentry success. These state-level variances
may be reflective of push and pull-factors on offenders, as well as opportunity structure for
employment and criminality within the state-context. Clearly, there are a number of state-by-
state differences that might affect the probability of reentry success for a given ex-offender.
In addition to this, it is important to note that parole, itself, is largely a state-level process.
Parole boards are established at the state level. Funding for reentry programs is typically
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managed by state level Departments of Corrections. State-level management of parole is
important because it sets up a more delineated jurisdiction for the offender. Therefore, there are
several reasons why the state is an important unit of analysis with which to study reentry.
Following the logic of Kubrin and Stewart (2006), it seems likely that parolees released to states
with higher poverty rates are more likely to fail than those released to more affluent states.
Research Questions and Hypotheses
Based on the literature and discussion above, the current research attempts to address the
following research questions:
1. Are federal reentry funds successful in lowering the parole failure rate at the state-
level?
2. What is the relationship between social context and reentry failure at the state-level?
Based on my review of the literature, I offer the following hypotheses. First, states which
receive more federal reentry grant funding will have lower parole failure rates. As I noted above,
prior literature suggests that federal funding has played an integral role in many areas. In terms
of my second research question, I hypothesize that adverse social context will negatively affect
reentry success. Specifically, states with higher levels of unemployment, greater violent crime
rates, higher federal assistance rates and higher poverty rates will have higher parole failure
rates. Each of these adverse factors is likely to make reentry more difficult for ex-offenders.
Finally, regarding the racial component of the study, states with higher percentages of minorities
(black and Hispanic) will have higher parole failure rates, reflective of the higher offending rates
for these minorities more broadly.
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Through secondary data analysis, I explore state-level variation in reentry success. Since
states vary in crime rates and poverty rates, my analysis of state funding offers a unique
perspective on the efficacy of state to state funded reentry spending. This project describes the
distribution of federal reentry funds to states and analyzes state-level correlates of state prisoner
reentry success.
Data
I utilize data from four sources for this project. First, I utilize data from the 2006 Annual
Parole Survey to examine reentry success at the state-level. This data was downloaded from the
Inter-university Consortium for Political and Social Research (ICPSR) located at the University
of Michigan. Specifically, I focus on the failure rates of those on parole. Here, the failure rate is
defined as the sum of those who returned to state prison with a new sentence, those who had
their parole revoked, other returns to incarceration and those who absconded, divided by the total
discharges from parole, and then multiplied by100 to make a percentage. Those who absconded
have stopped reporting to their parole officers and those who have had their parole revoked are
those who have had that parole nullified. Failure rate serves as the dependent variable in the
analysis.
Second, I utilize data from the 2005 Community Survey to document the socio-structural
conditions of states. These data were downloaded using the American FactFinder tool on the
U.S. Census Bureau’s website. I selected the year 2005 for two reasons. First, it is temporally
prior to the measure of recidivism derived from the 2006 Annual Parole Survey. Though I am
unable to provide a true casual analysis in this study, selecting data from 2005 allows for the
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possibility that these factors impacted the 2006 failure rates. Second, I selected 2005 data
because it was the year following President Bush’s Prisoner Reentry Initiative of 2004 which
was vital legislation addressing reentry and thereby marked an important time point for studying
reentry processes. Specifically, I acquired data from the census on the following variables: race,
unemployment rate, those receiving federal assistance and the poverty rate. Racial data
represents the percentage of the population which is white (non-Hispanic), black (non-Hispanic)
and Hispanic. Black and Hispanic represent the largest populations which deal with prisoner
reentry within the states. The percentage of the population which is white in these models
created issues of multicollinearity in the regression models presented in the results section, hence
its omission. The unemployment rate, which is the percentage of people in the labor force who
are currently unemployed, is important to analyze because much of the reentry effort focuses on
connecting inmates to jobs and the employment rate may represent a baseline level of risk of
parolees not meeting the conditions of their parole. The variables representing federal assistance
and the poverty rate, both of which are measured as percentages of the population, give us a
window into the levels of poverty and how they vary state to state. These factors seem especially
important, given Kubrin and Stewart’s (2006) result regarding the recidivism rates in affluent
and poor neighborhoods.
