COURT ORDERED COMMUNITY SERVICE: EFFECTS OF SOCIODEMOGRAPHIC
FACTORS ON PROGRAM COMPLETION
Nicole Mariana Penge
B.S., San Diego State University, 2007
THESIS
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
CRIMINAL JUSTICE
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
FALL
2010
COURT ORDERED COMMUNITY SERVICE: EFFECTS OF SOCIODEMOGRAPHIC
FACTORS ON PROGRAM COMPLETION
A Thesis
by
Nicole Mariana Penge
Approved by:
__________________________________, Committee Chair
Yvette Farmer, Ph.D.
__________________________________, Second Reader
Dan Okada, Ph.D.
____________________________
Date
ii
Student: Nicole Mariana Penge
I certify that this student has met the requirements for format contained in the University format
manual, and that this thesis is suitable for shelving in the Library and credit is to be awarded for
the thesis.
__________________________, Division Chair ___________________
Hugh Wilson, D.P.A.
Date
Division of Criminal Justice
iii
Abstract
of
COURT ORDERED COMMUNITY SERVICE: EFFECTS OF SOCIODEMOGRAPHIC
FACTORS ON PROGRAM COMPLETION
by
Nicole Mariana Penge
Abstract
Court ordered community service is a severely under researched correctional option.
Previous findings from the literature show that sociodemographic factors influence
recidivism, offenders’ willingness to serve alternative sanctions, and the type of work
order/sentence an offender receives. Therefore, this research was conducted to determine
if sociodemographic factors affected an offender’s likelihood of completing a community
service order. Secondary data collected from the Alternative Sentencing Program in
Sacramento during the year 2008 was used to examine five factors that were likely to
influence program completion. These factors included: gender, ethnicity/race, education,
income, and age. A sample of 941 cases was drawn from the study population. Analysis
indicated that sociodemographic factors have at least some effect on program completion.
However, none of the relationships between the independent variables and the dependent
variable were found to be significant. Despite the lack of significance the findings from
this study still have important implications and can be used to aid practitioners in the
implementation of these programs and assist judges in making more informed sentencing
decisions.
_______________________, Committee Chair
Yvette Farmer, Ph.D.
_______________________
Date
iv
ACKNOWLEDGMENTS
My deepest appreciation and gratitude to all those who have made this research
possible. To my friends and family who supported me, my professors who aided and
inspired me, and the Alternative Sentencing Program for granting me access to their data.
v
TABLE OF CONTENTS
Page
Acknowledgments…............................................................................................. …………… v
List of Tables .................................................................................................................... … viii
Chapter
1. INTRODUCTION…………………………………….………………………...….….… 1
Statement of the Problem ............................................................................................. 1
2. LITERATURE REVIEW ................................................................................................... 4
Restorative Justice ....................................................................................................... 4
Lack of Research in the United States ......................................................................... 9
Recidivism ................................................................................................................. 11
Program Completion .................................................................................................. 17
Sociodemographic Differences .................................................................................. 19
The Vera Institute ...................................................................................................... 22
Sociodemographic Effects on Program Completion .................................................. 26
Theory.. ...................................................................................................................... 28
3. METHODOLGY .............................................................................................................. 35
Introduction.. .............................................................................................................. 35
Population.. ................................................................................................................ 35
Sampling Technique.. ................................................................................................ 39
Data Collection Strategy.. .......................................................................................... 40
Data Entry .................................................................................................................. 41
Measures .................................................................................................................... 42
Limitations ................................................................................................................. 43
4. ANALYSIS OF FINDINGS ............................................................................................. 45
Analytic Plan.............................................................................................................. 45
Population Univariate Analysis ................................................................................. 45
Sample Univariate Analysis ....................................................................................... 48
Bivariate Analysis ...................................................................................................... 48
5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS ...................................... 53
Overview of Study ..................................................................................................... 53
vi
Discussion ................................................................................................................. 53
Implications ............................................................................................................... 54
Limitations ................................................................................................................ 55
Appendix A. List of Variables ............................................................................................. 58
Appendix B. Client Registration Form ................................................................................. 59
Appendix C. Court Referral Form ........................................................................................ 61
Appendix D. Measurement Issues ......................................................................................... 62
References ............................................................................................................................... 64
vii
LIST OF TABLES
Page
1.
Table 1 Description of Sociodemographic Factors……...……………………...47
2.
Table 2 Effects of Gender on Program Completion….………….………...........49
3.
Table 3 Effects of Ethnicity/Race on Program Completion………….….……...50
4.
Table 4 Effects of Education on Program Completion………….….…………..50
5.
Table 4 Effects of Income on Program Completion…………….…….………..51
6.
Table 4 Effects of Age on Program Completion…………..……………….......52
viii
1
Chapter 1
INTRODUCTION
Statement of the Problem
Numerous programs and alternatives to incarceration exist within the criminal
justice system. One such alternative is community service. “Community service is
compulsory, free, or donated labor performed by an offender as punishment for a crime”
(Caputo, 2004, p. 148). Offenders are sentenced, usually by a judge but also occasionally
by their probation officer, to complete a certain amount of hours, in a specified amount of
time, at a non-profit organization. These requirements are referred to as a community
service order (CSO). Community service orders first began in England and Wales in 1973
in response to the Wootton Report with legislative backing from the Criminal Justice Act
1972. The use of community service programs expanded quickly from there, mainly
throughout continental Europe and into Western nations. The CSO was perceived as a
desirable alternative to short-term imprisonment in response to rising crime rates (Harris
& Lo, 2002).
In a majority of European nations, community service is imposed as an alternative
to short-term imprisonment. National laws limit the minimum and maximum hours
sentenced (Harris & Lo, 2002; Menzies & Vass, 1989; Muiluvuori, 2001; Spaans, 1998),
however, CSOs differ in the United States. About one-third of the states have community
service programs (Meeker, Jesilow, & Aranda, 1992) which are run locally rather than by
state or federal governments (Harris & Lo, 2002). In the United States, there are no laws
or standards fixing the number of hours to various offenses and in those jurisdictions
2
utilizing CSOs, there are typically no maximum or minimum hour requirements (Meeker
et al., 1992). Instead, each jurisdiction is free to set the limits or standards by which they
follow often leaving the rates for converting fines and jail time into community service
hours up to judicial precedent. Additionally, community service in the U.S. is generally
not perceived as a realistic option for serious offenders (Harris & Lo, 2002) and is instead
used for minor offenders such as traffic violators, misdemeanants, and low-level felons as
a portion of their probation (Caputo, 1999).
A lack of uniformity in community service orders has led to legal and operational
considerations within community service programs in the U.S. that make them difficult to
analyze and evaluate (Harris & Lo, 2002). This is because without uniformity the exact
goals and objectives on which these programs are to be measured are difficult to define.
Despite this, research provides insight into the completion rate of these programs. These
studies show that community service programs typically have very high completion rates.
The majority of them also far exceed the program designer’s original expectations.
Although each program operates differently with various goals and objectives,
community service program completion is similarly defined simply as an offender who
completes the required amount of hours in the allotted time frame.
Very few studies have evaluated program completion of CSOs, as they are a
severely under-researched correctional option (Bouffard & Muftic, 2006). The one study
that has been conducted in the United States, so far, was performed by Bouffard and
Muftic (2006) in Fargo, North Dakota. Bouffard and Muftic sought to determine how
“seriousness” factors affected completion and recidivism. Seriousness factors in this
3
study included a whole range of extralegal considerations. Sociodemographic factors
were found to affect completion rates; however, the research setting, i.e., a small urban
town where many of the residents had similar characteristics may have affected the
diversity distinctions. Because of the idiosyncracies of the research setting, there are
issues with generalizability. Identifying the effects of sociodemographic factors is an
important gap to fill since previous research has found that sociodemographic factors
influence recidivism (Muiluvuori, 2001), offenders’ willingness to serve alternative
sanctions (May & Wood, 2005), and the type of work order/sentence an offender receives
(Meeker et al., 1992; Menzies & Vass, 1989). If sociodemographic factors influence
these areas, it is reasonable to believe that they will also affect an offender’s ability to
complete a community service sentence. If practitioners were made aware of these
differences, they could better design programs to fit specific types of offenders.
Additionally, this information would allow judges the ability to better adjudicate cases by
matching the offender to the most appropriate sentence. For this reason, this study will
attempt to answer the question: Do differences in sociodemographic factors influence
an offender’s successful completion of a community service order?
4
Chapter 2
LITERATURE REVIEW
Restorative Justice
Several different definitions of restorative justice (RJ) can be found in the
literature creating a problem discerning what programs/practices are restorative (Bonta,
Wallace-Capretta, Rooney & Mcanoy, 2002; McCold, 2004; Sullivan & Tifft, 2005). One
of the most useful definitions comes from Bazemore and Walgrave (1999) who define
restorative justice as, “action that is primarily oriented toward doing justice by repairing
the harm that has been caused by a crime” (p. 48). Restorative justice rejects the
dominant justice paradigm in the U.S. that relies on retribution and punishment and is
instead centered upon the ideals of rehabilitation and reparation. RJ seeks to repair the
damages to the offender, the victim, and the community, that crime inflicts (Bazemore &
Schiff, 2005; McCold, 2004; Sullivan & Tifft, 2005). Offenders, victims and the
community are the primary stakeholders in the restorative justice process and as such
Bazemore and Schiff (2005) argue that at least two of the groups must be included if a
program touts any real restorative connection. In the RJ process the stakeholders are
brought together to express their feelings regarding the crime and to negotiate a
resolution (McCold, 2004). For the process to work the offender must accept
responsibility for his/her crime (McCold, 2004; Sullivan & Tifft, 2005).
In discerning whether or not a program is based on a restorative philosophy
certain principles must exist. Van Ness and Strong (1997) capture this essence while
adding an emphasis on community restoration. Because of the focus that community
5
service programs place on community restoration these are the most appropriate foci of
this study. Bazemore and Schiff (2005) define these as:
1) The principle of repair - justice requires that we work to heal victims,
offenders, and communities that have been injured by crime.
2) The principle of stakeholder participation – victims, offenders, and
communities should have the opportunity for active involvement in the justice
process as early and as fully as possible.
3) The principle of transformation in community and government roles and
relationships – we must rethink the relative roles and responsibilities of
government and community. In promoting justice, government is responsible
for preserving a just order, and community for establishing a just peace (pp.
32-33).
