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WEEK 5 DISCUSSIONPROMPT A:In Fass, Heilbrun, DeMatteo, and Fretz’s article they investigated the predictive abilities of the LSI-R, the COMPAS, and selected criminogenic variable for rearrest within 1 year of community release. What did the result indicate? The results found further support for what previous empirical data to predict rearrest. What is that data and why do you think it is relevant to this week’s material?PROMPT B:In the article Can 14,737 Women Be Wrong? The authors provide some policy recommendation. What assessment instrument do they rely on for their recommendations? Why? Do you agree or disagree with their selection? Defend your position.


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Seq: 1
Can 14,737 women be wrong? A meta-analysis of
the LSI-R and recidivism for female offenders*
Paula Smith
Francis T. Cullen
Edward J. Latessa
University of Cincinnati
Research Summary
Over the past two decades, researchers have been increasingly interested in measuring the risk of offender recidivism as a means of
advancing public safety and of directing treatment interventions. In this
context, one instrument widely used in assessing offenders is the Level
of Service Inventory-Revised (LSI-R). Recently, however, the LSI-R
has been criticized for being a male-specific assessment instrument that
is a weak predictor of criminal behavior in females. Through the use of
meta-analytic techniques, we assessed this assertion. A total of 27 effect
sizes yielded an average r value of .35 ([confidence interval] CI = .34 to
.36) for the relationship of the LSI-R with recidivism for female
offenders (N = 14,737). When available, we also made within-sample
comparisons based on gender. These comparisons produced effect sizes
for males and females that were statistically similar.
Policy Implications
These results are consistent with those generated in previous research
on the LSI-R. They call into question prevailing critiques that the LSIR has predictive validity for male but not for female offenders. At this
stage, it seems that corrections officials should be advised that the LSIR remains an important instrument for assessing all offenders as a prelude to the delivery of treatment services, especially those based on the
principles of effective intervention. Critics should be encouraged, however, to construct and validate through research additional genderspecific instruments that revise, if not rival, the LSI-R.
* Direct correspondence to Paula Smith, 600G Dyer Hall, 2600 Clifton Ave.,
University of Cincinnati, Cincinnati, OH 45221 (e-mail: paula.smith@uc.edu).
CRIMINOLOGY & Public Policy
Volume 8 Issue 1 Copyright 2009 American Society of Criminology
Seq: 2
Smith et al.
Keywords: offender assessment, Level of Service Inventory, rehabilitation, correctional policy
The dominant reality of U.S. corrections is the inordinate expansion of
the correctional system. Since the early 1970s, prison and jail populations
have increased from approximately 200,000 to more than 2.3 million
(Sabol, Couture, and Harrison, 2007; Warren, 2008). On any given day,
one in a hundred Americans is behind bars (Warren, 2008). Equally troubling, when probation and parole are considered, the number of individuals
under state supervision exceeds 7 million (Glaze and Bonczar, 2006). As
might be anticipated, a steady stream of books have been written documenting and seeking to understand this era of mass incarceration and
community control (see Abramsky, 2007; Gottschalk, 2006; Lynch, 2007;
Simon, 2007; Tonry, 2004). Regardless, DiIulio (1991) was prescient when
he warned nearly two decades ago that there would be “no escape” from
these correctional realities.
As Feeley and Simon (1992) point out, the growth of the correctional
enterprise has created an organizational crisis as to how to house, feed,
supervise, and ultimately release the large and unending stream of humanity that flows through the system (see also Simon, 1993). At its worst, this
situation has led to a “new penology” in which a disturbing goal of displacement transpires—where the larger social purposes of corrections,
such as rehabilitation, are replaced by the daily, pragmatic need to monitor and process correctional populations. In the best case scenario, a
premium is placed on those correctional administrators who can confront
challenging organizational conditions—the most obvious of which is
intense overcrowding or large case loads—and in turn foster a safe environment and the delivery of human services (see DiIulio, 1987).
Although not new—they extend back to the work of Ernest Burgess in
1928 and to Sheldon and Eleanor Glueck in 1950 (Bonta, 1996; Jones,
1996)—offender assessment instruments are key tools in managing correctional populations. These instruments are employed primarily to measure
the “risk” that an offender will recidivate if released into the community.