Thirdly, violent crime is also included as an independent variable in this study. I
downloaded state-level violent crime rates (which are the number of homicides, rapes,
aggravated assaults, and robberies per 100,000 people) using the Federal Bureau of
Investigation’s Uniform Crime Report via the “UCR Online Data Tool.” The primary reason to
include this variable is because states with more crime are likely to be harder for ex-prisoners to
successfully reenter, as it will be easier and more likely for the offenders to find themselves in
18
situations conducive to crime. It is important to note that there are varying levels of crime
throughout the different states. The dichotomy between those states with more crime and those
with less crime shows that crime rates of a specific state are integral to the probability of
successful reentry in a state.
Lastly, I gathered data on federal spending on reentry from USAspending.gov.
USASpending.gov is a government website which details federal grants for various topics. For
this project, I searched their databases for grants related to the topic of reentry between the years
2000 and 2005. The website provided information on which state the grant was provided to and
I recorded this information for each grant listed on the website in an Excel sheet. After I
gathered the data, I merged this data with the prior three sources into a single SPSS dataset. I
then utilized the total parole figures from the 2006 Annual Parole Survey to calculate a
“spending-per-capita” variable (spending divided by the parole population at the end of the year)
in order to account for differences in the re-entering population between states. Table 1, below,
presents descriptive statistics for the variables in this study.
Table 1- Descriptive Statistics for Variables (N=31 States)
Mean Standard Deviation Description of Variable Failure Rate 37.404 16.87428 Percentage who failed on parole Spending Capita 3337.8211 12156.91232 Amount spent on an individual parolee Unemployed 6.3548 1.27928 Percentage who are unemployed Federal Assistance 2.4839 0.72438 Percentage who receive federal assistance Poverty Rate 13.0645 2.82767 Percentage who live in poverty Violent Crime 404.871 193.79142 Violent crime rate per 100,000 Hispanic 8.6129 9.64945 Percentage who are Hispanic Black 9.9355 9.80114 Percentage who are Black
First it is important to note that the 2006 Annual Parole Survey only included failure rates
for 31 of the 50 states. I do not know why there was no data reported for the other 19 states,
though this is both a clear limitation of the current research and a call for better data collection
on recidivism in the United States. For those states who reported this data, the mean failure rate
was 37.404, suggesting that 37% of the parole population fails parole in a given year.
It is also worth noting that there is considerable variation in re-entry spending across
states. The average “reentry spending per capita” is about $3300, indicating that states receive
enough federal grant money to spend about $3338 on each parolee per over the 5 year period.
The standard deviation is $12,157, suggesting that the actual amount of federal grant money
received varies substantially from state to state. Given this skew, I transform this variable using
a natural logarithm transformation for the regression analyses in the Results chapter.
Methods
I adopt a two-pronged approach to studying reentry at the state-level. First, I focus my
attention on examining reentry spending at the state level. Here I identify state-level
characteristics associated with higher and lower levels of reentry spending using correlational
analysis. My goal is to examine the distribution of how federal reentry grant spending, focusing
on identifying which states are getting money and which state-level factors are associated with
obtaining federal funds. The data collected shows that there is substantial variation in the
allocation of money to each state. For example, the state receiving the fewest grant dollars was
Kentucky and it received $1,863,899. Conversely, the state with the most grant dollars was
Georgia and it received $9,454,547. While the average was $2,983,202, the standard deviation
was $1,416,199, indicating that funding varied substantially from state to state. I explore this
20
phenomenon further in the results section below. In addition to a more qualitative discussion of
the states receiving the most and least in funds, I also present data on bivariate correlations
between federal funding received and various social-structural factors at the state-level.
My second and primary focus is to examine which state-level characteristics are
associated with reentry failure. In order to study this process, I conduct both bivariate and
multivariate analyses. The bivariate analyses present the correlation between independent
variables (spending and state-level context variables) and the failure rate, while the multi-variate
analysis supplements this effort through the use of multiple regression analysis, which allow me
to examine multiple factors at once and to employ statistical controls. The failure rate variable is
used as the dependent variable in these regression analyses.
21
Chapter IV: Results/Analysis
First, I explore the distribution of spending and then the failure rate. Different states
received different amounts of money in total from 2000 to 2005. The chart below shows the
funding for all fifty states over this time period in millions, along with the other variables White
(later omitted), Black, Hispanic, Unemployed, Federal Assistance, Poverty Rate and Violent
Crime.
