Measuring Public Support for Prisoner Reentry Options.

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research-article2015

IJOXXX10.1177/0306624X15578438International Journal of Offender Therapy and Comparative CriminologyGarland et al.

Article

Measuring Public Support for Prisoner Reentry Options

International Journal of Offender Therapy and Comparative Criminology 1–19 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0306624X15578438 ijo.sagepub.com

Brett Garland1, Eric Wodahl2, and Lisa Cota1 Abstract Few topics have been discussed more extensively or feverishly within correctional academic and professional circles in the past few decades than prisoner reentry. Although program and policy evaluations have been conducted, a lack of public support for prisoner reentry initiatives could undermine the sustainability of prisoner reentry as a large-scale movement. Interestingly, no multivariate, explanatory analyses of the correlates of support for prisoner reentry policies could be found in the literature. This omission is due in part to the absence of clear psychometric measures to assess support. The current study examines the data obtained from a sample of residents in a Midwestern state to determine the dimensionality of support for prisoner reentry interventions using both exploratory factor analysis (EFA) and ordinary least squares (OLS) regression. Specifically, our expectation is that the following three-factor structure will be identified: (a) support for transitional programs aimed at building skills and knowledge to handle the obstacles of the prison-to-community transitional process, (b) support for post-release transitional housing units, and (c) opposition to denying offenders housing opportunities. Our results support a three-factor model. The implications of these findings for future research are discussed. Keywords prisoner reentry, public opinion, corrections, measurement models

Introduction Prisoner reentry has emerged as one of the most discussed topics in correctional discourse over the past two decades. The heightened attention given to criminal offenders 1Missouri

StateUniversity, Springfield, USA of Wyoming, Laramie, USA

2University

Corresponding Author: Brett Garland, Department of Criminology and Criminal Justice, MissouriStateUniversity, 901 S. National Avenue, Springfield, MO65804, USA. Email: [email protected]

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as they exit prison is fueled in large part by a massive increase in the number of prisoner releases. Approximately 709,000 prisoners were released from state and federal correctional facilities in 2010, a statistics that more than quadrupled from 1980 when 170,000 prisoners were released that year (Guerino, Harrison, & Sabol, 2011; Lynch & Sabol, 2001). The growing number of prisoner releases has serious implications. Sixty-eight percent of ex-prisoners are rearrested within 3 years of release, and of these recidivists, almost half are arrested after only 6 months (Langan & Levin, 2002). Studies on prisoner reentry have identified various post-release obstacles related to housing, employment, drug addiction, health care, transportation, psycho-social adjustment, and reintegration into families and local community networks which place ex-prisoners in jeopardy immediately after release (Clear, Rose, & Ryder, 2001; B. Garland, Wodahl, & Hershberger, 2011; La Vigne, Visher, & Castro, 2004; O’Brien, 2001; Richie, 2001; A. L. Solomon, Gouvis, & Waul, 2001; Urban Institute, 2006; Visher, Kachnowski, La Vigne, & Travis, 2004; Wodahl, 2006). In addition, some scholars believe that offenders are having more difficulty adjusting to life after prison in recent years considering that they spend more time incarcerated per prison commitment, experience fewer institutional treatment opportunities, and receive less formal community supervision due to higher caseloads (Petersilia, 2001; Travis, Solomon, & Waul, 2001). A wide range of initiatives have been launched to address the modern prisoner reentry phenomenon. Funded in part by federal legislation and government grants, prisoner reentry initiatives have taken a variety of forms, including job training and placement programs, transitional houses, therapeutic communities for drug offenders, reentry courts, faith-based restorative justice programs, and an array of collaborative efforts under broader partnership models (Maruna & Lebel, 2002; Seiter & Kadela, 2003; Taxman, Young, Byrne, Holsinger, & Anspach, 2002; Willison, Brazzell, & Kim, 2011). In 2010 alone, US$114 million was allocated as part of the Second Chance Act to prisoner reentry initiatives such as mentoring programs, reentry courts, and reentry-related substance abuse and criminal justice collaborations. One reality emanating from the diverse, fragmented approach to addressing the prisoner reentry problem is a lack of convincing empirical justification for prisoner reentry policies and practices. Although promising approaches exist for easing the prison-to-community transition (Bouffard & Bergeron, 2006; Duwe, 2012), the extent to which reentry interventions can collectively increase likelihoods of successful post-release adjustment is largely undetermined (Lattimore, Steffey, & Visher, 2010; Walker, 2011; Wilson & Davis, 2006).

