Employment and earnings among ex-offenders with disabilities: A multivariate analysis of RSA-911 data

Abstract

BACKGROUND:

Ex-offenders with disabilities encounter barriers with obtaining employment upon post-release. Offender status may affect not only opportunities for employment, but earnings as well for ex-offenders with disabilities.

OBJECTIVE:

METHODS:

Descriptive and multivariate statistical analyses utilizing archival Rehabilitation Services Administration Case Service Report (RSA-911) data from fiscal years 2004– 2013 was employed.

RESULTS:

Findings indicated that African American ex-offenders with disabilities are employed at higher rates than both Hispanic and White ex-offenders but earn less than both of these groups.

CONCLUSIONS:

Implications for VR service providers, training and policy reform are discussed.

Keywords

African American Hispanic/Latino disability rehabilitation employment offender

1 Introduction

Ex-offenders with disabilities face multiple barriers and disadvantages to employment not only because of a disability, but more often because of a criminal record. Graffam (2016) suggests in the context of ex-offenders’ multiple disadvantages are more than “multiple”; they are complex and interactive. As ex-offenders with disabilities leave prison, their debilities continue to cause them problems as they re-enter their respective communities (Travis et al., 2001). Such barriers include, but are not limited to, low educational attainment, a lack of job skills, poor work history, low self-esteem or motivation, racism of employers or co-workers, substance abuse, stigma, negative public attitudes, and economic obstacles that are complicated by physical, cognitive, behavioral and mental health problems that limit their employability.

People with disabilities experience high levels of discrimination when applying for and maintaining employment (Darakai et al., 2017). Ex-offenders with disabilities are therefore likely to face significant challenges in their efforts to find meaningful and stable work. Unfortunately, ex-offenders re-enter society with limited assistance or access to resources; yet are expected largely to manage their own reintegration. The lack of support often increases recidivism and decreases reoffending (The Sentencing Project, 2011; Visher et al., 2010).

Substance abuse is strongly associated with offending. Bennett et al. (2008) reported the odds of offending were three to four times greater for drug users than non-drug users, with the odds highest among crack users and lowest among recreational drug users, and this relationship held true across a range of offenses including robbery, burglary, prostitution and shoplifting. Terry and Cardwell (2015) examined the question of common concepts for recovery across the fields of mental health, substance abuse, and criminology. The authors found three common themes: (a) recovery journeys are difficult and relapse or setbacks are common; however, many people can and do overcome deeply entrenched problems, (b) finding meaningful opportunities and roles helps to build a positive self-image, and (c) supportive friends and family play a key role in sustaining these journeys, while discriminatory attitudes and labels can hold people back. In addition, substance abuse adversely affects employment outcomes for offenders because many of them test positive on drug screens.

The purpose of this study is to discuss barriers to employment for ex-offenders with disabilities and to identify how racial/ethnically marginalized ex-offenders are disproportionately unemployed and earn less than their White counterparts. Information is presented on the relationship between employment and race and how stigma affects the behavior of ex-offenders. Implications for rehabilitation counseling and recommendations are presented from the analysis. The intent is to further promote the necessity of identification of criminal history in RSA 911 data to assist rehabilitation counselors with preempting potential barriers and discrimination toward racial and ethnically marginalized ex-offender.

2 Race and offender status

Historically marginalized groups (i.e., African American/Black and Latino) are overrepresented among the offender population and experience institutionalized racism in the criminal justice system; thus, they receive harsher sentences. An examination of the intersection of race and offender status reveals disproportionate representation of African Americans and Latinos compared to Whites in offender and incarcerated populations (Owens et al., 2017). Two competing hypotheses for these large race disparities have been proposed. The first, “differential involvement hypothesis”, is that African Americans and Hispanics commit more crime and more of the types of crime (e.g., violence) that lead to processing in the criminal justice system (Blumstein, 1993; Elliott, 1994). The second hypothesis, “differential criminal justice system selection hypothesis”, suggests that differential police presence, patrolling, and profiling, combined with discrimination in the courts and correctional systems, leads to more African Americans and Latinos being arrested, convicted, and incarcerated (Chambliss, 1994; Zimring & Hawkins, 1997). Over time, the literature includes research supporting both hypotheses. However, “the most recent generation of evidence suggests that while racial dynamics have changed over time, race still exerts an undeniable presence in the sentencing process” (Kansal & Mauer, 2005, p.1). Moreover, recent studies are more methodologically sound and the focus is not on the sentencing process as usually plagued by racial bias, rather on examining if racial bias does exist in the sentencing process, under what circumstances does it manifest itself and when is it most apparent (Kansal & Mauer, 2005).