Restorative justice has been identified as one of the major philosophies governing
the use and goals of community service programs; however, a review of the existing
literature highlights differing opinions as to how closely these programs resemble RJ
practices. McCold (2004) believes there is a difference between RJ and what he terms
community justice (i.e., community service programs) and that the two should be kept
separate because fusing them poses a serious threat to RJ. He claims this is because
community justice excludes the victim and that community is meant to refer to the victim
and the offender’s families and relatives, not the actual geographic community that was
harmed. However, many disagree with McCold’s assessment. Instead, community justice
and RJ are seen as complementary and that the latter is an essential component of the
former (Clear, 2004; Karp, 2004). Furthermore, merging the two is promising for social
and economic justice (Thomson, 2004) and adding community justice theory to RJ
practices ameliorates the shortcomings of RJ (Harris, 2004). These shortcomings include:
6
a failure to take violence seriously, to protect the rights of minority or juvenile groups,
and to deal with the unequal bargaining power of the parties (Harris, 2004). Thus, it
appears as though community justice and RJ have a symbiotic relationship with each
feeding on and strengthening the other.
According to McCold (2004), one of the major factors that hinders community
service programs’ acceptance as fully restorative is the exclusion of one of the
stakeholders, the victim. Although, CSOs can be directed to serve a specific victim, the
vast majority of them involve service to the community not to the actual victim(s)
(Agopian, 1989). Sullivan and Tifft (2005) also identify the exclusion of the victim as a
major shortcoming of programs claiming to be restorative. However, some crimes are
‘victimless’ and the majority of victims do not wish to be part of the restorative process
(Bonta et al., 2002; Karp, 2004). Bonta et al.’s (2002) analysis of a restorative program
found that only 12% of victims were willing to participate in the process. In cases of
‘victimless’ crimes most scholars tend to hold the view that the community is the
symbolic victim of crime. If the victim does not want to participate or the offender has
committed an act that is ‘victimless’, then the community is the victim and by completing
a CSO the offender is restoring the community through his/her service. During the
community service experience the offender is provided the opportunity to discuss his/her
feelings regarding the offense and the victims (community members) can tell the offender
how such crimes affect him/her.
McCold (2004) defines the community under RJ as the victim and offender’s
family and friends. Therefore, his second criticism is that community justice involves
7
members of the community who are not relevant to the issue at hand. Umbreit, Coates
and Vos (2004) claim that McCold’s definition is not that of a community but rather of a
social network and that is not how community is typically defined in RJ theory or
practice. Furthermore, Sullivan and Tifft (2005) claim that the community must involve
more than the family of those directly involved because crime indirectly affects others in
the community. Because the community is also harmed the response to crime must be
drawn from the community and ought to build and strengthen the community as well as
the victim and offender (Sullivan & Tifft, 2005). According to Caputo (2004),
community service is linked to the philosophy of restorative justice by a belief that crime
affects the entire community and that free labor benefits the community in a meaningful
way. Services provided by the offender through community service are meant to benefit
the victim, the community and the offender (Caputo, 2004). Community service is also
believed to incorporate many rehabilitative and beneficial aspects for the offender such as
developing job skills, the ability to make reparations, and freedom from incarceration.
Furthermore, many researchers have suggested changes to the practices of community
service programs that would increase the validity that community service is a restorative
justice practice (Bazemore & Maloney, 1994; Bouffard & Muftic, 2007; Gelsthrope &
Rex, 2004).
One of the key restorative justice suggestions made is that offenders should be
screened and matched to an appropriate work placement based on the offender’s skills,
needs, and offense (Gelsthrope & Rex, 2004). Taking the time to conduct this assessment
would have positive program and offender outcomes (Bazemore & Maloney, 1994). This
8
is in contrast to programs such as the one operated by the Vera Institute in New York
City where offenders are placed in large work parties that are not relevant to the
offender’s characteristics or his/her offense (McDonald, 1986). Evidence has defended
the use of personalized placements rather than work parties. Findings show that offenders
who are given personalized placements are more likely to benefit from this type of
sanction (Bouffard & Muftic, 2007; Gelsthrope & Rex, 2004). Programs such as one in
Los Angeles that requires gang members to clean up gang related graffiti from
neighborhoods (Agopian, 1989), or programs that require offenders convicted of littering
to perform trash pick-up, incorporate added restorative components. Matching offenders
to work sites that directly provide restoration to the community for the specific harm that
the offender has inflicted through the commission of his/her crime incorporates all three
principles of restorative justice. Karp (2004) argues that community service is consistent
with both RJ and community justice if a CSO is part of a collective decision-making
process, is linked to the harm caused, and serves to reintegrate the offender by developing
job skills and pro-social behavior.
Community service orders in Europe are more closely aligned with the principles
of restorative justice than are CSOs in the United States (Bouffard & Muftic, 2007). This
is primarily because the United States criminal justice system is based more heavily on
punitive crime policies such as incapacitation and retribution (Bazemore & Schiff, 2005;
Caputo, 2004). This is evident in the fact that the U.S. incarceration rate is the highest in
the world and is nearly five times higher than the rates in other Western nations (Sullivan
& Tifft, 2005). Caputo (2004) claims that when community service was first established
9
in the United States during the 1960s and 1970s the goal was “symbolic restitution”. The
objective of community service was to keep offenders who could not afford fines out of
jail and avoid the negative costs to offenders’ lives. However, the shift in criminal justice
policy from rehabilitation to retribution in the 1980s changed the goals of community
service programs as well. The goals of these programs became punishment and
retribution rather than restoration.
Community programs in England, Ontario, and Hong Kong have already achieved
the goal of specialized placements and work parties are not utilized in these countries (Lo
& Harris, 2004; Menzies & Vass, 1989). Despite these criticisms community service can
still be viewed as incorporating restorative justice philosophies. Additionally, Bouffard
and Muftic (2007) and Lo and Harris (2004) promote a move further in the direction of
restorative justice practices in community service programs. They advocate the use of
specialized placements, including all parties in the decision making process and,
matching offender, victim, and community needs. Bazemore and Schiff (2005) claim that
there is no absolute distinction of restorative justice on which to gauge programs and
practices, instead, “broad principle-based dimensions and degrees of what may be called
‘restorativeness’” must be created for real world situations that most closely achieve the
overall principles and values of restorative justice (p. 34).
Lack of Research in the United States
Evaluation research of restorative justice programs is scarce (Bonta et al., 2002).
Further compounding this issue is that despite the fact that community service programs
have been operating in the United States since the 1960s, relatively few studies have been
10
conducted to evaluate these programs (Bouffard & Muftic, 2006; Bouffard & Muftic,
2007; Killias, Aebi & Ribeaud, 2000). Bouffard and Muftic (2006) refer to community
service as, “a comparatively new and under-researched form of correctional option” (p. 2)
and according to Caputo (2004), “evaluation literature is quite modest” (p. 165). The vast
majority of evaluations have been conducted in Europe and other industrialized nations
(Bouffard & Muftic, 2006). Although the information available is valuable, their findings
may not be relevant and cannot be generalized to U.S. populations where crime rates
differ from other Western Nations. This is a problem because program evaluation is an
important aspect of criminal justice. Evaluation allows policy makers, practitioners and
others an opportunity to decide what is working, what needs to be changed, and where
resources should be allocated. Empirical evaluations of these programs would add
legitimacy to their continued use and provide information on how to improve their
quality.
Community service programs in the United States are considered intermediate
sanctions. Intermediate sanctions are punishments that fall somewhere between probation
and prison and are meant to be cost effective alternatives to incarceration or supervision
(Caputo, 2004). In contrast to European countries where community service is generally
utilized as an alternative to short term imprisonment (Bouffard & Muftic, 2007; Knapp,
Robertson & McIvor, 1992; Lo & Harris, 2004; Muiluvuori, 2001), community service in
the U.S. is typically reserved for less serious offenders and for fines for those convicted
of traffic violations (Bouffard & Muftic, 2006; Bouffard & Muftic, 2007; Caputo, 1999;
Harris & Lo, 2002). Evaluation research in the United States could lead to a greater use
11
of community service as a sentence for a broader range of offenses. A lack of empirical
research regarding the value of this option could be responsible for the limited use of this
alternative for chronic and more serious offenders (Caputo, 1999). One reason cited for
this shortcoming is a lack of uniformity in CSOs throughout the U.S. which has led to
very vague legal and operational variables (Harris & Lo, 2002) as well as unclear
objectives and goals (Bazemore & Maloney, 1994). Garcia (2004) goes further to claim
that the goals and objectives that are reported are unclear, diverse, and conflict with each
other. Goals range from those related to offender treatment to improvements of the
criminal justice system itself (Garcia, 2004). The lack of uniformity makes analysis and
evaluation of these programs difficult because the goals community service programs are
intended to achieve are inconsistent, thus researchers are uncertain how to evaluate them
(Bazemore & Maloney, 1994). Garcia (2004) suggests that a clear mission statement with
realistic goals and objectives will make evaluation of community service programs more
feasible. Additionally, she found that recidivism is the most common variable on which
community corrections programs are evaluated, which according to some, is
inappropriate (Garcia, 2004) and evaluation should instead be conducted based on the
program’s goals and objectives (Bazemore & Maloney, 1994). Bouffard and Muftic
(2006) specifically point out that recidivism and program completion are still severely
under-researched aspects of community service programs.
Recidivism
Given that recidivism is the main result on which community service programs
are evaluated (Garcia, 2004), a closer look at this outcome is necessary. Growing
12
numbers of offenders behind bars along with the cost of incarceration make alternatives
to imprisonment popular. Other countries have found that the use of community service
programs has led to decarceration effects because offenders are diverted from sentences
of jail or prison time (Caputo, 1999; Harris & Lo, 2002). Diverting offenders from
incarceration to community service programs is cost effective. A study conducted by
Knapp et al. (1992) in Scotland, where community service is funded by the government,
found that a CSO is much less expensive than custody. In fact, the costs for community
service were comparable to about six weeks of imprisonment. They found that savings
may be even greater for programs that are run by non-profit organizations and do not
receive government funding. Additionally, it is believed that the negative effects of
incarceration such as loss of employment and social contacts could be avoided through
community service and would therefore reduce recidivism (Spaans, 1998). Unfortunately,
it seems as though a negative consequence of community service may be net-widening, in
which more offenders are brought into the criminal justice system and receive harsher
punishments than they would if no alternatives existed (Knapp et al., 1992; Lo & Harris,
2004; Mair, 2004; Spaans, 1998). In fact, it is pointed out that if community options did
not exist, many of these offenders might otherwise have received fines (Mair, 2004).