Public Support and Prisoner Reentry Public support is important to consider when assessing the sustainability of prisoner reentry initiatives. Although prisoner reentry programs have received political backing for the past several years, political support may diminish if the public begins to feel that efforts to assist ex-prisoners with their return lack legitimacy and effectiveness (Ogle, 1998). Studies have identified that politicians and other policymakers integrate


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public opinion into decisions regarding the distribution of public funds (Burstein, 2003; Nicholson-Crotty, Peterson, & Ramirez, 2009; Wlezien, 2004). More specifically, the termination of correctional initiatives such as reformatories in the 1800s; the industrial, for-profit prison in the early 20th century; and Pell Grants for prisoners in the 1990s were affected by shifts in public attitudes (D. Garland, 2002; Seiter, 2010). The sustainability of prisoner reentry policies and practices may be particularly linked to public support as many reentry programs are embedded in communities where collaborative responses among formal organizations and community groups are viewed as critical (Byrne, Taxman, & Young, 2002; Travis et al., 2001). A few studies have examined the public’s general attitudes toward helping prisoners as they return to society. Krisberg and Marchionna’s (2006) analysis of a national Zogby Poll found that 7 out of 10 Americans favor the delivery of reentry services in institutional and community settings. More than half of respondents thought job training, drug treatment, mental health services, family support, mentoring, and housing were all “very important” for ex-prisoners to be successful. In addition, the Second Chance Act was supported by nearly 8 out of 10 respondents. A study on public opinion and prisoner reentry in Missouri similarly found support for fundamental components of reentry (B. Garland, Wodahl, & Schuhmann, 2013). For example, 89% of Missouri residents believe it is a good idea to help people coming out of prison get services, 76% felt that employment-based reentry programs should strive to get prisoners earning enough money to make a stable living, and roughly 9 out of 10 Missourians favor substance abuse and mental health programs for recently released prisoners. Although the public clearly supports the general concept of prisoner reentry, support fades when other factors are considered. Immerwahr and Johnson (2002), for example, found that Philadelphia residents were much more in favor of financially supporting reentry initiatives than prison costs. However, very little financial aid was advocated for prisoner reentry interventions when funding child care for low-income families was a competing option. B. Garland et al. (2013) noted that support for reentry-related substance abuse, mental health, and general health care services dropped by half when the prospect of paying higher taxes for funding costs was considered. In addition to the few studies examining public attitudes toward helping ex-prisoners transition to society, a substantial amount of research has explored public support toward the punishment and treatment of offenders more generally. Although exhaustively reviewing this research is beyond the scope of this article (for more thorough reviews, see Cullen, Fisher, & Applegate, 2000; Maruna & King, 2004; Reynolds, Craig, & Boer, 2009), certain themes emanate from this literature relevant to our inquiry and are thus important to highlight. First, public support for rehabilitative responses to law violators has remained strong even during the peak of the tough on crime movement (Cullen et al., 2000; Flanagan, 1996; Gerber & Engelhardt-Greer, 1996). Cullen and Moon (2002) attributed this support to the public realization that most offenders will return to the community and that “rehabilitation is one of the few tools at the state’s disposal to make these offenders less dangerous” (p. 17). A second consistent theme from the public opinion literature is the existence of punitive attitudes (Cullen et al., 2000; Flanagan, 1996). Strong public support for