Table 2- Funding for all States from 2000 to 2005 with Social Context Variables
Federal Violent Spending White Black Hispanic Unemployed Assistance Poverty Crime
States ($) (%) (%) (%) (%) (%) (%) Rate GA 9,454,547 63 29 7 7 2 14 446 FL 7,828,305 77 15 20 6 2 13 709 LA 5,816,841 64 32 3 9 2 20 597 MD 5,084,563 61 29 6 6 2 8 704 NC 4,638,538 71 21 6 7 2 15 469 NV 4,515,519 76 7 24 6 2 11 608 CA 4,391,333 61 6 35 7 3 13 526 IL 3,441,871 72 15 15 8 2 12 552 NJ 3,260,410 70 13 15 6 2 9 355 MI 3,254,806 80 14 4 9 3 13 554 VA 3,219,812 72 19 6 5 2 10 283 IN 3,115,963 86 9 5 7 3 12 324 MO 2,890,316 85 11 3 7 3 13 526 PA 2,780,000 85 10 4 7 3 12 425 MA 2,735,378 83 6 8 6 2 10 461 SC 2,697,203 67 29 3 8 2 16 767 CO 2,677,619 83 4 20 6 2 11 397 HI 2,641,778 25 2 8 4 3 10 256 OH 2,624,007 84 12 2 7 3 13 350 DE 2,603,234 74 20 6 6 2 10 633 MS 2,599,745 61 36 2 9 3 21 280 AL 2,567,696 71 26 2 7 1 17 433 ND 2,541,374 92 1 1 4 2 11 111 MN 2,509,525 88 4 4 6 3 9 297 AZ 2,472,359 76 3 29 6 2 14 512 NM 2,471,436 70 2 44 7 3 19 646
22
MT 2,452,110 91 0 2 5 2 14 282 OR 2,448,554 87 2 10 8 3 14 287 NY 2,448,070 67 15 16 7 3 14 444 SD 2,405,820 88 1 2 5 2 14 179 CT 2,405,461 81 9 11 6 3 8 273 WV 2,402,970 95 3 1 7 2 18 274 KS 2,398,733 85 6 8 6 2 12 389 NE 2,386,908 90 4 7 5 3 11 287 IA 2,384,225 93 2 4 5 3 11 293 WI 2,344,847 88 6 5 6 2 10 242 ID 2,332,353 92 0 9 6 3 14 257 AK 2,307,370 69 3 5 9 7 11 632 RI 2,295,881 98 1 11 6 3 12 252 VT 2,284,772 97 0 1 5 4 12 126 UT 2,269,422 90 1 11 5 2 10 225 TN 2,185,282 80 16 3 7 3 16 757 NH 2,156,337 95 1 2 5 3 8 135 WA 2,145,962 81 3 9 7 4 12 346 OK 2,139,355 75 7 7 7 4 17 509 TX 2,124,599 72 11 35 8 2 18 528 ME 2,115,238 97 1 1 6 5 13 112 AR 2,087,000 79 15 5 7 2 17 528 WY 1,940,775 92 1 7 5 2 10 230 KY 1,863,899 90 7 2 8 2 17 267
The chart above shows the recipients of federal funding for reentry. Seven states
received over $4,000,000 over the time period of 2000-2005. In addition to listing the amount of
money allocated to each state, I also provide social context variables. The top recipients are
located throughout the country from the South to the Midwest. Focusing on the relationship
between race and funding, the chart shows that those states receiving the most reentry funding
have lower percentages of white population. States with larger black and Hispanic populations
received greater levels of federal grant funding. Turning to the relationship between economic
factors and grant money, the table shows that the unemployment rate of the top funded states is
between 6% and 9%. These unemployment rates generally are above the average unemployment
23
rate of 6.35%. The percentage of the population receiving federal assistance for these top funded
states is between 2% and 3%, which is also generally above the average rate. The variable with
the most variation among these top ten funded states was poverty rate. Louisiana is the 3rd most
funded state and had the highest poverty rate of the group with 20%. Conversely, Maryland was
the 4th most funded state and had a much lower poverty rate of 8%. With the exception of New
Jersey, each of the top ten funded states had an above average violent crime rate.
Examining the states receiving the most funding suggests that federal grant money is
generally being funneled to the states that are likely to need it most. That is, states with higher
crime rates and more adverse social conditions are likely to benefit most from access to federal
reentry dollars. However, rather than only examine the funding of the states, I also provide a
more formal analysis of this issue using bivariate Pearson correlations. Bivariate correlations tell
us the strength and statistical significance of the relationship between two variables while
accounting for all data points in a sample. As such, these results (presented in Table 3) describe
the overall pattern of relationships between state-level characteristics and the receipt of federal
grant dollars.