Despite this negative consequence, findings suggest that more offenders are diverted
from prison using alternatives to incarceration (Spaans, 1998).
Negative costs of diversion from incarceration may exist when re-arrest and
recidivism are considered. Recidivism generally refers to repeated or continuing relapse
into a pattern of behavior, usually criminal. A study of one community service program
13
in New York City found that 25% of these offenders were re-arrested for an additional
charge sometime after the original sentencing and before the completion of their CSO
(Caputo, 1999). Caputo (1999) found that the majority of additional arrests in this study
were made for misdemeanor violations with only one person-related misdemeanor assault
and three low level non-violent felony offenses. Thus, it can be argued that if community
service programs did not exist these additional crimes may have been avoided but it
would also eliminate the projected rehabilitative or diversion benefits.
Findings regarding community services’ effects on recidivism rates are varied and
may rely more on extenuating factors rather than participation in this sanction. For
example, sociodemographic differences are significant factors in recidivism (Muiluvuori,
2001). Additionally, several studies have found factors that may be more closely
correlated with recidivism than whether or not an offender participates in a community
service program (Bouffard & Muftic, 2007; Spaans, 1998). These findings suggest that
the use of recidivism as a goal of community service may not be appropriate, and that
community service programs that adopt more objectives of restorative justice would lead
to more accurate evaluations.
When looking at the overall effectiveness of RJ programs at reducing recidivism
the results are promising. Bonta et al. (2002) found that when compared to juvenile
programs, adult programs are significantly more effective at reducing recidivism. Also,
when offenders who have gone through the RJ process commit new offenses, they tend to
be less serious than new offenses committed by offenders who have not (Dhami & Joy,
2007). Finally, Bonta et al. (2002) found that when community service was associated
14
with a restorative justice program recidivism was reduced. However, the same effect was
not found for community service when it was coupled with probation. Thus, community
service programs that incorporate restorative justice principles are more likely to reduce
recidivism than those that do not.
In determining whether or not recidivism is a legitimate goal for community
service programs it is important to compare the rates of recidivism to other forms of
punishment. Spaans (1998) found that those sentenced to community service or a
suspended prison sentence are significantly less likely to reoffend when compared to
offenders sentenced to unconditional prison sentences. According to Spaans, 83% of
those offenders in the unconditional prison sentence group reoffended within five years
as opposed to the suspended prison sentence group and in the community service group
which reoffended at a rate of 60%. However, offenders who were sentenced to
unconditional prison sentences had significantly longer prior police records than the
offenders in the community service group. This finding led to the conclusion that
community service programs are only partially able to reduce recidivism since recidivism
is more highly correlated to a history of prior police records than the type of sentence
received. Additionally, Muiluvuori (2001) using a quasiexperimental research design,
compared recidivism rates of 342 offenders given a CSO to offenders given a prison
sentence of up to eight months. No statistical differences in recidivism among the group
sentenced to prison and those sentenced to community service were found. This suggests
that community service can be utilized to divert offenders from incarceration and reduce
costs while still insuring public safety.
15
Recidivism was defined as “offences leading to conditional or unconditional
prison sentences or sentences to community service” (p. 76). However, after controlling
for drop-outs and no shows, Muiluvuori found that individuals who complete a CSO are
less likely to reoffend but if they do, they reoffend later when compared to the prison
group. This suggests that a closer look at program completion may provide insight into
which offenders are best suited for this type of sanction.
The majority if not all of the studies conducted on the recidivism rates for
community service programs use incarceration-bound offenders as a comparison group
which may be inappropriate (Bouffard & Muftic, 2007) especially in the U.S. where
community service is rarely used as an alternative to incarceration. For this reason
Bouffard and Muftic (2007) compared recidivism rates for community service to criminal
fines, which is a more likely sanction to be utilized for comparison purposes in the U.S.
Using a quasiexperimental research design Bouffard and Muftic compared a
sample of 200 offenders who received a CSO to a sample of 222 offenders sentenced to a
monetary fine for their first DUI offense. Arrest records were gathered from the local
police department in order to calculate recidivism rates. Offenders sentenced to
community service were considered to have become recidivists post-program if they were
arrested after the date of their successful completion or termination for the program while
in-program recidivism was recorded as those who were arrested for a new offense before
the date of their termination or completion of the CSO.
Recidivism was recorded for fined offenders if the offender had another arrest
after the date the fine was imposed. A bivariate analysis found that race and criminal
16
history were related to the probability that either group recommitted with non-whites and
offenders with a prior criminal record being more likely to recommit. A multivariate
analysis of, race, criminal history and offense type was found to be significantly related
to post-sentence recidivism. The same relationships were found for these variables as in
the bivariate analysis while interestingly, it was found that offenders charged with a
violent or property crime were less likely to reoffend at any point after receiving their
sentence.
Of the 200 offenders in the community service sample, 28 reoffended in-program
and these offenders were more likely to have a prior arrest record, be given more severe
sentences and be older. In comparing the two samples, offenders sentenced to community
service were less likely to reoffend than those given a traditional fine. This finding
supports the use of community service over monetary fines for reducing recidivism
especially when considering that the community service group had more severe prior
arrest records than the fined group. However, there was less likelihood of repeat
offending for anyone successfully completing either sentence. Therefore, it appears that
successfully complying with any court ordered sanction will reduce recidivism.
Despite the mixed findings, several studies have found at least some support for
the contention that completing a CSO does decrease recidivism (Bouffard & Muftic,
2006; Killias et al., 2000) and instances of delinquency (Killias et al., 2000).
Additionally, a survey of offenders’ attitudes toward community service indicates that
offenders in the program felt that their participation made them less likely to offend again
(Gelsthorpe & Rex, 2004). Interestingly, some offenders found the work to be enjoyable
17
and continued to donate their time or find employment with the agency even after their
community service obligation was completed (Knapp et al., 1992; Weisburd, Einat &
Kowalski, 2008). Although, participating in a community service program may not
dissuade offenders from committing further crimes or change their lives, it is still a useful
option as it benefits the community and is more cost efficient (Caputo, 1999).
Program Completion
Program completion is one of the main factors currently used in evaluating
community service programs (Gelsthorpe & Rex, 2004). Completion is generally defined
as an offender who fulfills the required amount of hours and abides by the programs
rules. Generally, research has shown that community service programs tend to have high
levels of completion (Caputo, 2004). A study performed in Finland in 1991 and 1992
found that the program had a completion rate of 85% after controlling for those who
never reported to the program (Muiluvouri, 2001). Similarly, a study from the
Netherlands found that despite a growing number of court referrals to community service
between the years 1981 and 1989 the failure rate remained relatively stable at 15% giving
the program an 85% completion rate (Spaans, 1998). Studies conducted in the United
States have shown a significantly similar rate of completion for community service
programs. Caputo’s (1999) New York City study had a completion rate of 71% and after
controlling for the offenders who never reported to the program a completion rate of
74%. This is exceptionally high considering that the contractual agreement for the
programs completion rate was only set at 60%. Thus, community service programs may
be more effective than practitioners had hoped, if program completion is a main goal of
18
these programs.
The lowest completion rate was found in a study conducted in Fargo, North
Dakota where the overall population of people sentenced to complete a CSO in 2003 had
a completion rate of 69% while the researcher’s random sample had a completion rate of
50% (Bouffard & Muftic, 2006; Bouffard & Muftic, 2007). Bouffard and Muftic (2006;
2007) also found that sociodemographic and case factors influenced offenders’
completion rates and that completing a community service sentence decreases recidivism
among adult offenders sentenced to a CSO. The above completion rates are especially
promising in regards to the effectiveness of community service programs. The research
shows these programs to have completion rates well over 50% and show that in some
cases even greater levels of success.
On the other hand, there are negative economic consequences for failures.
Failures occur when an offender fails to complete the assigned number of hours in the
allotted amount of time or when an offender fails to comply with the program’s
prescribed rules and regulations. Knapp et al. (1992) examined the costs of community
service in Scotland and found that breached (incomplete) orders were more expensive to
monitor than were completed orders. In fact, breached orders represent additional costs to
the court and in sentencing as well and these costs are shown to be high when compared
to completed orders, thus, reducing the cost effectiveness of community service
programs. However, only 10% of offenders in Knapp et al.’s study breached their order
and as such the negative costs associated with such outcomes are rather small.
Additionally, community service programs in Scotland are funded by the government in
19
contrast to some programs in the United states that are run by non-profit or local agencies
and do not receive government funding. The cost of breached orders in these nongovernment funded programs may be significantly less. The study also found that longer
orders were not more likely to be breached therefore they are no more costly.
Overall, it appears as though community service programs are very successful if
they are measured based on program completion. When offenders did fail the most
common reason cited is absenteeism (failure to report to work) and rule violations
(Caputo, 1999). Additionally, some studies found that offenders’ sociodemographic
differences may affect completion rates (Bouffard & Muftic, 2006; Muiluvuori, 2001).
Sociodemographic Differences
Experiences vary depending on social class, gender, race, age, and other markers
of social position and affect who we are and how we behave (Andersen & Collins, 1995).
According to Andersen and Collins (1995) “institutions are built from and then reflect the
historical and contemporary patterns of race, class and gender relations in society” (p.
192). Currently hegemony in the U.S. is based on the beliefs and experiences of white,
upper-class males while excluding those of minority and/or oppressed groups (Anderson
& Collins, 1995). Disregarding the effects of oppressed groups and their
sociodemographic differences leads to the formation of bad social policy which will serve
only to reproduce, rather than solve, social problems (Anderson & Collins, 1995; Dyck,
2000). Thus, community service programs, that are institutions of the justice system,
must explore sociodemographic differences of the people who participate in their
programs in order to implement effective policies.
20
Several studies have found that sociodemographic differences (i.e., age, sex,
ethnicity, income, education level) affect different aspects of CSOs. However, the results
are varied. A study conducted by Muiluvuori (2001) found that sociodemographic factors
affected completion rates and recidivism. Offenders who were older, had shorter
sentences, had never been in prison, and were not convicted of a property offense were
more likely to complete their CSOs. Muiluvuori’s findings also suggest that younger
offenders were more likely to drop-out of the program and reoffend sooner than older
offenders; however, after the completion of a CSO, the effects of age on recidivism were
not statistically significant. Additionally, Muiluvuori’s findings regarding age may be
skewed since the average age of those sentenced to community service was older in
Finland than in other countries and generally older than those who were sentenced to
prison. Therefore, these findings cannot be generalized to other countries. Conversely,
Bouffard and Muftic (2007) found that non-white offenders and those with a prior
criminal record were significantly more likely to reoffend. They also found that older
offenders were more likely to reoffend while still in the program than were younger
offenders. Also, in regards to completion, Gelsthorpe & Rex (2004), using the Pathfinder
projects found no association between the length of a CSO and completion but they did
find that offenders who were employed and those that were educated were more likely to
complete. The Pathfinder projects were community service programs meant to increase
job skills, help offender needs, and encourage responsible attitudes and behaviors and
were implemented in 10 probation areas throughout England and Wales.