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incarceration and other enhanced criminal punishments such as the death penalty and three strike laws suggests that the public holds retributive attitudes (Cullen et al., 2000; Flanagan, 1996; Maruna & King, 2004), which appear to coexist with rehabilitative sentiments (Doble, 2002). Further evidence of punitive attitudes can be found in public support for prison austerity measures. Lenz (2002), for example, found little public support for supplying prison inmates with luxuries such as cable television or special meals, especially when these amenities were paid for with tax dollars. Applegate (2001) attributed similar findings to the principle of least eligibility, which asserts that “prison inmates are the least eligible or least deserving members of society for any free benefit from the government” (p. 256). These punitive sentiments do not fade completely after the offender is released from prison as is evidenced by public support for felony disenfranchisement laws (Dawson-Edwards, 2008; Heumann, Pinaire, & Clark, 2005). While punitive attitudes exist, they are not uniform. Retributive attitudes are shaped largely by the nature of the offense and the background of the offender (Cullen et al., 2000; Flanagan, 1996; Reynolds et al., 2009). The public, for example, is largely supportive of punitive punishments aimed at certain types of offenders, such as violent, sexual, and repeat offenders, but more tolerant of rehabilitative sentencing alternatives for non-violent and first-time offenders (Cullen et al., 2000; Reynolds et al., 2009). A final theme emanating from the public opinion literature is that attitudes toward offenders and punishment often vary by respondents’ individual characteristics. Demographic characteristics, such as gender, age, educational attainment, and race or ethnicity, are often correlated with views on punishment (Applegate, Cullen, & Fisher, 2002; Maruna & King, 2009; McCorkle, 1993; Payne, Gainey, Triplett, & Danner, 2004; Spiranovic, Roberts, & Indermaur, 2012). Level of familiarity has also been found to moderate views on offenders and punishment. A recent study by Hirschfield and Piquero (2010) found that people having greater familiarity with ex-offenders held less stigmatizing attitudes toward this population. This is consistent with the literature on stigmatization of persons with mental illness, which has found that those who have greater familiarity with mental illness view this population as being less dangerous (Angermeyer, Matschinger, & Corrigan, 2004; Corrigan, Green, Lundin, Kubiak, & Penn, 2001). Political ideology is another individual characteristic that has influenced public opinion. More specifically, the literature indicates that politically liberal individuals are more likely to support rehabilitative and oppose punitive correctional initiatives (Applegate, Davis, & Cullen, 2009; Flanagan, 1996; B. Garland, Melton, & Hass, 2012). Another branch of literature relevant to our inquiry into the dimensions of public support for prisoner reentry programs comes from research on the NIMBY (Not in My Backyard) phenomenon. The NIMBY literature seeks to understand public opposition to a variety of undesirable or unpopular land uses ranging from toxic waste disposal sites to residential facilities for the mentally ill. Overall, this research reveals limited public support for residential facilities catering to marginalized groups, especially those focusing on criminal offenders (Dear, Wilton, Gaber, & Takahashi, 1997; P. Solomon, 1983). NIMBY research suggests that opposition to these facilities is not


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tied to retributive values; rather, opposition is more directly attributable to the perceived consequences generated by these facilities such as declining property values and threats to the safety and security of the individual and his or her close acquaintances (Dear, 1992; National Law Center on Homelessness and Poverty, 1997). Despite the sizeable literature on perceptions of correctional rehabilitation and punishment, little attention has been directed at why people favor or oppose current reentry policies and practices. B. Garland et al. (2013) inferred that different types of values such as self-interest, social welfare, and retribution affected variation in responses to specific questions in their Missouri study, although these values were not directly measured. More sophisticated techniques for determining how public opinion toward correctional policy is shaped require multivariate analyses with measures for public attitudes toward a policy and potential predictor variables. Complex and multifaceted concepts such as support for reentry initiatives typically require the development of multi-item indices for adequate measurement. Single-item measures are often unreliable by failing to sufficiently tap all aspects of a dimension (DeVellis, 2012; Warner, 2013). At this point, empirically justifiable composite measures of attitudes toward prisoner reentry initiatives do not exist, which impedes progress toward accurately analyzing causal relationships. Hirschfield and Piquero (2010) devised a composite measure to gauge attitudes toward ex-prisoners, but not reentry initiatives. Their scale contained items such as perceptions of whether a person feels ex-prisoners are dangerous and dishonest and the likelihood of associating with these people. Leverentz (2011) purported to measure attitudes toward reentry through multi-item scales, although the only two dependent variable scales included in her research analyzed feelings about correctional punitiveness and offender redeemability—both of which may overlap with, but are much broader than, prisoner reentry. The absence of empirically justified measures of support for reentry initiatives makes it premature to examine correlates of support with multivariate analyses. The current study explores whether dimensions of public attitudes toward prisoner reentry options exist. Using data from a broader public opinion survey in a Midwestern state, we propose three broad dimensions related to support for or opposition to prisoner reentry: (a) support for programs designed to help offenders develop their skills and knowledge to successfully navigate through the prison-to-community transition, (b) support for transitional housing for offenders immediately after release and during a post-release adjustment phase, and (c) opposition to denying recently released prisoners access to opportunities due to ex-prisoner status. We maintain that these different dimensions exist because prisoner reentry is broad and multifaceted, and different goals and implications are attached to varying aspects of reentry initiatives. Furthermore, existing research on public support for reentry programs as well as the literature on public attitudes toward offenders and punishment in general support the existence of these varying dimensions. Reentry programming seeks to prepare a person for success in their post-prison experiences and implies offenders can change and lead productive lives, making perceptions regarding their redeemability relevant to supportive or oppositional attitudes. Transitional housing