These assessments coincide with new penology and managerial thinking in
that they can be used to routinize and rationalize decision making that
otherwise would be discretionary (e.g., who to release on parole and who
to give probation). In this way, the correctional system gains in efficiency,
and the community presumably gains in public safety. At the very least, it
seems that criminal justice officials are taking credible steps to use science
to manage risk, which includes dangerous offenders (Simon, 1993).
Gender and Risk Assessment
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These instruments compile information about each offender, which in
turn is used to predict the risk of recidivism. For the most part, the risk
factors measured have been historical and “static” in nature (for a review,
see Andrews and Bonta, 2006). That is, the instruments have focused on
what has already occurred in an offender’s life (historical) and on what
cannot be changed (static). For example, a person’s criminal history is an
important predictor of future waywardness; still, an intervention cannot
change a criminal record because it is, by its nature, in the past and thus
unchangeable. This approach is not necessarily a problem if one wishes
only to assess the risk of recidivism and to manage inmates or control
offenders under community supervision. But as Bonta (1996:22) points
out, instruments composed primarily of static factors provide “little direction for rehabilitation. . . . Rehabilitation is based on the premise that
people can change, and if assessment is to contribute to rehabilitation
efforts, it must be capable of measuring change.”
In this context, an alternative approach to offender assessment has been
developed by Canadian psychologists Don Andrews, James Bonta, Paul
Gendreau, and others (Andrews and Bonta, 2006; Bonta, 1996; Gendreau,
1996); together, they are recognized as comprising the Canadians’ school
of correctional intervention (Cullen, 2002). Their ideas were developed
within a correctional and national culture that was social-welfare oriented,
and they were informed by professional ethics from their home discipline
of psychology. Perhaps not surprisingly, their goal was to improve the lives
of offenders; accordingly, they rejected the managerial, new-penology
view of risk assessment prevailing in the United States during the “get
tough” era of the 1980s and beyond (Simon, 1993). The Canadians’
approach has three major features, which are outlined next.
First, building on the existing empirical evidence (see, e.g., Gendreau,
Little, and Goggin, 1996), the approach argues that recidivism is predicted
most accurately by including both static risk factors (e.g., criminal history)
and dynamic risk factors. Dynamic risk factors, which are also called
“criminogenic needs,” are those predictors of recidivism that are potentially mutable. They would include, for example, antisocial attitudes,
family functioning, and association with criminal peers.1
1. According to Andrews and Bonta (2006), the major risk factors include the
following: (1) antisocial/procriminal attitudes, values, and beliefs; (2) antisocial/
procriminal peers; (3) temperament and personality factors such as being aggressive,
impulsive, adventurous, and pleasure seeking; (4) a history of antisocial behaviors; (5)
family factors such as family criminality, lack of caring and cohesiveness, as well as
neglect and abuse; (6) low levels of educational, vocational, or financial achievement;
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Smith et al.
Second, rejecting new-penology thinking, the purpose of offender
assessment should be not only risk management but also offender treatment. The inclusion of dynamic factors is critical because it is these
“criminogenic needs” that rehabilitation programs will target for change.
That is, by focusing on and changing these factors (e.g., reducing antisocial
thinking), offenders’ recidivism will be reduced. This strategy is referred to
as the “need principle.” Another principle of effective intervention set
forth by Andrews and his colleagues is the “risk principle,” which states
that treatment should be devoted primarily to high-risk offenders. The
“responsivity principle” asserts that treatment modalities should be used
that can alter the criminogenic needs that underlie recidivism. Cognitivebehavioral programs are viewed as being particularly appropriate for this
task (Andrews and Bonta, 2006; Gendreau, Smith, and French, 2006; Lipsey, Chapman, and Landenberger, 2001; see also MacKenzie, 2006).
Third, and of particular concern here, the Canadian scholars have developed an assessment instrument that predicts recidivism and can be used as
the basis for effective intervention. This instrument is called the Level of
Service Inventory or, the LSI as it is now commonly known; its revised
version is termed the LSI-R (Andrews and Bonta, 2006; Bonta, 1996). The
LSI-R consists of 54 items, most of which measure dynamic risk factors
that are known as having criminogenic needs. Existing studies show that
the LSI-R has predictive validity with regard to recidivism (Gendreau,
Goggin, and Smith, 2002; Gendreau et al., 1996; Vose, Cullen, and Smith,
2008). Based on the extant research, Andrews and Bonta (2006:289) conclude that “all of the comparisons showed the LSI-R to predict as well or
better than the other [assessment] instruments.”