Gender differences and their effects on CSOs have also been under-researched
21
(Gelsthorpe & Rex, 2004). Numerous studies have found that women are less likely to be
sentenced to community service than men (Caputo, 1999; Gelsthorpe & Rex, 2004;
Killias et al., 2000; Muiluvuori, 2001; Spaans, 1998). Gelsthorpe and Rex (2004) found
several other differences between women and men sentenced to complete a CSO. When
compared to their male counterparts, women were, on average, older, more likely to be
white, were better educated, had strong job qualifications, were less likely to be
employed, were in a stable living condition, and were more likely to be caring for
dependents. Men and women also differed on how they felt about their experience.
Women felt more confident that they had improved their skills and believed that their
community service would help them get a job. These findings suggest that men and
women experience community service sentences differently and these differences may
influence their chances of successful completion.
Other factors of CSOs are also affected by offender’s sociodemographic
differences. May & Wood (2005) found that sociodemographic factors influenced the
type and duration of an alternative sanction that offenders were willing to serve in order
to avoid one year in jail. They found that although gender did not affect whether or not an
individual chose to participate in an alternative sanction, it did affect the amount of time
individuals were willing to serve. They found that females were willing to serve longer
sentences of CSOs than males. Additionally, younger offenders were willing to serve
more months of community service to avoid one year in prison than their older
counterparts.
Meeker, Jesilow and Aranda (1992) found that the type of service offenders were
22
sentenced to was affected by sociodemographic factors. They found that sex and ethnicity
were linked to the type of CSO an offender received, but not to the amount of hours, to
which they were sentenced. Men and non-whites were more likely to receive work
sentences to Caltrans (California Department of Transportation), which is more labor
intensive than work at a non-profit organization. However, differences in sex and
ethnicity did not affect the amount of hours an offender was sentenced which normally
followed sentencing guidelines based on offense and prior record. Results suggest that
bias in sentencing occurs in decisions where judges have more discretion which is where
extralegal sociodemographic factors come in to play.
Finally, the odds of receiving a CSO can be influenced by sociodemographic
factors (Menzies &Vass, 1989). A study conducted by Menzies and Vass (1989)
comparing CSOs in England and Ontario found that gender affected whether or not an
individual was sentenced to complete a CSO. When compared to males, females were
less likely to receive a CSO in England but more likely to receive an order in Ontario.
These findings are most likely due to the fact that community service in England is
designated for those who would otherwise serve a short-term jail sentence, while CSOs in
Ontario are typically reserved for low-level offenders and in lieu of fines. This fact
accounts for the gender differences between the two countries since females are less
likely to commit serious offenses or have long criminal histories.
The Vera Institute
Perhaps the most comprehensive and in-depth study conducted in the United
States on community service programs to date was carried out by McDonald (1986)
23
for the Vera Institute in New York City. This study is so important to the literature as it is
cited by almost every study examining community service programs. The Vera Institute’s
Community Service Sentencing Project had two objectives. The first was to draw in
offenders who would otherwise have been sentenced to jail and the second was to provide
a punitive response to offenders whose offenses did not warrant jail but were too severe
to receive probation. The Institute’s project operated in three boroughs of New York
City: the Bronx, Brooklyn, and Manhattan. McDonald’s research was meant to explore
what happens when a new criminal justice sanction is imposed and to explore the effect it
has on those receiving the sentence and to the community as a whole. From the time of
the project’s inception in 1979 until 1983, about one thousand offenders city-wide were
being sentenced to the project annually.
Several different methods were utilized to evaluate different outcomes of the
Community Service Project. Analysis showed it to have a completion rate between 8589% for all three boroughs. McDonald found that decarceration effects were especially
high in Manhattan where about two-thirds of offenders were diverted from a jail sanction
which exceeded the expectations of the institute. In the other two boroughs, decarceration
affects were much lower but a restructuring in the way these two courts sentenced
offenders to the project in 1983 raised the rates to about the same as those in Manhattan.
McDonald was able to gather information on the project’s likely recidivism rates by
compiling arrest records for 494 offenders sentenced to the project during 1981-1982
from the three boroughs. He found that within 180 days of being given a CSO 43% of
offenders were re-arrested, most for nonviolent offenses. Additionally, in Manhattan, the
24
number of offenders who had been re-arrested grew to 69% within a year. McDonald
suggested that this was due to the relatively lengthy criminal histories of participants not
because of evidence that a jail sentence would have deterred offenders from committing
further crimes and there was no indication that jail sentences had any greater
rehabilitation effects.
In an additional experiment by McDonald, interviews were conducted with 81 of
the Institute’s participants during the months from July-September of 1982. These
offenders constituted half of the participants sentenced during this period and were
randomly chosen so that they would represent the entire population during this time
period. The results found that offenders in the project were typically black or Hispanic
men in their mid-twenties who were single and had few to no dependents. Most of the
participants were low income, had several prior arrests, had received prison sentences and
were arraigned for nonviolent property offenses. Additionally, McDonald found that the
majority of offenders did not see their work as restitution, other than in a vague sense. In
fact, many of the offenders did not see their crimes as involving victims. Although there
was some ambivalence in answering, two-thirds of the offenders did not see their CSO as
a punishment because they had not received jail time and the required work was no more
demanding than a regular job. For the one-third of offenders who felt the sanction was
punitive the most often cited reason was the lack of pay.
McDonald made three broad conclusions. The first was that community service is
not a panacea because it did not stop offenders from committing additional crimes. The
second is that despite the costs of community service, it is a valuable addition to the list
25
of available sanctions. Although, community service costs less than incarceration, using
community service as a substitute to incarceration does not decrease jail populations
because other offenders replace those who were diverted. The third conclusion is that the
project demonstrated that despite popular belief, the courts could be restructured to
sentence offenders to community service rather than jail time. Finally, McDonald
concluded that community service had both positive and negative consequences. The first
positive consequence is that instead of offenders sitting in jail at taxpayer expense, they
are performing valuable work and services in the community. Second, the use of
community service in lieu of jail creates room in jails and prisons for more serious
offenders. The third positive consequence is that the community service option provides
the courts greater flexibility in having punishments that fit the crime and the criminal.
The negative consequences associated with the sentence included the financial cost of
running the program and the inability to prevent crimes that those sentenced to the project
could not have committed if they were in jail. However, evidence suggests that if
sentenced to jail, these offenders would have committed additional crimes in the same
amount of time once released.
One of the major limitations of this study is that it was conducted almost 30 years
ago suggesting that its findings may no longer be applicable to today’s offenders and
their practices. Additionally, the program specialized in offenders who were likely to be
sentenced to jail and therefore are not representative of the majority of United States
community service programs that are usually only utilized for minor offenders.
26
Sociodemographic Effects on Program Completion
A plethora of studies have been conducted in European countries that examine the
outcomes of CSOs; however, comparatively few studies in the United States have done
the same (Bouffard & Muftic, 2006). The most common reason cited for this
inconsistency is a lack of uniformity for the goals and objectives of CSOs in the U.S. For
this reason, Bouffard and Muftic’s (2006) North Dakota research explored whether or not
offender characteristics affect program completion and evaluated program recidivism to
determine the effectiveness of community service sentences. This was done to determine
which offenders were most appropriate for this type of sanction and if the use of CSOs
should be expanded beyond low-level offenders.
Bouffard and Muftic (2006) selected offenders from RESTORE, which is a nonprofit community-based corrections agency. The participants were chosen from agency
records during 2003. The total population consisted of 810 adult offenders and a sample
of 200 offenders were randomly selected and used for the statistics gathered on offender
characteristics. A second sample using 100 clients who were randomly selected from the
total population of 560 offenders who successfully completed the program and another
100 offenders were randomly selected from the total population of 250 offenders who did
not complete the program was obtained. This second sample of participants was used in
the analysis on recidivism and a single officer collected criminal histories for the entire
sample.
The variables analyzed in the first sample of participants included gender,
ethnicity, age, education, the number of hours to be completed, previous community
27
service sentences, the referral source, the number of days given to complete the sentence,
offense charge and whether or not the participant completed. For the second sample, the
variables considered included prior arrest history and re-arrest records during or
following their CSO.
Findings suggest that offenders who completed the CSO were more likely to be
young, white, have a higher level of education, received a lower number of hours, were
given less time to complete their sentence, and were referred directly from court rather
than probation or parole. Additionally, the study found offenders with prior arrest
records, older offenders and non-white offenders were more likely to be re-arrested
during the program. Results also indicate that post-program arrest was higher among
individuals with the above-mentioned characteristics as well as those who had more
community service hours and more time to complete their sentence. Recidivism was
drastically decreased if the offenders had been directly referred by the court, had attended
some college, and had less time to complete their sentences.
These results indicate that completing a community service sentence decreases
recidivism among adult offenders sentenced to a CSO. It also indicates that not everyone
may be an appropriate candidate for this type of sanction. The analysis revealed that
offender characteristics influenced whether or not the CSO was completed. As such,
Bouffard and Muftic suggest that those who sentence offenders to serve this type of
sanction should consider these factors when determining whether or not it is an
appropriate sentence.
Although, Bouffard and Muftic shed light on many important aspects that affect
28
community service program completion and outcomes, more research is needed. Due to
the relatively small samples, these results cannot be generalized to other programs. The
sample was also predominantly white and three fourths of the participants were male thus
biasing the results and diminishing representativeness of the study’s findings.
Theory
Individual choices and behaviors are influenced by a variety of factors ranging
from biology to environmental and other social effects. The process by which a person’s
behaviors, thoughts and feelings are affected by social forces is known as social influence
(Cialdini & Goldstein, 2004; Nail & Helton, 1999). Two types of social influence aid in
the understanding of an individual’s choice to complete a CSO, conformity and
compliance. An offender who completes a CSO has complied with the order and as such
has conformed to the sanction.