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aims to offer a secure place for offenders to regain their footing and rebuild credibility, although it also presents unique concerns by concentrating former criminals in one location, which can generate fears about public safety and potentially plummeting property values. Policies which deny opportunities such as government-subsidized housing to specific types of offenders likely tap into respondents’ retributive attitudes and generate questions of fairness and whether government intervention is infringing upon individual rights.

Method The data for this study come from a randomly selected sample of 1,000 residents from a Midwestern state. This randomized list was generated by Survey Sampling, incorporated in 2008. In May 2008, questionnaire packets were sent by mail to the addresses of each sample member. A cover letter explaining the purpose of the study and the confidentiality of responses was contained in the packet, along with the questionnaire and a prepaid return envelope. Reminder letters were then mailed to all participants 1 week later. At 5 weeks and 9 weeks after the first mailing of the questionnaire packet, questionnaires were again sent to non-respondents. Of the 1,000 individuals originally sampled, a minimum of 85 persons were unable to respond due to factors such as wrong mailing addresses, medical ailments, and death. A total of 386 surveys were received, which represents a response rate of 42% ([386 / 915] × 100) when considering the number of people able to participate. Survey respondents were 59% male, 92% White, and 36% had received a 4-year college degree or higher. The average age was 55. Statistics from the U.S. Census Bureau (2010) indicated that 49% of this Midwestern state’s residents are male, 85% White, and 24% hold at least a 4-year degree; the average age is 46. These figures indicate that the final sample studied overrepresented male, White, more educated, and older residents, which is not uncommon with mail surveys (Maxfield & Babbie, 2009). Released prisoners in this Midwestern state are 33.5% Black, 61.7% White, 1.5% Hispanic, and 0.6% Other races or ethnicities. Approximately one out of five (20.8%) recently released prisoners are violent offenders, 4.8% are sex offenders, 31.3% are drug-related offenders, 4.3% are driving while intoxicated (DWI) offenders, and 38.7% are property and other non-violent criminals. The survey contained a total of 84 questions divided into seven sections. Most of the questionnaire items dealt directly with opinions related to policies, programs, and practices affecting ex-prisoners during their prison-to-community transition. A few sections asked questions related to topics such as religious beliefs, community conditions, and personal characteristics. The analysis here focuses on 19 survey items that were designed to load on specific dimensions of attitudes toward reentry initiatives. At the beginning of the survey, respondents were instructed to specifically think of exprisoners who have been released from prison for 3 months or less. Items related to job training, education, and substance and mental health services are proposed to load onto a transitional programming factor. Using six-item, Likerttype response scales ranging from 1 (oppose strongly) to 6 (favor strongly),