Table 3- The Correlations of the Different Variables with Spending.
Variable Pearson's Correlation Unemployment Rate 0.148 Federal Assistance -0.271+ Poverty Rate -0.025 Violent Crime 0.420** Hispanic 0.149 Black 0.561** n = 47; + p <0.10, *p<0.05, **p<0.01
Based on this analysis, the only statistically significant correlates of spending are federal
assistance, violent crime, and the percentage of the population which is Black. The negative and 24
(borderline) statistically significant correlation between spending and federal assistance indicate
that states where greater proportions of the population receive federal assistance are likely to
receive less in federal reentry grant funding. The correlation between spending and violent
crime and spending and percentage of the population which is Black are positive. These
statistically significant correlations indicate that states with higher crime rates and larger Black
populations receive more federal reentry grant funding. In general, these results confirm my
earlier assertion that federal grant money is generally going to the states which need it most,
though it is interesting to note that factors like the unemployment rate are unrelated to federal
funds, given that employment conditions are often a part of the conditions of parole.
Predictors of Reentry Failure
I turn my attention to the primary focus of reentry success. In order to do so, I examine
both bivariate correlations and linear regression results. The bivariate correlations are presented
in Table 4:
Table 4- The Correlations of the Different Variables with Failure Rate
Variable Pearson's Correlation Spending -0.230 Unemployed -0.028 Federal Assistance 0.097 Poverty Rate -0.087 Violent Crime -0.078 Hispanic 0.104 Black -0.399* n = 31, + p <0.10, *p<0.05, **p<0.01
The only significant correlate of failure rate was percentage of the population that was
Black. The negative and statistically significant correlation between percentage of the
25
population that was Black and failure rate indicate that states with a higher percentage of the
population that is Black have a lower failure rate on parole.
Next I conduct a linear regression analysis. Linear regression models analyze the
relationship between a single dependent variable (failure rate) and multiple independent
variables (logspending per capita, unemployed, federal assistance, poverty rate, violent crime,
Hispanic and black) at the same time. These models go beyond simple bivariate correlations in
that they provide statistical controls (meaning that all of the variables can be analyzed at once).
In terms of model fit, the R-Squared-value for this regression tells us that the independent
variables in the regression model account for 46.9% of the total variation in a state’s failure rate.
This is a fairly large R-squared, suggesting that this regression model does a good job of
explaining variation in state-level parole failure rates.
Table 5- Coefficients of the Regression Model
B(Std.Error)
n = 31, + p <0.10, *p<0.05, **p<0.01
The table above provides the coefficients of the independent variables along with the
standard errors in parentheses. According to the multiple regression model, only two factors are
statistically significantly related to reentry failure controlling for other factors. Interestingly and
counter to my expectations, the unemployment rate, the federal assistance rate, poverty rate,
violent crime rate and the percentage of the population that is Hispanic or Latino were not
significantly related to reentry success.
The statistically significant variables are the log of federal spending per capita and the
percentage of the population which is black. Both variables have negative relationships with
reentry failure, indicating that states with higher levels of these factors tend to have lower parole
failure rates. Specifically, this indicates that a 50% increase in federal reentry spending is
predicted to decrease the failure rate by about 1% (-5.858*log(1.10)=-0.98), controlling for other
factors. Similarly, a 1 percent differential in the percentage of the population which is Black is
associated with a 1.4% decrease in the expected failure rate, controlling for other factors.
These results indicate that the social context of reentry is important, as parolees returning
to states with large Black populations and to states receiving more federal reentry dollars are at
less risk for failure than other states. The race result is somewhat surprising as it suggests that
failure is less common in states with larger Black populations. Conversely, the spending result
occurs in the expected direction. This provides general support for the idea that states which
receive more federal reentry grant dollars tend to have lower failure rates.
27
Chapter V: Conclusions
Summary of Results
The current project adopted a two-pronged approach to studying reentry at the state-level.
First I provided a descriptive and correlational analysis of federal reentry spending. Then, I
examined the correlates of reentry failure at the state-level.