Conformity is the process by which an individual changes his/her behavior to
match the real or perceived prevailing social norms, attitudes or beliefs (Cialdini &
Goldstein, 2004). Conformity is a group phenomenon that occurs in both small groups
and in society as a whole. Research on conformity is generally conducted in a group
setting and examines overt social pressure or unconscious/perceived pressure. The
motivation to conform comes from a need to obtain social approval or a desire to
accurately interpret reality and behave accordingly (Cialdini & Goldstein, 2004).
Compliance, on the other hand, refers to acquiescence (Cialdini & Goldstein, 2004) or
more generally, the act of conforming. According to compliance theory, individuals
attempt to achieve their goals in the most efficient and rewarding manner possible
29
(Cialdini & Goldstein, 2004). For this process to work an offender must have an accurate
perception of reality and must be able to correctly process and react to new information
(Cialdini & Goldstein, 2004). However, Cialdini (1993) notes that as technology and
society advances so too does the amount of information that needs to be processed. This
ever increasing amount of information causes people to use shortcuts in order to process
the information and make a decision. He identifies several situations that have the ability
to illicit automatic and mindless compliance from people, most of which is achieved
without the person’s knowledge.
Cialdini refers to acts used to increase a person’s willingness to comply with a
request as ‘weapons of influence’. People use ‘shortcuts’ in their everyday lives in order
to process information more efficiently and make a decision. These shortcuts include the
belief that more expensive things have higher quality, that a scarce item is superior to an
abundant item, that people who appear to be an authority on a subject should be trusted
and their orders followed, etc. (Cialdini, 1993). However, these shortcuts can be
exploited and become weapons to increase compliance by sales people and those wishing
to gain something through another’s willingness to behave in a way beneficial to the
other person (Cialdini, 1993). However, these weapons are not the only factor influencing
compliance.
Demographic and social factors also have an effect on compliance and therefore
need to be addressed. According to Dyck (2000), restorative justice programs fail to
address the social and structural aspects of criminal conflict. These conflicts are rooted in
ethnicity/race, gender, class, and other factors and RJ programs should seek to address
30
not only the specific issue at hand but also the underlying structural causes of crime
(Dyck, 2000). Therefore, community service programs need to address the
sociodemographic factors that are rooted in conflicts by identifying differences and
working to correct them. For this reason, this research will examine sociodemographic
factors as they affect compliance and conformity to a legal sanction, the completion of
court ordered community service.
The literature on conformity and compliance has shown that sociodemographic
characteristics have an effect on these forms of social influence. One of the strongest
correlations is gender. Gender is a learned identity that is structured in social institutions
and is a set of characteristics used to distinguish between males and females (Andersen &
Collins, 1995). Typically, gender is used interchangeably with the word sex to denote the
biological condition of being male or female. Conformity and compliance research has
shown that there are differences in which individuals respond to social influence based on
gender. Research has shown that American women are more likely to have a positive
attitude toward the legal system than American men (Torney, 1971). Conformity research
has also found that women are more susceptible to group influence (Crutchfield, 1955;
Beloff, 1958) and are more likely to comply with traffic laws than men are (Sigelman &
Sigelman, 1976). However, women are not more likely than men to conform on feminine
topics (such as cosmetics or apparel) or in areas in which they are more familiar (Sistrunk
& McDavid, 1971). Furthermore Beloff (1958) distinguished between acquiescent
conformity in which people conform to an expressed group opinion based on social
pressure and conventional conformity in which people conform to the behaviors and
31
attitudes of their culture or subculture. Even though women were more likely to conform
than men in both types of conformity, the differences were not significant for
acquiescence but were very significant for conventionality. Thus, women are
significantly more likely to conform to certain types of conformity such as conventional
conformity than others and they are most likely to conform to conventional factors such
as legal sanctions.
Research regarding the effects of ethnicity on conformity are mixed and complex.
Ethnicity refers to, “identity with or membership in a particular racial, national, or
cultural group and observance of that group’s customs, beliefs, and language” (Hirsch,
Trefil & Kett, 2005, retrieved from http://dictionary.reference.com/browse/ethnicity).
Since the dominant national identity in the U.S. is Caucasian, Americans disregard the
distinctions between ethnicity and race and the two terms are used interchangeably
without regard to differences in language, culture, or other factors (Andersen & Collins,
1995). Thus, some programs will use the term ethnicity when referring to racial
categories. Even though there are differences between race and ethnicity, people in one
racial group will experience the same institutional prejudices regardless of their ethnicity
(Andersen & Collins, 1995) so interchanging the two words will not affect the findings of
this study. Traditionally cultures and ethnicities from collectivist countries (usually found
in eastern and southern nations) are more likely to conform than people from cultures and
ethnicities in individualist countries (usually found in western industrialized nations)
(Triandis, Bontempo, Villareal, Asai, & Lucca, 1988; Suizzo, 2007). However, the
effects of ethnicity on conformity are much more complex.
32
Literature on completion of a CSO shows that white offenders are the most likely
ethnic group to conform to program rules and regulations, while the literature on
completion of drug or alcohol treatment programs has mixed results. One study found
that white women were more likely to complete an all female residential substance abuse
treatment program (Knight, Logan, & Simpson, 2001) while another study found that
white clients were more likely to complete outpatient drug treatment but less likely to
complete inpatient drug treatment (Wickizer, Maynard, Atherly, Frederick, Koepsell,
Krupski, & Stark, 1994). Wickizer et al. (1994) hypothesizes that members of those
ethnic groups whose norms and culture fit with those of the program will be the most
likely to complete their orders. This may help to explain why white offenders are more
likely to comply with a CSO than other ethnicities since American law and sanctions are
based heavily upon Anglo-Saxon (or western) traditions (Andersen & Collins, 1995).
According to Yngvesson (1995) restorative justice practices are dominated by white,
middle- to upper-class professionals. Despite the melting pot theory of America, many
minority groups in the U.S. still maintain strong ties to their ethnic group and many live
in communities in which their traditional ways of life are maintained (Andersen &
Collins, 1995; Hirsch et al., 2002). Although collectivist cultures exhibit high levels of
conformity toward their in-group they may actually be non-conformists toward members
of an out-group (Triandis et al., 1988). Following this reasoning, white offenders are
more likely to conform to the rules and regulations of a CSO than people belonging to
other ethnic groups.
According to Andersen and Collins (1995), equality of education does not lead to
33
equality of income, however, education does improve the situation of disadvantaged
groups and is important to any struggle to reduce inequality. Education level can be
linked to income because research has shown that income increases with higher levels of
education (Baum & Payea, 2005). Although research has found that those who are more
affluent (i.e., those that are educated and have higher levels of income) are more likely to
be positively associated with individualist goals and thus less likely to conform (Suizzo,
2007; Triandis et al., 1988), many studies have found that those who are more educated
and wealthier are more likely to comply to program rules and health regulations (Hahn &
King, 1982; Knight et al., 2001; Touvier, Kesse-Guyot, Méjean, Estaquio, Péneau,
Hercberg & Castetbon, 2010; Wickizer et al., 1994). Studies have shown that those with
higher income levels and levels of education were more likely to comply with nutrition
and health program recommendations (Touvier et al., 2010). Additionally, those who
complete drug treatment programs and therefore comply with the program, are more
likely to be wealthier (Hahn & King, 1982) and to have higher levels of education
(Knight et al., 2001; Wickizer et al., 1994). These findings are similar to those found in
the literature on completion of community service orders.
Evidence supporting the effects of age on conformity is scarce in the literature.
Research regarding community service programs shows ambiguous findings on the
effects of age on program completion which may be conceptualized as conformity to this
sanction. However, findings from a study conducted by Sigelman and Sigelman (1976)
found that older drivers were more likely to comply to a red light traffic law than were
younger drivers. Zhou, Horrey and Yu (2009) also found that in China, older individuals
34
were less likely to conform to risky street crossing behaviors than younger offenders.
Additionally, research from substance abuse treatment has shown that older people are
much more likely to complete the treatment program (Grella, 1999; Wickizer et al.,
1994). Taken together these studies show that older offenders are less likely to comply to
illegal or risky behaviors but more likely than younger offenders to comply with rules
and regulations.
The goal of this research is to determine whether or not sociodemographic factors
influence CSO completion rates. As such, the following hypotheses were derived:
H01: Gender will not affect the likelihood of completing a CSO;
Ha1: Women will be more likely to complete a community service order than men;
H02: Ethnicity will not affect the likelihood of completing a CSO;
Ha2: White offenders will be more likely to complete a CSO than non-white offenders;
H03: Education will not affect the likelihood of completing a CSO;
Ha3: Offenders with higher levels of education will be more likely to complete a CSO
than offenders with lower levels of education;
H4: Offenders who have higher levels of income will be more likely to complete a CSO
than offenders with lower levels of income; and
H5: Older offenders will be more likely to complete a CSO than younger offenders.
35
Chapter 3
METHODOLOGY
Introduction
This research explores the relationship between sociodemographic factors and
completion of a community service order. The dependent variable in this study is
program completion while the independent variables include age, gender, ethnicity/race,
income, and educational level (see Appendix A). The independent variables are measures
of an offender’s sociodemographic factors that could affect his/her likelihood of
completing a CSO.
Population
The study population was drawn from offenders who were sentenced to complete
a CSO in Sacramento, California and were clients at the Alternative Sentencing Program
(ASP) which is part of the Volunteer Center of Sacramento. This agency is a non-profit
organization that contracts with the Sacramento County Court to provide supervision to
offenders sentenced to court ordered community service. As such, this program does not
receive any form of federal or other governmental funding. Instead, it is financed entirely
through fees charged to the offender for supervision of their CSO. Program fees are based
on an increasing scale according to the number of hours the offender is sentenced to
complete. Low-income offenders receive discounted services after they provide proof of
their financial hardships. Since the program diverts offenders from the justice system but
is not funded by the government, it stands to reason that this option decreases costs to the
criminal justice system.
36
The majority of offenders who participate in ASP are referred by a judge through
the Sacramento County Court. However, offenders who are sentenced in other counties or
states but who reside in Sacramento County can have their cases transferred with the
approval of his/her sentencing jurisdiction. During the disposition phase of a court
proceeding, a judge sentences an offender to a certain amount of community service
hours, which are usually converted on a scale based on the violation, the amount of the
fine, and/or the number of days in jail that the offender is attempting to avoid. The judge
also determines the date in which the offender must have his/her hours completed. This
process is sometimes conducted by a probation officer for violations of probation or past
discrepancies, but these cases are rare.