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respondents noted their degree of support for or opposition to ex-prisoners re-entering society receiving the following across three subsections of the survey: job training for food services, landscaping, roofing, carpentry, computer programming, and business management; educational programs to earn a GED/high school diploma and 2-year technical degree; and treatment services for substance abuse and mental health needs. We included multiple types of blue-collar vocational training given the diverse focus of job-based reentry training. The second proposed dimension is transitional housing. Respondents were provided six-item, Likert-type response scales, again ranging from 1 (oppose strongly) to 6 (favor strongly), and asked to indicate their support for transitional housing units based on the location and the type of offender placed there. Specifically, respondents rated support for transitional housing units placed in their city for violent offenders, neighborhood for violent offenders, city for sex offenders, neighborhood for sex offenders, city for drug offenders, and neighborhood for drug offenders. The introduction to this subsection specifically stated the following: “Some communities have created transitional housing centers for offenders coming out of prison. These centers range from large-scale facilities designed to house many people to more traditional housing arrangements which hold only a few ex-prisoners.” Violent offenders were defined as people who were imprisoned for crimes such as muggings and beatings. Sex offenders were defined as those who were sent to prison for crimes such as rape and other forms of illegal sexual conduct. Finally, drug offenders were described as people who were incarcerated for selling or possessing illegal drugs. The distinction between city and neighborhood for each crime type as well as the distinctions among violent, sex, and drug crimes were driven by the expectation of attitudes diverging due to NIMBY concerns. Given potential concerns about declining property values and individual safety associated with NIMBY, support for transitional housing facilities is expected to fluctuate when respondents are asked to consider proximity (Dear, 1992). Likewise, support for transitional housing programs is expected to vary in relation to the perceived threat posed by the residents, as would likely be the case when respondents are asked to consider various types of criminals such as violent, sexual, or drug offenders (Brown, 1999, 2009; Wilton, 2000). The final proposed dimension, denial of opportunities, taps into whether respondents oppose a recently released prisoner being denied opportunities due to their offender status. All three items here are about housing assistance and were positioned in a survey section where respondents were asked to think about issues related to housing and prisoner reentry. For these items, each person was asked his or her agreement or disagreement based on a 6-point scale, ranging from 1 (disagree strongly) to 6 (agree strongly). This response scale was reversed for the analysis so that higher scores indicate stronger opposition to denying offenders housing assistance. This modification ensures that higher scores on each dimension are reflective of more supportive attitudes toward reentry, which is important for consistency and interpretation. The housing items for this dimension asked separately whether respondents felt housing agencies should be able to deny a person the right to live on their property if the person is a violent offender, sex offender, or drug offender. Offenders could be denied


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opportunities in other aspects of their return to society, such as employment, child care, and voting rights (Lynch & Sabol, 2001; Petersilia, 2000, 2001). Unfortunately, survey items specific to the denial of these types of opportunities were not included. Accordingly, the proposed denial of opportunities dimension is referred to as denial of housing assistance throughout the remainder of the article. The variation of items based on crime type (sex, violent, and drug offenders) is justified because retributive attitudes, which likely drive support for these policies, vary across offender types.

Analytic Strategy The first step in the analysis calls for an exploratory factor analysis (EFA) on the 19 items expected to load onto a particular dimension of support for prisoner reentry. EFA examines correlations among groups of variables for the presence of subsets of correlations, which exist relatively independently of other subsets (Tabachnik & Fidell, 2007). Those subsets are representative of factors, which “reflect underlying processes that have created the correlations among variables” (Tabachnik & Fidell, 2007, p. 607). Principal axis factoring (PAF), which assesses the covariance, or communality, of the variables, was used to extract the factors. Whereas other strategies, such as principal components analysis, seek to explain the maximum variance of a dataset, the goal of principal axis factoring is to reproduce the underlying correlation matrix with the fewest number of factors (Tabachnik & Fidell, 2007). Principal axis factoring is the best fit here as this study’s foremost goal is to determine whether three distinct dimensions of public support for prisoner reentry exist.1 The second step is an external correlates test using ordinary least squares (OLS) regression. External correlates tests are used to examine the validity of separate composite scales. If composite scales are representing distinct dimensions, relationships between the scales and other variables should vary in regression analyses. A lack of variation in significant relationships and their strength would indicate the presence of a singular concept. We use the following variables as potential predictors in the external correlates test: age (measured in years), race (1 = White, 0 = non-White), gender (1 = male, 0 = female), education (1 = bachelor’s degree or higher, 0 = less than bachelor’s degree), political ideology (measured on a scale ranging from 1 = extremely liberal to 9 = extremely conservative), and minor child (1 = has a minor child, 0 = has no minor child). To determine whether responses might differ between the sample and true population, the sample was weighted to reflect the population demographic characteristics. Responses to each survey item were then examined descriptively for both the weighted and unweighted sample, and no substantive difference was identified. As a result, it is very unlikely that demographic overrepresentations in the sample influenced the factor analysis or regression results.