Beyond the initial sentencing, patterns of inequality based on race for African Americans and Latinos are evident in the criminal justice policies and practices over the past three decades. According to The Academies of Sciences, Engineering, and Medicine (2018), disparities start before the sentencing decision. For example, prosecutors’ decisions about case selection, charging decisions, and statutory enhancements can be very discretionary and, consequently, very unequal, as well as highly punitive. The criminal justice system’s impact on racial minorities and communities of color is illuminated by the Center for American Progress as follows:

While people of color make up approximately 30 percent of the U.S. population, they account for 60 percent of those imprisoned.

One in three black men can expect to go to prison in their lifetime.

Students of color face harsher punishment in school than their White peers, leading to a higher number of youth of color incarcerated.

African American students are arrested far more often than their White classmates.

African American youth have higher rates of juvenile incarceration and are more likely to be sentenced to adult prison.

With significant increase in the number of women incarcerated over the last three decades, women of color have been disproportionately represented.

The war on drugs has been waged primarily in communities of color where people of color are more likely to receive higher offenses.

Once convicted, black offenders receive longer sentences compared to White offenders.

Voter laws that prohibit people with felony convictions to vote disproportionately impact men of color.

People of color face disparities in wage trajectory following release from prison (Kerby, 2018).

Clearly, disparities exist and the adverse effects on people of color carry over into other aspects of life over the lifespan. In relation to employment, ex-offenders of color are faced with bans on employment in a number of sectors in most states, which are dominated by racial minorities. Moreover, disparities in wage trajectory for African American ex-offenders are more severe compared to Whites. After release from prison or having an offender status, wages grow at a 21 percent slower rate for African American former inmates compared to White ex-convicts (Lyons & Pettit, 2011).

3 Employment and wage earnings

Employment is important in reducing recidivism in ex-offenders (Giordano et al., 2002: Swensen et al., 2014). Employment is central in the lives of ex-offenders because having a job reinforces social conformity, promotes close and frequent contact with conventional others in the workplace, can create new situations for supervision and monitoring, creates opportunities of social support, and creates a change in routine activities with the opportunity for identity transformation (Devers, 2011). Although much emphasis is put on the importance of work for ex-offenders, the quality of work is equally important. That is, it is just as important for ex-offenders to find gainful employment that offers a living wage. Unfortunately, the perpetual labor market punishment creates a counterproductive system of release and poverty, especially for Blacks or Latinos – even more so for women - with the status as “formally incarcerated” (Couloute & Kopf, 2018). Race may be more of a factor in unemployment than offender status. The unemployment rate for African Americans in general is double that of Whites. Offender status then becomes a collateral sanction for racial minority groups.

Apel and Horney (2017) investigated the role of work quality and why work matters among adult male offenders. Their finding suggested employment significantly reduces self-report crime, but only when employed men reported strong commitment to their jobs, whereas other work characteristics were unrelated to crime. That is, among serious criminally involved men, the subjective (commitment) experience of work takes priority over its objective (hours, income) characteristics. Moreover, the results indicated that routine activities only partly mediate the relationship among work, job commitment, and crime, whereas the majority of the work-crime relationship remains unmediated. Weaver (2016) asserted employment alone is not sufficient; rather, it is the personal meaning and outcomes of either the quality of the work or participation in employment and how these influence an individual’s self-concept, social identity and interact with a person’s priorities, goals, and relational concerns.

A record of conviction and incarceration affects an ex-offender’s path to economic mobility not only for the individual, but for subsequent generations. According to Western and Pettit (2011), incarceration carries significant and enduring economic repercussions for the remainder of the person’s working years. Western and Pettit calculated the impact of incarceration on economic mobility and found the following results. First, incarceration is concentrated among men, the young, uneducated and racial and ethnic minorities, especially African Americans. Second, incarceration negatively affects former inmates’ economic prospects. Third, former inmates experience less upward mobility than those who are never incarcerated. Forth, the impacts of incarceration reach far beyond former inmates to their children and families. Finally, a child’s prospect of upward economic mobility is negatively affected by the incarceration of a parent. These findings suggest for individuals who had been incarcerated, the ripple effects result in less success in getting ahead even with maturity, hard work and experience. In both relative and absolute terms, ex-offenders’ current work and earning prospects are negated by their past crime conviction.