Once an offender is sentenced to the program s/he is given ten days to report to
ASP. An offender who fails to report to the program after a month’s time or before
his/her required completion date (whichever comes first) will be terminated from the
program as a no-show. Once an offender reports to the program s/he is required to fill out
a client agreement form which contains the agency’s rules and regulations and personal
information about the client. After the agreement form is completed the offender is
assigned to a caseworker who is responsible for explaining the program’s rules and
regulations, and for matching the offender with an appropriate agency. Program
guidelines instruct caseworkers to base offender placements on the court’s objectives, the
offender’s characteristics (i.e., skills, disabilities, schedule, and transportation) and the
work site agency’s needs and regulations. According to the agreement between the
Superior Court of California, Sacramento and ASP the practices of the program are based
37
on a restorative justice model. Indeed, the practices used by the program to determine
offender-assignment mirror those described by Gelsthorpe and Rex (2004) and Bazemore
and Maloney (1994) as activities that strengthen the community service program’s
commitment to restorative principles.
Furthermore, ASP contracts with over 200 non-profit agencies throughout
Sacramento County offering offender placement. Approved employees at each non-profit
agency supervise the offender’s work and sign off on his/her hours on an ASP timesheet
whenever s/he works. The approved hours are then reported to ASP and given to the
appropriate caseworker. The caseworker is responsible for guiding the offender through
the process, monitoring his/her hours, and verifying the authenticity of the signatures on
the offender’s timesheet. Additionally, the caseworker is responsible for notifying the
courts of completions and failures.
The study population used for this research included all offenders whose CSOs
were closed between January 1, 2008 until December 31, 2008 as either a completion or a
failure. The ASP was chosen because of access to the program and the program director’s
willingness to grant access to any necessary data which was advantageous for budget and
time constraints. Additionally, Sacramento County was chosen because it has a relatively
large and diverse population and ASP has a large number of clients which makes findings
more reliable and easier to generalize to other community service programs.
The total population of the study included 13,789 cases that were closed in the
year 2008. Per the design of this study, certain cases were excluded from the sample
frame. The first set of cases that were excluded were 58 vacated cases. When a case is
38
vacated it means that the offender is no longer required to participate in the ASP. Most
cases are vacated if the offender has chosen to fulfill the court obligation in another way
i.e., paying a fine, going to traffic school, being incarcerated, or some other form of
punishment. In rare cases, if the client passes away before completing his/her CSO this
counts as vacated. Confirmation is received from the court or via a death certificate
before a caseworker or administrative assistant vacates a case. Since vacated cases are
those in which the offender is no longer required to complete a CSO they were deleted
from this study. The second set of cases that were excluded were 3,469 no-shows, which
means that the client never reported to ASP to sign up. No-shows were determined
through the use of the disposition. This category records the reason why a case is sent
back to court for further disposition. The no-shows were excluded because they would
reflect a false negative picture of ASP since they would have to be coded as failures.
Additionally, sociodemographic information could not be obtained for these offenders.
The third set of cases to be excluded were 1,611 cases where an offender had multiple
cases closed in 2008. In this scenario only one of the cases were included in the sampling
frame. Multiple cases for the same client were excluded because they would bias the data
giving an offender with multiple cases a greater likelihood of being selected into the
sample and therefore skewing sociodemographic data.
In order to find the clients who had multiple cases closed out in 2008 the data
were sorted by the client’s ID number. The first case referred to ASP was the case that
was kept for the sample frame. If an offender had more than one case referred at the same
time then a computerized random number generator was used to determine which case
39
was kept for the sample frame. These rules were used to reduce bias in the results. The
fourth set of cases that were excluded were 453 juvenile cases. Juveniles were excluded
because they are a protected population and consent would be required from the
juvenile’s parent or guardian. The final set of cases that were excluded were 209 cases
that did not contain any information on four of the sociodemographic categories. Since
these cases did not include sociodemographic data they could not be analyzed and were
therefore excluded.
Sampling Technique
After all the exclusions were made, the sampling frame included 7,989 cases. Due
to the large number of cases in the population a sample was drawn for analytic purposes.
A confidence level, a confidence interval and the population size were used to determine
the appropriate sample size (Babbie, 2007). The sample size for this study was chosen
using a confidence level of ninety-five and a confidence interval of three. Using an
internet web site and these parameters it was determined that the sample size would be
941 cases (http://www.surveysystem.com/sscalc.htm).
The sample population was drawn from these cases using simple random
sampling. This technique was chosen because a list of all of the elements in the
population was available. Data were provided in an Excel document and was then
uploaded to SPSS to select the sample and analyze the data. All of the elements in the
population were numbered on the SPSS spreadsheet between number 1 and 7,989. SPSS
was used to generate random numbers and picked the 941 cases to include in the sample.
40
Data Collection Strategy
Data regarding certain variables such as ethnicity/race, gender, education level,
and income were collected through self-reported information on the client agreement
form (see Appendix B) given to clients before their initial interviews. When a client
reports to ASP to enroll s/he is given this form which is attached to the agency’s rules
and regulations. The information regarding client sociodemographic information is
voluntary and the form states that this information is used for statistical purposes only.
Date of birth was collected from information provided on the court referral form (see
Appendix C). The court referral form is filled out by the court clerk after sentencing and
provides all of the necessary client and case information. After the clerk fills out this
form, a copy is given to the client, and another copy is sent to ASP through inter-office
mail. This referral form outlines for ASP the parameters on which to supervise the client
and is a contract between the courts, the client and ASP which informs all parties what is
expected of the client.
All of the data collected from the client agreement form and the court referral
form are entered into Microsoft Access which is a database that ASP uses to house all of
its information. The database holds a separate file for each client with sub-files that
contain all of the court information for each individual case. Administrative assistants are
responsible for entering all of the court referral forms into the system while individual
caseworkers are responsible for entering the self-reported information on the client
agreement form.
The Microsoft Access system allows the creation of a statistical report based on
41
the offender’s disposition date. The date parameters are entered into the program, January
1, 2008 to December 31, 2008, and then allows a user to choose which categories from
the database will be included in the report. After all of the categories are selected, the
system allows the user to convert the information into a Microsoft Excel spreadsheet. The
program director was responsible for compiling all of the information and downloading it
onto a compact disk.
All identifying information such as client’s name, address, phone number(s) and
court cross-reference numbers were excluded. The only identification is a client ID
number that is sequentially assigned as clients are entered into the system. However, the
system cannot search clients based on their ID number alone, therefore offender
anonymity is assured.
Data Entry
Since sociodemographic information is self-reported and voluntary it is
sometimes necessary for caseworkers to interpret this information. If an offender has
chosen not to report his/her gender then the caseworker will enter the gender of the
offender based on appearance or if it is uncertain, the caseworker will obtain the
information from the offender’s drivers license. In instances where offenders do not
report his/her ethnicity/race, caseworkers either leave this information blank or record the
response as ‘other’. If the offender circled more than one ethnicity/race the caseworker
recorded them as ‘other’ or chose the ethnicity/race for which the client most greatly
resembles. Clients can self-identify as ‘other’ if they do not feel as though they belong to
any of the listed ethnicities. In regards to education level, either no entry is made or a 0 is
42
recorded for a client who failed to provide this information. Therefore, both the blank and
0 entries will be calculated as missing data.
An offender’s education level is recorded in the Microsoft Access database
numerically ranging from 1-20 with one being first grade and each subsequent grade
following. The question on the client agreement form for education level is open ended
and as such not all offenders report his/her education level numerically. However, there is
a standard set of open ended responses offenders use. In cases when an offender writes
“GED” “Diploma” or “High School” the caseworker equates these responses with the
number 12. For offenders who report “Some college” or “first year of college” the case
worker equates this with the number 13; an offender who reports “AA degree” is given
the number 14; an offender who reports “bachelor’s degree” is assigned the number 16;
an offender who reports “Master’s degree” is assigned the number 18; and an offender
who reports “PHD” or “doctorate” is assigned the number 20. Finally, the last selfreported variable, income, is entered with the amount the offender provides. This variable
is the most likely to be left blank by an offender because s/he does not feel comfortable
supplying this information. Also, many offenders are unemployed and as such report “0”
or “none”. In both of the above instances the caseworker will either not enter anything
under income in Microsoft Access or a 0; both answers will be counted as missing data.
The remaining variables are derived from the court referral form and as such are entered
exactly as they appear on the form.
Measures
The variable ethnicity/race originally included seven categories: African-
43
American, Asian, Caucasian, Hispanic, Native American, Pacific Islander/Polynesian,
and Other. However, there were relatively few Asian, Native American, and Pacific
Islander/Polynesian respondents and for this reason they were included in the Other
category for purposes of analysis. Therefore, ethnicity/race was collapsed into four
categories which included: African-American, Caucasian (which will be referred to as
White), Hispanic, and Other.
In the original data set, education was originally coded as “last grade completed”
(which was changed to education when the data were collapsed) with responses ranging
from 1-20. These categories were collapsed for reporting purposes into three categories:
less than HS or GED, HS or GED, more than HS or GED. These categories were chosen
based on the distribution of the data and reflect practices found in the literature (Bouffard
& Muftic, 2006). (See Appendix D for a detailed description of measurement issues
encountered in this research).
Limitations
Due to the method of data collection and the means by which it is entered into the
system there are some limitations to this study. Reliability and validity issues arise from
the data because some offenders may not have been truthful about certain information,
especially education level and income. Offenders might also choose to withhold
information because it is not required and or they feel uncomfortable answering certain
questions. However, misinformation is rare considering the voluntary nature of selfreports and that the information is being collected in order to fulfill a court ordered
obligation. Additionally, data entry errors may also decrease validity in the study since
44
ASP staff may not have correctly entered all of the information, may not have recorded
all of the information, or may have made incorrect decisions when determining an
offender’s ethnicity/race. The most common categories for entry errors would be for the
self-reported sociodemographic variables. However, errors are not typical and are
sometimes corrected throughout the course of the offender’s case. Information on the
court referral form is much less likely to be entered incorrectly and will be reliable
because it is cross-referenced repeatedly by the caseworker, the client and the court.
The final limitation to this study is missing data or data that were not entered into
the system. The most likely variables to be missing data are the sociodemographic factors
which are not required, self-reported and are additionally not necessary for the
supervision of a case so some caseworkers may forget to enter them. However, based on
analysis of the population it appears as though this is rare. The majority of variables have
few to no missing responses with the exception of income.