Results The dataset was first examined for missing data prior to factor analysis. Missing responses composed 1% of the dataset for the variables analyzed. Deleting cases


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Figure 1. Initial scree plot for 19 items expected to load onto dimensions of support for prisoner reentry.

containing missing data listwise resulted in the removal of 28 respondents, leaving a final analyzable sample of 358 people. For the EFA, an oblique rotation was specified, as the three factors were expected to correlate with each other. To justify the extraction of three factors, a scree plot of eigenvalues was first examined (Cattell, 1966). Eigenvalues represent the percentage of variance explained by the given factors. The angle of curvature on the scree plot indicated that a three-factor solution was most appropriate (see Figure 1). As indicated in Table 1, all items in the EFA loaded as expected at the .522 absolute value level or above, and no cross loading exceeded .2 in absolute value. Cronbach’s alpha values were above .80 for each factor, indicating good internal consistency. Eigenvalues for the three factors were 7.702, 2.925, and 1.164. The cumulative percentage of variance explained was 62.056%. The Kaiser–Meyer–Olkin Measure of Sampling Adequacy was more than adequate at .842, and the Bartlett’s Test of Sphericity was significant at the .001 level. Non-redundant residuals with absolute values greater than 0.05 were less than 19%, indicating good model fit. The factors were all correlated positively with each other at the .01 level of statistical significance. Transitional programming and transitional housing had a correlation coefficient of .474, and transitional programming and denial of housing assistance were correlated at a coefficient value of .293. Transitional housing and denial of housing assistance had a correlation coefficient


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Table 1. EFA Results for Public Attitudes Toward Reentry Items (N = 358).

Job training in roofing Job training in carpentry Job training for landscaping Educational program for GED/high school diploma Job training for food services Support substance abuse treatment Support mental health treatment Educational program for 2-year degree Job training in computer programming Job training in business management Transitional housing in neighborhood for violent offenders Transitional housing in city for violent offenders Transitional housing in neighborhood for drug offenders Transitional housing in city for drug offenders Transitional housing in neighborhood for sex offenders Transitional housing in city for sex offenders Denying violent offenders housing assistance Denying drug offenders housing assistance Denying sex offenders housing assistance Cronbach’s α Eigenvalues

M (SD)

Factor 1

Factor 2

Factor 3

4.587 (1.191) 4.531 (1.217) 4.232 (1.376) 5.159 (1.077)

.934 .919 .914 .754

4.581 (1.175) 4.698 (1.144) 4.665 (1.166) 4.338 (1.506) 3.838 (1.574) 3.500 (1.553) 1.966 (1.092)

.712 .690 .651 .650 .595 .522 .832

2.522 (1.390)

.815

2.271 (1.231)

.804

2.885 (1.434)

.781

1.844 (1.109)

.756

2.464 (1.419)

.915

2.321 (1.216)

.888

2.682 (1.359)

.747

2.346 (1.350) .927 7.702

.908 2.925

.687 .827 1.164

Note. Cumulative variance explained = 62.056%. Kaiser–Meyer–Olkin = .832. Bartlett’s test significance = .000. EFA = exploratory factor analysis.

of .443. While the factors are correlated, the coefficients are not very high, which further suggests the dimensions are distinct. OLS regressions results examining the validity of the factors are presented in Table 2. Each model was statistically significant. Three variables—gender, education, and political ideology—significantly predicted scores on the transitional programming scale. Respondents who were female, had bachelor’s degrees, and held more liberal political attitudes indicated stronger support for transitional programming. Only education and political ideology significantly affected support for transitional housing. More educated and politically liberal respondents reported stronger


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Table 2. OLS Regression Results for Each Dimension of Public Attitudes Toward Reentry. TransProg Age Race Gender Education Political ideology Minor child R2

TransHous

Denial

b

B

b

B

b

B

.002 −.292 −.425* .382* −.146* .077 .150*

.025 −.081 −.200 .178 −.252 .031

−.005 −.181 −.092 .470* −.108* −.139 .067*

−.075 −.047 −.040 .201 −.173 −.052

.001 −.721* .070 .199 −.136* .067 .083*

.011 −.189 .031 .087 −.223 .026

Note. OLS = ordinary least squares; TransProg = transitional programming; TransHous = transitional housing; Denial = denial of housing assistance. *p< .05.