One other point worthy of mention is that increased policing of African American and Latino neighborhoods automatically increases their chance of arrest. Once arrested, individuals are entered into a criminal database. An inherent problem with criminal record databases is inaccuracies that plague criminal history reports such as false positive identifications and the release of sealed and expunged information. The increasingly common use of and reliance on criminal records databases by employers has compound existing social and economic problems for people of color with criminal records because it leads to a disproportionate exclusion of African Americans and Latinos from the workforce (Paul-Emile, 2014).

Rehabilitation counselors working with ex-offenders in general, and racial and ethnically marginalized ex-offenders in particular are encouraged to understand the barriers to employment and earnings outcomes. In addition, having prior knowledge (i.e., RSA-911 data) about offender status may assist counselors in understanding not only limitations placed on employment, but also motivational factors in seeking employment.

4 Stigma affect behavior and employment outcomes

Labels such as offender, criminal, felon, and inmate are stigmatizing (Becker et al., 1963). According to Labeling Theory, one consequence of such tags is the internalization and acceptance of a criminal identity (Becker et al., 1963). That is, both an individual and the larger community may reinforce the criminal identity by denouncing and differentiating the ex-offender from other citizens (Kiss & Kras, 2015). The anticipation of experiencing discrimination may explain why perceived labeling leads to maladaptive behavior of ethnic minority ex-offenders. Ex-offenders from racial and ethnically marginalized groups must contend with perceived stigma (perceptions that society currently holds negative views of one’s group) and anticipated stigma (focuses on the future and what a person expects to experience as a result of stigma; Quinn & Chaudoir, 2009). Often, both of these are manifested as discrimination in employment hiring practices. Ex-offenders continue to face barriers to employment despite recent studies that “cast doubt on the assumption that the existence of a criminal record correctly forecasts one’s work behavior, and data show that after not reoffending for several years a person with a criminal record is no more likely than anyone else to have a future arrest” (Paul-Emile, 2014, p.895).

Moore et al. (2013) examined stigma among offenders and found race impacts the relationship between stigma and behavior. That is, offenders from racially marginalized groups tend to process and cope with stigma differently than non-minorities. Racially marginalized groups experience visible stigma (e.g., skin color, racial features, dialect or language) and are used to incorporating stigmatization into their psychological coping. Racially marginalized ex-offenders with disabilities have triple stigmas (being a minority, ex-offender, and having a disability), which potentially reduce employment opportunities. Moore et al. (2016) expanded on the study of Moore et al. (2013) and found African Americans and other racially marginalized groups do not experience as many negative effects resulting from the perception of additional stigmas because of having to manage racial discrimination. Another possible explanation is that on average racially marginalized ex-offenders are functioning worse at the one-year post-release time point than White offenders. In addition, perceived stigma did not predict recidivism, substance dependence symptoms, or mental health symptoms.

Although men with criminal records are more likely than women with criminal records to receive a negative response from employers, both Black and Latino men are less likely to receive a positive response compared to White men (Decker et al., 2014), even when they do not reoffend. The question then becomes, how do stigma, labeling, and racial discrimination influence African American/Black and Latino ex-offenders’ employment outcomes and hourly wage earnings? This question served as a foundation to investigate the employment and earnings outcomes for African American/Black and Latino ex-offenders regarding the following research questions:

What impact does race/ethnicity of ex-offenders have on employability?

Does disability type impact the employability of ex-offenders?

How does race/ethnicity impact wage earnings for ex-offenders?

5 Methods

Data were derived from the fiscal year 2004– 2013 Rehabilitation Services Administration Case Service Report (RSA-911) database. The RSA-911 database is an administrative dataset on individual characteristics, services provided, and employment outcomes of all vocational rehabilitation customers who complete rehabilitation in a fiscal year. It is a public database compiled with input from agencies that provide services within the state-federal program for vocational rehabilitation. Living arrangement at application was the variable used to capture the participants’ criminal histories, as there is no variable that captures this information presently. In particular, living arrangement at application encompasses private residence, community residential/group home, rehabilitation facility, mental health facility, nursing home, halfway house, substance abuse treatment center, homeless shelter, adult correctional facility, and other. This variable also considers the participants’ residence as either temporary or permanent.