According to the Canadian scholars, the LSI-R is central to the delivery
of effective offender treatment, whether in prison or in the community.
Currently, correctional agencies often place offenders in rehabilitation
programs either collectively (i.e., everyone receives the same program) or
based on inaccurate clinical judgments about what might benefit an
offender. By contrast, a core principle of effective intervention is that
“responsive” interventions should be directed at high-risk offenders. This
is the case for two reasons. First, low-risk offenders—those who would “go
straight” on their own—either do not benefit from, or are made more
criminogenic by, interventions. Second, high-risk offenders not only pose
(7) a lack of prosocial leisure activities; and (8) abuse of drugs and alcohol. Although
these risk factors are all viewed as important, it is necessary to note that the first four
items are referred to as the “Big Four” and are considered to be the most robust among
the set (Andrews, Bonta, and Wormith, 2006).
Gender and Risk Assessment
Seq: 5
the greatest threat to the community but also can potentially experience
substantial reductions in recidivism. Again, this means that a valid assessment of risk level is essential to an effective correctional intervention
(Andrews and Bonta, 2006).
In this context, and given its empirical status, the LSI-R has emerged as
perhaps the leading offender assessment instrument in corrections. Again,
it gains added credibility because it is rooted in the empirical literature on
predictors of recidivism and is integrated with a prominent paradigm of
correctional treatment—which are the key principles of effective intervention (Cullen, 2002; see also Cullen and Gendreau, 2000; Gendreau et al.,
2006; Ogloff and Davis, 2004). Across North America, the LSI-R is in use
in more than 900 correctional agencies (Lowenkamp, Lovins, and Latessa,
2009; see also Listwan, Johnson, Cullen, and Latessa, 2008).
It is within this context that a recent, salient critique of the instrument
takes on special importance: It is claimed that the LSI-R has predictive
validity for males but not for females (Holtfreter and Cupp, 2007; Reisig,
Holtfreter, and Morash, 2006). For Andrews, Bonta, and colleagues, the
LSI-R is based on the general principles of social learning theory and cognitive psychology. In turn, they believe that the predictors of crime and
recidivism are substantially the same for male and females; that is, the
proximate causes of criminality are “general” rather than “gender specific” (for supportive meta-analytic evidence, see Dowden and Andrews,
1999; Gendreau et al., 1996; Hubbard and Pratt, 2002; Moffitt, Caspi, Rutter, and Silva, 2001; Simourd and Andrews, 1994). In this view, gender is
important but to the extent that it shapes how and to what extent males
and females are exposed to and/or acquire common risk factors (e.g., antisocial peers).
These observations have three important implications. First, treatment
programs should have similar effects for males and females. Inappropriate
programs (e.g., boot camps) will not be effective for either gender; by contrast, programs that adhere to the principles of effective intervention will
work equally well for males and females. Evidence exists to support this
claim (Andrews and Bonta, 2006). Second, gender may be important in
the way in which treatments are delivered; this approach is termed “specific responsivity” (Andrews and Bonta, 2006). Thus, although cognitivebehavioral programs may be effective across genders, women may respond
better if the treatment is delivered in a female-only group and where an
emphasis is placed on creating “a community with a sense of connection”
(Andrews and Bonta, 2006:465). And third, the LSI-R should predict
recidivism and be used as an instrument assessing offender change equally
well for males and females. Notably, Andrews and Bonta (2006:301–302)
recently presented data that show similar predictive validity across gender
Seq: 6
Smith et al.
for a recent version of the LSI-R on a sample of 561 Ontario probationers
followed for 3 years after release from supervision. Vose (2008) reports
similar results regarding the predictive validity of the LSI-R across gender
for probationers and parolees in Iowa.
The current critique of the LSI-R as being a male-specific assessment
instrument is embedded within the larger criminological debate over
whether the causes of crime are general (as most prevailing theories of
crime claim) or are gender specific (as feminist scholars argue) (see Daigle, Cullen, and Wright, 2007; Miller and Mullins, 2006; Salisbury, 2007).