support for transitional housing units. Race and political ideology had statistically significant effects on denial of housing assistance. Black and politically liberal respondents were more opposed to denying housing to offenders during reentry. The external correlates test using OLS regression shows differences in predictors for each dimension. In addition, the beta weights indicate the relative strength of education and political ideology as predictors differed noticeably across transitional programming and transitional housing. Political ideology was the stronger variable for transitional programming, whereas education was stronger for transitional housing. Finally, the independent variables collectively were much stronger predictors of transitional programming. Specifically, about twice the amount of variance was explained by the independent variables for transitional programming (15%) in comparison with transitional housing (7%) and the denial of housing assistance (8%). Although the R2 values are rather small, the models were not designed for theory testing but rather to examine discriminant validity through an external correlates test. As a result, the low R2 values should not be interpreted as posing a limitation. Several potential limitations of this research should be noted. First, the research is conducted on residents from a single state. Studying a sample from a single area obviously poses risks regarding the generalizability of the results. However, the demographic characteristics of this Midwestern state, with the exception of Hispanic ethnicity, are quite representative of the United States. A second limitation is the crosssectional nature of the analysis. Opinions change over time, which is always a concern when trying to determine the exact amount of support or opposition for a policy or practice. The analysis here, however, is focused on whether distinct dimensions of public attitude exist, which are less likely to be altered by temporally based changes. A third limitation is that we only asked about sex, violent, and drug offenders, leaving out other types of offenders to conserve survey space. Future research should examine whether attitudes about reentry are different when items are directed at property, DUI (driving under the influence), and vice-related offenders who are likely perceived as


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less serious social threats. Fourth, a residence location variable was not included. Exploring whether a person resides in a rural, suburban, or urban location would be an interesting addition to the analysis, especially when considering that many transitional housing units are placed in urban environments. Finally, the survey items did not distinguish between males and females. People may be more receptive to assisting female rather than male offenders with reentry needs.

Discussion This research adds to the very limited literature on public perception of prisoner reentry. The results tentatively suggest the existence of at least three dimensions: transitional programming, transitional housing, and denial of opportunities as represented by denial of housing assistance. This analysis is preliminary, and additional work is required to fully develop and confirm these dimensions and to explore the possibility of additional dimensions. A few points about the factor analysis are important. First, all items loaded sufficiently on the expected factors, although all items loading onto transitional programming might not be necessary. The job training items related to roofing, carpentry, and landscaping were all very high, suggesting that a more general item might sufficiently tap feelings toward reentry training for these outdoor-oriented, blue-collar jobs. Interestingly, training for food services, a blue-collar occupation, did not load nearly as strongly. Second, the denial of opportunities dimension needs to be examined with additional items as it only represented denial of housing assistance here. Opportunities can be denied to offenders in other areas such as employment and voting. Without items to measure denial of other types of opportunities, it is not clear whether a broader dimension of denial of opportunities truly exists or whether it is limited specifically to housing. Finally, the transitional programming items are not asking about a specific type of program such as a reentry court, therapeutic community, or faith-based services. Attitudes toward transitional assistance might vary based on the type of program providing services. Notably, the responses to the transitional programming items on average were much more favorable than transitional housing and denial of housing items. In addition, the city-specific transitional housing items received greater support than the neighborhood-specific items. Although the purpose of this study is to examine the expected dimensionality of attitudes toward reentry options, these findings warrant a few comments. Political psychology research supports that certain types of values influence differences in public opinion (Brewer & Gross, 2005; Feldman, 2003). Transitional housing and denial of housing opportunities likely arouse stronger emotional reactions and greater concerns about public and personal safety and the fair distribution of government resources than transitional programming. Housing is a universal need, and thus, offenders may be viewed as less deserving of housing assistance than non-offenders (Applegate, 2001; B. Garland et al., 2013). The public recognizes that offering programmatic assistance to offenders is one of the few options available for reducing recidivism (Cullen & Moon, 2002), and any expectation that the public