In terms of reentry spending, my results indicate that there is considerable variance in the
distribution of federal reentry grant dollars. Interestingly, my results are somewhat promising in
that both my informal discussion of the funding of the fifty states and the bivariate correlations I
present suggest that states with the highest crime rates receive the most federal reentry grant
dollars. This suggests that federal dollars are being funneled to those states with the most severe
crime problems, which is a justifiable method of distributing these funds. This study examined
violent crime, but it may be necessary to examine non-violent crime as this is the most common
form of crime. It is notable though that other adverse social conditions, like unemployment and
poverty, are unrelated to the distribution of federal reentry dollars.
Turning my attention to the predictors of reentry failure, results indicated that states
which receive more federal funding for reentry programs have lower rates of failure for parolees.
This broadly suggests that increases in spending on reentry services have a positive impact on
states ability to improve the reentry success of their parolee populations. Put simply, states
which receive higher levels of reentry funding see greater successes in reentry. This has a few
implications. First and foremost, this suggests that federal grant money earmarked for reentry
has been important for states and has produced measurable results. Given these results, a
broadening of reentry funding is likely to produce positive results in more and more states.
28
Therefore, the most obvious policy implication here is that the federal government should
continue to invest funds into reentry efforts.
Clearly, additional research is needed on this topic, as the current research is ultimately
correlational. More importantly, the current research is limited in that it is unable to account for
the actual manner in which federal reentry grant dollars are spent. While this research
demonstrates that heightened levels of funding are, overall, a boon to the reentry process, it is
possible that certain types of funding and certain types of programs may be even more successful
than others. Still, these general results are promising. Increased funding of state reentry services
and programs may offer hope that states can mitigate the damaging effects of mass incarceration.
This may imply that states would be well advised to invest their own internal funds to reentry
programs. States that invest in reentry will strengthen the ex-offenders, their families and their
communities while saving money on future incarceration. Though the short-term cost of reentry
programming may be a burden on already stretched state budgets, the long term benefits could
prove to be cost-effective in the long-term.
In addition to providing evidence on the relationship between reentry spending and
reentry success, the current research also contributed to the literature by providing a much
needed contextual analysis of reentry. The majority of research on reentry focuses on individual-
level characteristics or specific reentry programs. While such research has produced important
results, it also neglects the long-standing sociological argument that social context has a strong
impact on life outcomes. Surprisingly, however, the current research only demonstrated a link
between the percentage of the population within a state which is Black and the parole failure
rate. This result was negative, indicating that states with larger Black populations have lower
failure rates, controlling for other factors. This may be in conflict with prevailing thought and
29
prior research regarding minorities and crime. This result is difficult to explain. It may be
reflective of the sample included in the study. Perhaps a different picture would emerge had all
50 states reported data on parole failure. If this result is accurate, however, it would suggest that
while African Americans may be disproportionately arrested and confined by the police and
sentenced by the courts, they may not be disproportionally violated or failed by parole officers.
Interestingly, none of the other social context factors were statistically significant
predictors of the parole failure rate. This was surprising, as prior research suggested that poverty
was an important predictor of reentry success (Kubrin and Stewart, 2006). It is difficult to
ascertain the importance of these results. Indeed, they could imply that context is largely
unimportant. Alternatively, this could be indicative of the fact that the state is too large of a unit
of analysis for the study of reentry processes. States tend to be large heterogeneous areas, so the
overall state-level of employment or poverty might not be indicative of the actual hardships that
any given parolee faces. Similar unit of analysis “scope” problems have been discussed in other
criminological research (Land, McCall, and Cohen, 1990). Additional research at different units
of analyses (like cities) is needed to investigate this possibility. Lastly, it should be mentioned
that these null results could be something of a statistical artifact. The small sample size in this
analysis resulted in a low overall level of power in the analysis, meaning that the regression
models in this study may struggle to find statistically significant relations (Cohen, 1992).
States vary in the amount of federal funding they receive for their reentry efforts. Many
factors could influence this phenomenon. Size and population are major factors in the amount of
federal reentry funding to each state. The more populated states, primarily in the South, received
the bulk of federal reentry money. Many of these states face problems of unemployment and
high crime rates while having a larger than average amount of minorities. The states with a high
30
majority of white population received the least funding. This would imply that race is a large
factor in federal reentry policy funding. Many states receive less funding had diverse ethnic
populations which could mean that the more ethnically diverse a state is, the more reentry
funding they will receive. Taking into account the diversity and population differences within
the country, I think that the states who need federal funding the most for reentry are receiving the
necessary assistance.