5.1 Participants

From 2004– 2013, 5,612,846 persons sought state vocational rehabilitation services. Of these persons, 32,825 (59%) were ex-offenders seeking vocational rehabilitation services. While RSA-911 data captures demographics for all racial groups, the researchers were interested in African American and Latino ex-offenders compared to White ex-offenders and their employability. The majority of ex-offenders were African American (46%), followed by Caucasian (38%) and Latino (33%), respectively. There were approximately 27,000 (83%) males and 5,500 (17%) female ex-offenders. In terms of race and gender, African American men were the largest group of ex-offenders (54%), followed by White (41%) and Hispanic (5%) men. For women, White women were the largest group of women at 57%, followed by African American (37%) and Hispanic (6%) women. The participants in the study varied in their primary disabilities. For both male and female ex-offenders, substance abuse, mental health, and mental retardation/developmental were the highest diagnoses for this population. Regarding having a substance abuse disorder, female ex-offenders had higher rates of substance abuse (48%) than men (40%). However, men and women had similar rates of having mental health disorders at a rate of 33.4% and 33.9%, respectively. Concerning mental retardation, the rates for these groups were dissimilar as more male ex-offenders were diagnosed with having this disorder (6%) than female ex-offenders (5%). Additional demographic information can be found in Table 1.

Table 1
Descriptive Statistics for All Variables

Variable Obs Mean Std. Dev. Min Max

Dependent Variable

Successful Employment Closure (Y/N) 32,825 0.419741 0.493524 0 1

Demographics

Male (Y/N) 32,825 0.832262 0.373639 0 1

Non-Hispanic Black (Y/N) 32,825 0.514943 0.499784 0 1

Hispanic (Y/N) 32,825 0.05112 0.220245 0 1

Transition Age Youth (14– 24 Y/N) 32,825 0.15997 0.366583 0 1

Elderly (65 + Y/N) 32,825 0.001401 0.037409 0 1

No Formal Education (Y/N) 32,825 0.061752 0.240708 0 1

Special Education Certificate (Y/N) 32,825 0.347022 0.47603 0 1

Post-Sec Education (Y/N) 32,825 0.121005 0.326138 0 1

BA above Education (Y/N) 32,825 0.012521 0.111196 0 1

Benefit and Insurance

Receiving Any Benefit (Y/N) 32,825 0.093313 0.290875 0 1

Have Any Insurance (Y/N) 32,825 0.098675 0.298229 0 1

Type of Disability

Substance Abuse (Y/N) 32,825 0.414501 0.492643 0 1

Mental Health Disability (Y/N) 32,825 0.338187 0.4731 0 1

VR Services Received (Y/N)