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might feel threatened or overly uncomfortable about offering such assistance has no empirical grounding. Consequently, reentry programming receiving greater support than the other dimensions makes sense. It is important to emphasize that the neighborhood-specific items about transitional housing did not load separate from the cityspecific items. Nonetheless, the less favorable responses on the neighborhood-specific items are likely the result of fear about declining property values and threats to public and personal safety (Dear, 1992; National Law Center on Homelessness and Poverty, 1997). The knowledge gained regarding the dimensionality of attitudes toward reentry options will help academics make more accurate attitudinal measurements in future analyses and thereby generate more valid results. Without research on the dimensionality of reentry measures, future researchers might combine transitional housing items with transitional programming and denial of opportunities items to form a composite scale. This study will deter researchers from making such mistakes and hopefully lead to further development of possibly stronger measures. Policymakers will also benefit as the information they receive from the academic community about public opinion toward reentry will have a firmer empirical basis and better guide integration of public input into policy and practice. More specifically, policymakers will be aided by an instrument that examines the dimensionality of reentry support by receiving clarity on which efforts the public will or will not endorse and how extensively each dimension will be backed. Current measures of reentry support might give policymakers the false impression that the public is completely supportive or completely unsupportive of reentry policies and initiatives when they are actually more likely to have differing levels of support for various options. Future studies should explore potential correlates of support for reentry policies and practices. Research has shown that people are supportive of justice-related policies that produce the desired results (Mears & Mancini, 2006; Nagin, Piquero, Scott, &Steinberg, 2006; Piquero & Steinberg, 2010). In addition, perceptions of local crime and disorder likely have some influence on support for reentry initiatives (Leverentz, 2011). Perceptions of criminal justice goals also might affect levels of support for reentry measures. People who are more receptive to the broader goal of rehabilitation may be less hesitant about supporting specific transitional skill programs aimed at enabling ex-prisoners to succeed. The extent to which rehabilitation advocates will back transitional housing and resist the denial of housing privileges to offender groups is less clear. Certainly, the odds of a recently released offender avoiding recidivism may increase after securing a stable living environment (Urban Institute, 2006). However, the desire for rehabilitative success may be moderated by the possibility that adding offenders to housing sites and specific high-crime neighborhoods could destabilize communities and lead to higher levels of crime (Clear et al., 2001). Evidence suggests that perceptions of offenders affect support for correctional policies. Increased familiarity with offenders leads to opinions that are less stigmatizing (Hirschfield & Piquero, 2010) and more favorable toward hiring offenders (Giguere & Dundes, 2002). Research on juvenile sentencing policies also shows that having a


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family member in the juvenile system reduces the likelihood of a person supporting harsher sentencing options (B. Garland et al., 2012). It is thus reasonable to propose that people who have more contacts and positive experiences with the offender population will be more likely to back reentry policies which offer aid and oppose policies that pose obstacles due to felony status. In addition, the reentry scales can be used to measure the impact of public support on the longevity and sustainability of current reentry initiatives. For example, if transitional housing units are placed in several locations throughout a state, longitudinal research could analyze support in each location with the units’ duration of operation. Another consideration for future research is to move the administration of this survey instrument beyond the general public to more specific groups for external validation. It would be interesting to see whether the factor structure identified here holds with criminal justice administrators and professionals, especially those working in probation, parole, and institutional settings. Studies examining how attitudes among these groups vary would be useful, as support for prisoner reentry policy within agencies may logically affect how forcefully the reentry policies are pursued. In addition, the number of years working in corrections, management versus ground-level position, and treatment versus custody orientations may prove to have independent effects on the three dimensions of support. In conclusion, this study provides a stepping stone to examine an under-researched but highly important area, public perception of prisoner reentry. For the first decades of the modern reentry movement’s existence, politicians and citizens have appeared nonresistant, if not quite supportive, of efforts to increase the chances of success for prisoners who reenter society. This honeymoon period with prisoner reentry, however, may be fading. The certainty of strong, sustained funding for reentry programs has waned at both the state and federal levels very recently (Grissom, 2011; Nolan, n.d.; Rogers, 2012). Reevaluations of the importance of prisoner reentry initiatives are likely driven in part by lackluster economic realities which are affecting funding and resource allocation (B. Garland et al., 2013). In addition, while the new prisoner reentry movement started with a flurry of ideas and signs of success, the impact of reentry programming is now being questioned (B. Garland & Wodahl, 2014; Lattimore et al., 2010; Walker, 2011; Wilson & Davis, 2006). As noted earlier, if the public perceives reentry initiatives as ineffective, this may seriously weaken support, which, in turn, can limit policymakers and professionals in their ability to implement and sustain reentry policies (Burstein, 2003; Nicholson-Crotty et al., 2009; Wlezien, 2004). The current study offers a starting point for understanding the reasons why the public supports or opposes reentry measures. Upon the platform laid by this research, academics and policymakers can study and analyze the various factors that contribute to the perceptions of reentry and be more informed to address concerns that may arise about prisoner reentry efforts. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.


15

Garland et al. Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors received funding from the College of Humanities and Public Affairs at Missouri State University to support the data collection phase of this research project.

Note 1.

To ensure that our results were not an artifact of the use of PAF, a particular form of factor analysis, the analysis was run a second time using principal components analysis (PCA). The PCA results mirrored the PAF results with all items loading on the correct factors and no crossloadings.

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