Limitations
There are, however, a number of important limitations that must be discussed in the
current research. As previously discussed, one of the major limitations is the sample size in this
study. I was only able to analyze 31 of the 50 states. A lack of statistical power might make it
hard to detect statistically significant variables, even if they are substantially significant. In
addition to this, the missing data could create issues of generalizability. It is not immediately
clear that the results of this research can be applied to the other 19 states. Therefore, while
reentry spending may be a useful asset for the 31 states I studied, additional research is needed to
determine if it plays a similar role in the remainder of the United States. On a related note, it was
very surprising that 19 (or 38%) of states did not report parole failure data to the 2006 Annual
Parole Survey. This should serve as a call for the collection of more and better data in order to
provide a more comprehensive evaluation of federal and state-reentry efforts.
Future Studies
This study offers some perspective for future studies. Future studies should approach the
reentry issue with a multilevel approach where more levels beyond the state or the individual are
taken into account. Incorporating individual characteristics, neighborhoods, cities, counties and
even countries may produce a more comprehensive study which may take context effects into
31
account. It is likely that differing factors influence reentry success. For example research shows
that individual neighborhood factors matter. A truly multilevel approach would allow
researchers to examine all of the factors. One issue with the current study is it focused on a cross
section. In the future, researchers should employ a longitudinal approach with many years or
even a span of decades to analyze. Additionally, it may also benefit researchers to examine the
state corrections budget and see how reentry is funded on another level besides the federal level.
In the current research, this “snap-shot” effect could explain the unusual race result, this is
something that only research looking at more years and data can address. Lastly, future research
will have to take into account phenomenon like the recession of 2007 or Hurricane Katrina and
the impact these major events have on the data. Watershed events like these may greatly
influence the data, social context and populations of the states.
Delineating itself from past studies which focused on individual level factors and specific
programs, this research is among the first to examine the cumulative effects of federal reentry
spending on reentry. This research emphasizes that federal reentry spending is integral to
successful prisoner reentry. The states currently receiving the most federal funding should be
receiving that money due to their crime rates and populations. It is likely that an increase in
federal reentry funding will lower recidivism and parole failure, in the long run saving the states
a great deal of money. Funding reentry programs is an economic and responsible way to address
the nation’s problem with mass incarceration while maintaining the importance of rehabilitation
in reentry.
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aakthar32@gmail.com 2810 Flint Hills Drive Bakersfield, CA 93313
Education MA, Sociology expected June, 2014 California State University, Bakersfield Bakersfield, CA
BA, California State University Bakersfield May 2011 Bakersfield, CA Major: Political Science Minor: Sociology
Work Experience Gym attendant, UMBC Retriever Activity Center, September 2005- March 2006 • Assist in gym maintenance and help around the gymnasium and activity center. • In charge of physical education class preparation and intramural sports. • Perform general administrative duties to support professional staff.
Sales representative, The Mobile Solution, Baltimore, MD, March 2006-September 2006 • Held top sales in cellular phones for two consecutive months in the Baltimore market. • Specialized in customer service and customer care assistance.
Front desk clerk, Dr. Amina, Houston, TX 2007-present (varying non-consecutive months of employment). • Assist in administrative duties throughout a pediatrician's office. • Helped out around the office on seasonal terms throughout the year.
Volunteer experience B.R.O.T.H.E.R.S. Volunteer group, Baltimore, MD. Winter of 2005- Fall of 2006 • Assisted at risk youth through mentoring, tutoring and athletic activity. • Worked directly in the community in the Baltimore area volunteering my time and efforts with a focus on the youth.
GED tutor, Bakersfield Homeless Shelter, Bakersfield, CA. May 2011 – present. • Taught individual adults and a class of adults how to master the skills necessary to pass the GED test.
McAlinden, Anne-Marie. 2011. “Transforming Justice: Challenges for Restorative Justice in an Era of Punishment-Based Corrections.” Contemporary Justice Review: Issues in Criminal, Social, and Restorative Justice 14(4):383-406.
Pager, Devah. 2003. “The Mark of a Criminal Record.” American Journal of Sociology 108(5): 937-975.
Petersilia, Joan. 2001. “Prisoner Reentry: Public Safety and Reintegration Challenges.” Prison Journal 81(3):360-375.