Assessment 32,825 0.475522 0.499408 0 1

Diagnosis 32,825 0.441919 0.496623 0 1

Counselling 32,825 0.52457 0.499404 0 1

College Education Services 32,825 0.012521 0.111196 0 1

Occupational/vocational training 32,825 0.026535 0.160721 0 1

On the job training 32,825 0.014349 0.118926 0 1

Basic academic/literacy training 32,825 0.011394 0.106133 0 1

Job readiness training 32,825 0.124296 0.329923 0 1

Disability related training 32,825 0.002194 0.046784 0 1

Misc. training 32,825 0.037106 0.189024 0 1

Job search 32,825 0.277593 0.447819 0 1

Job placement 32,825 0.322011 0.467254 0 1

On the job supports 32,825 0.089018 0.284773 0 1

Transportation 32,825 0.28984 0.453695 0 1

Maintenance 32,825 0.209322 0.406831 0 1

Rehab. technology 32,825 0.004905 0.069863 0 1

Reader 32,825 0.000213 0.014602 0 1

Interpreter 32,825 0.000914 0.030218 0 1

Personal assistance 32,825 0.000274 0.016556 0 1

Technical assistance 32,825 0.010967 0.10415 0 1

Information/referral 32,825 0.083534 0.276692 0 1

Other services 32,825 0.340381 0.473844 0 1

Variable	Obs	Mean	Std. Dev.	Min	Max
Dependent Variable
Successful Employment Closure (Y/N)	32,825	0.419741	0.493524	0	1
Demographics
Male (Y/N)	32,825	0.832262	0.373639	0	1
Non-Hispanic Black (Y/N)	32,825	0.514943	0.499784	0	1
Hispanic (Y/N)	32,825	0.05112	0.220245	0	1
Transition Age Youth (14– 24 Y/N)	32,825	0.15997	0.366583	0	1
Elderly (65 + Y/N)	32,825	0.001401	0.037409	0	1
No Formal Education (Y/N)	32,825	0.061752	0.240708	0	1
Special Education Certificate (Y/N)	32,825	0.347022	0.47603	0	1
Post-Sec Education (Y/N)	32,825	0.121005	0.326138	0	1
BA above Education (Y/N)	32,825	0.012521	0.111196	0	1
Benefit and Insurance
Receiving Any Benefit (Y/N)	32,825	0.093313	0.290875	0	1
Have Any Insurance (Y/N)	32,825	0.098675	0.298229	0	1
Type of Disability
Substance Abuse (Y/N)	32,825	0.414501	0.492643	0	1
Mental Health Disability (Y/N)	32,825	0.338187	0.4731	0	1
VR Services Received (Y/N)
Assessment	32,825	0.475522	0.499408	0	1
Diagnosis	32,825	0.441919	0.496623	0	1
Counselling	32,825	0.52457	0.499404	0	1
College Education Services	32,825	0.012521	0.111196	0	1
Occupational/vocational training	32,825	0.026535	0.160721	0	1
On the job training	32,825	0.014349	0.118926	0	1
Basic academic/literacy training	32,825	0.011394	0.106133	0	1
Job readiness training	32,825	0.124296	0.329923	0	1
Disability related training	32,825	0.002194	0.046784	0	1
Misc. training	32,825	0.037106	0.189024	0	1
Job search	32,825	0.277593	0.447819	0	1
Job placement	32,825	0.322011	0.467254	0	1
On the job supports	32,825	0.089018	0.284773	0	1
Transportation	32,825	0.28984	0.453695	0	1
Maintenance	32,825	0.209322	0.406831	0	1
Rehab. technology	32,825	0.004905	0.069863	0	1
Reader	32,825	0.000213	0.014602	0	1
Interpreter	32,825	0.000914	0.030218	0	1
Personal assistance	32,825	0.000274	0.016556	0	1
Technical assistance	32,825	0.010967	0.10415	0	1
Information/referral	32,825	0.083534	0.276692	0	1
Other services	32,825	0.340381	0.473844	0	1

5.2 Procedures

Among the variables captured for living arrangement at application, the researchers used the adult correctional facility variable to address the research questions and to differentiate those persons who were living in a non-adult correctional facility and correctional facility. For research question one, race/ethnicity was used as the independent variable, while gender, age, education, benefit received, type of disability, and services received from VR were covariates. Employability was used as the dependent variable and was measured using the Closure 26 variable used in the RSA-911 guidelines. Closure 26 is measured by a client’s competitive employment outcome as defined by the RSA-911 guidelines for achieving competitive employment. Consumers who have achieved successful competitive employment need to have been employed for at least 90 days in a competitive integrated employment setting or self-employed. On the other hand, unsuccessful outcome refers to clients not working after completing their planned vocational rehabilitation program. The types of employment industry include successful closure, self-employment, volunteer, and competitive employment.

For research question two, type of disability was used as the key independent variable. The specific disabilities used in this study identified were mental health and substance abuse. The covariates included gender, race/ethnicity, age, education, benefit received, insurance, and services received from VR. Similarly, to research question one, employability was used as the dependent variable for research question two.

Race/ethnicity was used as the independent variable for research question three. Gender, age, education, benefits received, insurance, type of disability, and services received from VR were used as covariates. The outcome variable for this research question was hourly wage = weekly earnings/hours worked for that week. This variable was coded in the RSA 911 codebook as weekly earnings at closure. The weekly earnings at closure variable was recorded as hourly wages earned for standardization and comparison purposes.

5.3 Data analysis

Descriptive and multivariate statistical analyses were used to address the three research questions including one-way ANOVA, chi-square, and logistic regression. In order to examine race/ethnicity, disability, and wages earned, the researchers adopted the multivariate logit model to relate to the employability of ex-offenders seeking vocational rehabilitation services.

To answer research question one, a 2×3 bivariate cross-tabulation was used to examine the distribution between successful employment outcome (yes/no) and race (White, Hispanic and Black). A logistic regression was used to assess the association between these two variables by introducing other covariates in the multivariate model. For research question two, a logistic regression was used to assess the association between employment outcome (yes/no) and two key explanatory variables-substance abuse status (yes/no) and mental health disabilities (yes/no). Other covariates were also included in the multivariate model. For the final research question, a one-way ANOVA was conducted to compare the differences in hourly wage among the three different racial/ethnic groups followed by an OLS regression to adjust for the effect of other covariates. Table 1 shows the descriptive statistics for all variables used in the analyses.