Again, empirical research has shown, now for some time, a similarity in
the causes of crime across gender (Simons, Miller, and Ainger, 1980; Smith
and Paternoster, 1987). For example, based on their study in Dunedin,
New Zealand, Moffitt et al. (2001:230) conclude that “the same risk factors
predict antisocial behavior in both males and females; we did not detect
any replicable sex-specific risk factors for antisocial behavior” (see also
Farrington and Painter, 2004). Gender-specific theorists disagree, arguing
that these more traditional approaches omit experiences—and thus risk
factors—unique to women. Thus, they point to distinct differences by gender in socialization, development, and economic marginalization as the
primary explanations for the gender differences in risk factors (ChesneyLind, 1989; Daly, 1992, 1994; Reisig, Holtfreter, and Morash, 2002). For
example, Covington and Bloom (1999:3) maintain that “the philosophy of
criminogenic risk and needs does not consider factors such as economic
marginalization, the role of patriarchy, sexual victimization, or women’s
place in society.” These unique life-course trajectories that lead to criminal
offending are referred to as “gendered pathways” (Daly, 1992, 1994; for a
summary, see Miller and Mullins, 2006:228–232).
The construct of gendered pathways holds important implications for
offender assessment and, ultimately, for treatment. If females predominantly enter crime for gender-specific reasons, then the LSI-R, which
assumes the generality of crime causation, would not be of much value in
predicting females’ recidivism or in directing treatment interventions with
women offenders. This possibility was poignantly suggested by the
research of Reisig et al. (2006). Based on a sample of 235 female offenders
under community supervision in Minnesota and Oregon, the authors
examined the LSI-R’s ability to predict recidivism across those who
entered crimes for gender-neutral reasons (economic motivation) or
gender-specific reasons (street women, harmed and harming women
whose lives were filled with chaos and abuse/neglect, battered women, and
drug-connected women). Their analysis revealed that although the LSI-R
predicted recidivism for the economically motivated offenders, it misclassified and had low predictive validity for offenders who entered crime
through gendered pathways. The economically motivated group, however,
Gender and Risk Assessment
Seq: 7
comprised only a quarter of the sample. The policy implications of this
finding are clear. A “cause for concern” (Reisig et al., 2006:400) was
found. The LSI-R risks endangering public safety and misallocating treatment resources by underclassifying some offenders (especially drugconnected females) and by overclassifying others. In short, the LSI-R may
be appropriate to assess male offenders but not female offenders.
Our project attempts to use a meta-analysis of extant studies to bring
additional evidence to bear on the ability of the LSI-R to predict recidivism for female offenders. This approach does not present a direct test of
the gendered pathways model, because, with the exception of Reisig et al.
(2006), current research does not divide offenders into pathway groups.
Even so, critics of the LSI-R claim that because of its gender-specific
nature, the ability of the LSI-R to predict recidivism for females should be
low and, in addition, should be far lower than for males (Holtfreter and
Cupp, 2007). Phrased alternatively, similar effects between the LSI-R and
recidivism across gender groups would increase confidence that the instrument can be used to assess not only males but also females.
To assess these issues, we undertook a meta-analysis that involved 25
studies and 27 effect sizes representing data on 14,737 female offenders. In
16 studies, we calculated the effect sizes for both males and females. These
data allowed us to conduct within-sample comparisons.
A meta-analysis involves the quantitative synthesis of research literatures, and it is now considered to be the review method of choice in
several disciplines (Hunt, 1997), which include criminal justice. Furthermore, this statistical technique has been applied in several previous studies
to evaluate the predictive validity of offender assessments (e.g., Campbell,
French, and Gendreau, 2007; Gendreau et al., 2002). A meta-analysis
expresses the outcome of interest (e.g., offender recidivism) from studies
in a common metric, which is referred to as an effect size, and calculates
an average. Variations in the magnitude of effect sizes can then be
examined in relation to potential moderators. Many advantages are associated with this statistical technique. First, it standardizes the review process
and generates a quantitative estimate of the magnitude of an effect. Second, it can highlight discrepancies and/or systematic shortcomings in a
research literature. Third, it provides an estimate of the certainty of an
effect through the use of fail-safe statistics. As a literature review technique, however, meta-analysis is not foolproof. Researcher biases can
affect retrieval and cod …
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