45
Chapter 4
ANALYSIS OF FINDINGS
Analytic Plan
A bivariate analysis was conducted with each independent variable against the
dependent variable. Nominal level data crosstabulations were used to analyze the
numbers and percentages for each category of the independent variable against each
category of the dependent variable. Chi-square analysis, as a measure of association, was
used as a test of significance for gender, ethnicity/race, and education. This test was used
because the data for both the independent and dependent variables are nominal.
When looking at all of the measures of central tendency for income and age, it
was clear that they were not normally distributed. For this reason, the median was used as
a measure of central tendency and to study the relationship each of these variables had on
program completion. This measure for central tendency was determined for those who
completed against those who failed to determine what effect the independent variables of
income and age had on the dependent variable program completion. The variables were
also broken down in the same fashion for the mode in order to provide a more thorough
analysis.
Population Univariate Analysis
The agency’s database contained information on 13,789 adult offenders after
excluding certain groups there were 7,989 who qualified for this study and had been
ordered to complete a community service order during the period of January 1, 2008
through December 31, 2008. During this time period 5,258 offenders (65.8%)
46
successfully completed their CSO. Table 1 provides descriptive statistics for the
population. Male offenders constituted more than half of the population (57.9%), and
whites were the largest ethnic/racial group (36.9%). More than two-thirds of the
population had at least graduated high school or obtained their GED and 30.5% had at
least some college education. Of the respondents reporting their income, one third
(34.5%) had an annual income of $1-20,000 and only 2.2% of respondents made $60,001
or more a year. The median age was 31 years and the mode was 19 years thus the
variable was not evenly distributed; however, the largest age group was the 18-25 year
olds who represented almost one-third of the population (See Table 1).
47
Table 1: Description of Sociodemographic Factors
Population
Parameters
Sample
Statistics
Male
Female
57.9%
42.1%
59.1%
40.9%
African-American
Hispanic
White
Other
Missing
28.9%
18.1%
36.9%
15.3%
0.8%
30.1%
16.9%
37.4%
15.1%
0.5%
Less than HS no GED
HS or GED
More than HS and GED
Missing
14.9%
50.9%
30.5%
3.8%
14.5%
52.3%
29.8%
3.5%
Median
Mode
$1-20,000
$20,001-40,000
$40,001-60,000
$60,001-80,000
$80,001+
Missing
$12,780
$12,000
34.5%
11.6%
3.4%
1.3%
0.9%
48.4%
$14,000
$12,000
34.5%
13.3%
4.1%
1.5%
0.5%
46.0%
Median
Mode
18-25
26-35
36-45
46-55
56+
Missing
31 Years
19 Years
33.4%
24.0%
19.6%
15.4%
7.0%
0.6%
31 Years
20 Years
34.2%
23.7%
17.7%
15.7%
8.4%
0.2%
Variable
Gender
Ethnicity/Race
Education
Income
Age
Note: Values may not total to 100% due to rounding.
48
Sample Univariate Analysis
Using a confidence level of ninety-five and a confidence interval of three 941
offenders were chosen for the sample. Over half of the offenders (64.2%) successfully
completed their CSO. Table 1 provides a description of the sample. The majority of
offenders were male (59.1%) and the largest ethnic/racial group was white (37.4%). The
majority of offenders (82.1%) had at least a high school diploma or GED and 29.8% had
at least some college education. Of those respondents who reported their income, the
largest income bracket was between $1-20,000 a year (34.5%) with only 2% of the
sample having an annual income of $60,001 or more. The median age for the sample was
31 years and the mode was 20 years while the largest age group (34.2%) was between the
ages of 18-25 years of age. Table1 also shows that the data from the sample are very
similar to those from the population, thus the sample is representative of the population.
Bivariate Analysis
The first hypotheses tested state that: gender will not affect the likelihood of
completing a CSO; and alternatively, women will be more likely to complete a
community service order than men. Results shown in Table 2, report that 66.7% of men
completed their CSO compared to 60.5% of women. Thus, men are somewhat more
likely to complete a CSO than women. The chi-square value was 3.813 with one degree
of freedom and a two-tailed probability of .051. Although it appears that there is a
significant difference in program completion rates between females and males, a
probability of this size is not significant and still allows for 5.1% of error, therefore the
results indicate failure to reject the null hypothesis and the alternative hypothesis is also
49
rejected. Women were not more likely to complete a CSO than were men and gender
does not have a significant effect on program completion.
Table 2: Effects of Gender on Program Completion
Program
Gender
Completion
Female
Male
Completed
233
60.5%
371
66.7%
Failed
152
39.5%
185
33.3%
Total
385 100.0%
556
100.0%
2
n= 941 x = 3.813 df= 1
α=.051
The second hypotheses were: Ethnicity will not affect the likelihood of
completing a CSO; and alternatively, white offenders will be more likely to complete a
CSO than non-white offenders. However, analysis shows that Hispanic offenders, not
white offenders, were the most likely ethnic/racial group to complete their CSO. Looking
at Table 3 it is evident that Hispanics were the most likely ethnic/racial group to complete
their CSO (69.2%), followed by Other (69%), whites (61.9%), and African-Americans
(61.8%). Therefore, the direction of the hypothesis is not supported. The chi-square value
was 4.625 with three degrees of freedom and a two-tailed probability of .201. Although
there are some differences in the completion rates of different ethnic/racial groups, a
probability of this size is not significant and allows for 20% of error. Therefore, the null
hypothesis cannot be rejected and the researcher also rejects the alternative hypothesis.
White offenders were not more likely to complete a CSO than were non-white offenders
and ethnicity/race does not have a significant effect on completion of a CSO.
50
Table 3: Effects of Ethnicity/Race on Program Completion
Program
Ethnicity/Race
Completion
A
H
W
Completed
175 61.8%
110
69.2%
218
61.9%
Failed
108 38.2%
49
30.8%
134
38.1%
Total
283 100.0% 159 100.0% 352 100.0%
2
n= 936 x = 4.625 df= 3 α= .201
O
98
69.0%
44
31.0%
142 100.0%
The third hypotheses were: Education will not affect the likelihood of completing
a CSO; and alternatively offenders with higher levels of education will be more
likely to complete a CSO than offenders with lower levels of education. Results from
Table 4, show that completion rates do increase with increases in education. Offenders
with less than HS or GED had a completion rate of 58.8%, followed by HS or GED
62.6%, and more than HS and GED 68.9%. Therefore, the direction of the hypothesis is
supported. The chi-Square value was 4.950 with two degrees of freedom and a two-tailed
probability of .084. Although the direction of the hypothesis is supported a probability of
this size is not significant and allows for 8% error. Therefore, the null hypothesis cannot
be rejected and the alternative hypothesis is rejected. Although offenders with higher
levels of education are more likely to complete a CSO than offenders with lower levels of
education, the effects are not significant.
Table 4: Effects of Education on Program Completion
Program
Completion
Education
HS or GED
Less than HS or
GED
Completed
80
58.8%
308
Failed
56
41.2%
184
Total
136
100.0% 492
2
n= 908 x = 4.950
df= 2 α= .084
62.6%
37.4%
100.0%
More than HS and
GED
193
68.9%
87
31.1%
280
100.0%
51
The fourth hypothesis was: Offenders who have higher levels of income will be
more likely to complete a CSO than offenders with lower levels of income. However,
because almost half (46%) of the data are missing any analysis of income cannot be
generalized to the population. Looking back at Table 1, it is evident that the majority of
respondents (34.5%) had an annual income between $1-20,000 with percentages
decreasing for every income bracket increase. Therefore, it is clear that income is not an
evenly distributed variable. Furthermore, the mean was $19,756.13, the median was
$14,000 and the mode was $12,000. Since these three measures differed the median of
$14,000 was used as a measure of central tendency and the mode is reported as a second
measure to display the differences. It is evident from Table 5 that the median income for
those that complete was $14,000 and the median income for those that fail was $14,400;
while the modal income for those that complete was $10,000 and the modal income for
those that fail was $12,000. From these results it appears that the opposite direction of the
hypothesis is supported; however, these findings are not significant. Given the amount of
missing data for this variable, a determination cannot be made about the hypothesis.
Table 5: Effects of Income on Program Completion
Program
Completion
COM
FAI
Median
Income
$14,000
$14,400
Modal
Income
$10,000
$12,000
The fifth hypothesis states: Older offenders will be more likely to complete a
CSO than younger offenders. The mean, median and mode for age are varied and thus the
variable does not have a normal distribution. The mean was 34.56 years, the median was
52
31 years and the mode was 20 years. For this reason the median will be used as a measure
of central tendency with the mode reported as a secondary measure to display the
differences. Table 6 shows that the median age for those that completed was 33 years and
the median age for those who failed their CSO was 30 years. The table also shows that
the modal age for offenders who completed and failed their CSO was 20 years. Since the
median age of those that completed is higher than the median age for those that failed, it
appears as though the direction of the hypothesis is supported. The modal analysis does
not support this finding. Furthermore, looking back at Table 1, it is evident that the most
common age group was offenders between the ages of 18 and 25 with 34.2% falling into
this bracket. Thus, the median may not fully represent the true relationship between age
and program completion.
Table 6: Effects of Age on Program Completion
Program
Completion
COM
FAI
Median
Age
33
30
Modal
Age
20
20
53
Chapter 5
SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
Overview of Study
Community service programs are a vastly under researched correctional option
and as such the effectiveness of these programs is unknown. Evaluation of these
programs would expand their use for a number of offenders and add legitimacy to their
continued use or even justification for their elimination. The literature has shown that
sociodemographic factors influence whether or not an offender completes his/her CSO.
Determining which factors effect program completion would increase the effectiveness of
these programs and the adjudication process by determining the most appropriate
sentence for an offender.
Using secondary data collected from the Alternative Sentencing Program in
Sacramento during the year 2008, five sociodemographic factors were identified to assess
whether or not differences affected an offender’s likelihood of completing his/her CSO.
The relationship of these five factors was analyzed individually against program
completion to determine what effect, if any, they had on the outcome.
The data provided evidence that differences in sociodemographic factors had
some effect on program completion. However, these effects were not as strong as those
found in the literature. Additionally, some of the findings were contradictory to findings
in the literature and the theory tested.
Discussion
Analysis showed that all of the independent variables had some effect on the
54
dependent variable. However, none of the relationships were found to be statistically
significant. Additionally, the hypotheses for education and age were the only two
supported by the analysis. The older the offender was the more likely s/he was to
complete his/her CSO, similarly, the more education an offender had the more likely s/he
was to complete.
Most of the findings from this study do not support those found in the literature or
the theory. There are a few possible explanations for these differences. First, ASP has a
larger more diverse population than that found in other studies such as those conducted
by Bouffard and Muftic (2006) and Muiluvuori (2001). Therefore, the size and diversity
of the population may reduce sociodemographic differences found in other studies that
used smaller more homogeneous samples. Second, findings from this study differ from
those in the theory suggesting that another theory may better explain an offender’s
willingness to complete his/her CSO than conformity/compliance theory. Another
possible explanation is that several types of conformity and compliance exist and one of
these more narrow subtypes may be more appropriate than general conformity/
compliance theory.
Implications
While significant relationships were not found in this analysis, relationships
between the independent variables and the dependent variable still exist which suggest
important implications to the practice of community service programs. Identification of
offenders who have several of the characteristics which make it less likely that s/he will
complete their CSOs (e.g., a younger, Asian, female offender with higher amounts of
55
income and lower education levels) should be made. Identification of these ‘at risk’
offenders would assist judges in making appropriate sentencing decisions and would aid
practitioners by allowing them to pay more attention to ‘at risk’ offenders.
Additionally, this research presented several implications for future and continued
research. Since data for this research were only drawn from offenders whose cases were
closed in 2008 the findings from this study can only be generalized to this population.
Therefore, future research could determine if the findings from this study persist to all
offenders sentenced to ASP. Additionally, since findings from this study varied from
those found in the literature, future research should be conducted to determine if the
effects of sociodemographic differences on program completion differ depending upon
the size and diversity of a population. Future research should also be conducted to
determine if conformity/compliance theory is appropriate to explain the relationship
between sociodemographic factors and program completion. Continuing evaluation and
research on community service programs is of vital importance to the continuation and
expansion of this intermediate sanction.
Limitations
This study faced several limitations. The first is that the population only included
offenders whose cases were closed in 2008 making generalizations to all ASP clients
impossible. Due to time constraints analysis of multiple years was not possible. This
research was also limited by missing or incorrectly entered data. Future studies should get
access to the original client registration forms to cross reference them with the database
to increase reliability. Furthermore, reliability and validity could be increased by
56
obtaining official statistics rather than self-reported data. Official statistics would
eliminate errors made by responses which were not truthful and missing data. While
findings from this research were not significant, a number of factors could be responsible
and future research would aid in determining what these factors are. Evaluating
community service programs will lead to more informed practices.
57
APPENDICES
58
APPENDIX A
List of Variables
Type of
Variable
Variable
Conceptual
Definition
Operational Definition
Age
The number of
years since a
person’s date of
birth.
Age is measured by subtracting the
client’s DOB (date of birth) from the
date ordered to determine a person’s
age in years.
Gender
A person’s
biological sex.
Independent
Variable
Ethnicity/
Race
Traits, background,
allegiance or
association with an
ethnic or racial
group.
Independent
Variable
Education
Level
The highest grade
level completed in
school.
Independent
Variable
Independent
Variable
Independent
Variable
Dependent
Variable
Income
Program
Completion
The amount of
money an
individual makes
in exchange for
labor, services or
other financial
transactions.
An offender who
completes the
required number of
community service
hours and all of the
programs
requirements.
Gender is measured by an offender’s
self identification as either male or
female. The data are coded as either an
M for male or an F for female.
Ethnicity/race is measured by selfreport of “Ethnic background” in
which the offender circles: African
American, Asian, Caucasian, Hispanic,
Native American, Pacific
Islander/Polynesian or Other. The data
are coded as A, S, W, H, N, P, and O
respectively.
Education is measured by the question
“level of school completed” and in the
database as last grade completed. The
responses range from 1-20. Numbers
1-11 are coded as less than HS no
GED, 12 as HS or GED, 13-20 as more
than HS and GED.
Income is measured by the following
question: “Approximate yearly
income.” The responses are open
ended.
Program completion is measured in the
database under disposition. Failure is
coded as BTC, RTP, RTC, FTP
(depending on where the cases are
being referred back to for further
disposition) while completions are
coded as COMP.
59
APPENDIX B
Client Registration Form
Date: _____________________
Last Name: _______________First Name: __________________ (Male/Female)
DOB
Age:
SS#
DL#
Street:
City:
State:
Home#
Cell#
Work#
Email:
Emergency Contact:
Phone:
Do you have any other names you may go by?
If so please list:
Yes
or
Zip:
No
Last Name: ______________________ First Name: ________________________
Have you ever been in our program before? Yes or No
Are you currently employed? Yes or No Are you enrolled in school? Yes or No
Do you have transportation? Yes or No Do you use the light rail or bus? Yes or No
Circle the days and write the hours that will best fit your schedule to complete your hours.
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday
-
-
-
-
-
-
-
Are you under the care of a doctor?
Yes or No
If you are requesting ASP to accommodate your physical needs, we may need medical
documentation.
Do you have any other past or current criminal convictions?
Yes or No
If so please list:
____________________________________________________________________
Are you on probation for this case
Yes or No
Probation officers Name: ____________________ Phone: ___________________
Are you now or ever been convicted or required to register as a PC 290 (sex offender)? Yes or No
Have you ever been convicted of PC 451 (arson)?
Yes or No
Statistical Purposes
Primary Language: ___________________ Level of school completed: ________
60
Ethnic background:
African America
Asian Caucasian
Pacific Islander/Polynesian
Hispanic/Latin
Other: ________________________
What is your approximate yearly income? ___________________
Native American
61
APPENDIX C
SUPERIOR COURT OF CALIFORNIA, COUNTY OF SACRAMENTO
ORDER TO REPORT TO THE ALTERNATIVE SENTENCING PROGRAM
CASE NO.
SECTION(S) VIOLATED
FELONY
MISDEMEANOR
DATE ORDERED
/
/
NAME (LAST, FIRST, M.I.)
ADDRESS (CITY, STATE, ZIP)
TELEPHONE NUMBER
(
)
DATE OF BIRTH
/
/
NUMBER OF
HOURS
JUDICIAL OFFICER
DEPARTMENT
X-REF #
FORMAL PROBATION
INFORMAL PROBATION
NO PROBATION
REQUIRED COMPLETION DATE
/
/
PROBATION OFFICER
PROP 36 CASE
RE-REFERRAL
You are ordered to report in person to the Alternative Sentencing Program for an interview within 10 CALENDAR
DAYS. APPOINTMENTS ARE NOT GIVEN. YOU MUST REPORT TO:
1111 HOWE AVE. SUITE #600 SACRAMENTO, CA 95825 916.567.3114
Office Hours: Monday, Wednesday, Thursday, and Friday - 8:00 a.m. to 5:00 p.m.
Tuesday – 10:00 a.m. to 5:00 p.m.
A $30 APPLICATION FEE PLUS THE FOLLOWING PROGRAM FEE WILL BE APPLIED
1-10 hours = $10
11-20 hours = $20
21-30 hours = $30
31-40 hours = $40
41-60 hours = $60
61-80 hours = $80
81-100 hours = $100
101-120 hours = $120
121-140 hours = $140
141-160 hours = $160
161-180 hours = $180
181-200 hours = $200
201-220 hours = $220
221-240 hours = $240
241-260 hours = $260
261-280 hours = $280
281-300 hours - $300
300-350 hours = $325
351-400 hours = $350
401-450 hours = $375
451-500 hours = $400
501-600 hours = $425
601-700 hours = $450
701-800 hours = $500
801-900 hours = $550
901-1000 hours =$600 Over 1000 hours $650
You must be prepared to pay at least the first $50 of all fees at the time of interview, or you will not be allowed to
sign up for the program. If you are unable to pay all of your fees at the time of interview, you must report to the
Alternative Sentencing Program with a minimum beginning payment of $50. You will be placed on a payment plan
and will be required to make monthly payments of $50 until the balance is paid. A one time $30 billing fee will be
added.
To be eligible to have your program fees reduced, you must meet the following criteria: 1) Have 41 or more hours
of community service to perform; 2) Provide proof at the time of interview that your total household income is less
than $850 per month. Proof must be in the form of AFDC, G.A., S.S.I., E.D.D., or similar statement. Once the
program manager has authorized a fee reduction, you will be required to pay a total of one-half of the original
program fee or $40 whichever is greater plus the $30 application fee.
AGREEMENT
As a condition of being admitted to the Alternative Sentencing Program, I/minor consent(s) to perform assigned
services strictly in the capacity of a volunteer and not as an employee of said agency, or of any other person, firm or
corporation. I/parent or guardian waive any and all claims for accident or injury or compensation of any nature
arising out of said services against the Superior Court of California, County of Sacramento, the Volunteer Center of
Sacramento and the Alternative Sentencing Program, its officers, agents and employees. Furthermore, I/parent or
guardian consent(s) to release to work placement supervisors pertinent information about any physical, mental or
emotional limitations I may have and the nature of sustained offenses. I understand and agree to the above
conditions.
___________________
DATE
________________________________________
SIGNATURE
62
APPENDIX D
Measurement Issues
The variable ethnicity/race included some invalid codes in the original data set. It
is impossible to obtain the correct information without the client’s agreement form which
the researcher does not have access to, for this reason incorrect data are counted as
missing data. In the income variable, two cases were mistakenly entered as multimillionaires. Since it is unlikely that any multi-millionaires participated in the program it
is much more likely that the caseworker mistakenly entered too many numbers under
income. Therefore, these two cases were included as missing data for this variable.
A few cases had incorrect dates which would affect the calculation of the
offender’s date of birth. Two cases were incorrectly entered with date(s) ordered as 2009
which is not possible because all of the cases were closed in 2008. Therefore, the year on
the date(s) ordered was changed to 2008. One case was incorrectly entered with a date
ordered as December of 2008 which is not possible because the actual and required
completion date was January 2008. Therefore, the date ordered was incorrectly entered so
the year was changed to 2007. Two cases had an incorrect required completion date. The
date had been entered as 2007, however, the date ordered and the actual completion date
was in 2008 making it impossible for the required completion date to be in 2007. In these
two cases the year was changed to 2008.
As a former employee of the Alternative Sentencing Program, the researcher was
able to correct some of these data entry errors in the original data set. The researcher used
intimate knowledge of the process and the way in which data are entered into the system
63
to make logical corrections. These cases were corrected in order to increase the reliability
of the data and to reduce entry errors.
64
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