6 Results

The results for research question one revealed that Black ex-offenders had the highest employability (46%) in terms of employment outcome followed by Whites (39%) and Hispanics (33%). Chi-square results of the bivariate analyses suggested significant differences in successful employment rates among White, Black, and Hispanic ex-offenders (see Table 2). The advantages of Black ex-offenders disappeared when controlled for the other covariates including age, education attainment at application, type of disability, insurance status at application, benefit status at application and services received (see Table 3). The multivariate logit model suggested that compared with otherwise White ex-offenders, Black ex-offenders are more likely to be employed. The expected odds for Black ex-offenders achieving employment outcomes are only 9% higher than that for White ex-offenders. Further results revealed that there was no difference in the employability between Hispanic and White ex-offenders.

Table 2
Cross tabulation of race and successful employment closure among whites, blacks, and hispanic ex-offenders

Employment Closure Status Non Hispanic White Non Hispanic Black Hispanic Total

Did not Achieve Successful N 8,778 9,147 1,122 19,047

Employment Closure % 61.63 54.11 66.87 58.03

Achieved Successful Employment Closure N 5,466 7,756 556 13,778

% 38.37 45.89 33.13 41.97

Total N 14,244 16,903 1,678 32,825

% 100 100 100 100

Employment Closure Status	Non Hispanic White	Non Hispanic Black	Hispanic	Total
Did not Achieve Successful	N	8,778	9,147	1,122	19,047
Employment Closure	%	61.63	54.11	66.87	58.03
Achieved Successful Employment Closure	N	5,466	7,756	556	13,778
%	38.37	45.89	33.13	41.97
Total	N	14,244	16,903	1,678	32,825
%	100	100	100	100

Table 3

Logistic regression of successful employment closure among whites, blacks, and hispanic ex-offenders

CLR 26 Dummy	Odds Ratio	Std. Error	Z	P>z	95% Confidence Interval
Non-His. blk	1.09648	0.0311401	3.24	0.001	1.037114	1.159244
Hispanic	1.001487	0.0644113	0.02	0.982	0.8828759	1.136033
White (ref.)	1.000000		N/A

For research question two, the results of the model on employment outcome (yes/no) suggested that ex-offenders with a substance abuse diagnosis are less likely (OR = 0.897) to achieve employment outcomes when compared with otherwise similar ex-offenders with sensory, physical, intellectual, and other types of disabilities (See Table 4). Additionally, there was no difference in the employability for ex-offenders with mental health diagnoses and with sensory, physical, intellectual, and other types of disabilities. Covariates in the model included age, race, education attainment at application, insurance status at application, benefit status at application and services received.

Table 4

Logistic regression of successful employment closure among types of disability

CLR 26 Dummy	Odds Ratio	Std. Error	Z	P>z	95% Confidence Interval
Substance abuse	0.8971453	0.0333165	– 2.92	0.003	0.8341659	0.9648796
Mental health	0.9816668	0.0359051	– 0.51	0.613	0.9137574	1.054623
Other (ref.)	1.000000		N/A

For the final research question, a one-way ANOVA was conducted to compare the differences in hourly wage among the three different racial/ethnic groups. The results suggested that the differences were statistically significant. Black ($8.05) and Hispanic ($8.86) ex-offenders had the lowest hourly wages, compared to White ex-offenders ($9.24). The disparities in wage remained constant even after controlling for the covariates. The multivariate regression OLS on hourly wage revealed that Black ex-offenders earned $1.08 less than their White counterparts and $0.75 less than their Hispanic counterparts. On the other hand, Hispanic ex-offenders earned $0.33 less than their White counterparts (See Table 5). Covariates in the model included age, education attainment at application, type of disabilities, insurance status at application, benefit status at application and services received.

Table 5

OLS regression of wages earnings among african american and latino ex-offenders

Hour Wage	Coef.	Std. Error	t	P>t	95% Confidence Interval
Male	1.309344	0.0722601	18.12	0.000	1.167704	1.450983
NH Black	1.082876	0.0509331	– 21.26	0.000	– 1.182711	– 0.9830398
Hispanic	1.000000	0.1249779	– 2.69	0.007	– 0.5813879	– 0.0914402

7 Discussion

African American and Latino ex-offenders with disabilities experience significant barriers to employment when compared to their White peers as well as the general population. As in previous research, one can speculate that African American and Hispanic ex-offenders would be expected to have greater need of job placement and jobs of higher wages because of stigma and discrimination over their lifespan (Abel & Horney, 2017). African American and Latino ex-offenders’ lived experience centers on having to contend with the criminal justice process and the additional oppression of racialization (Glynn, 2016).

The difference in earnings between African American, Latino, and White ex-offenders could possibly be a function of not only the type of job, but also the geographic location of the job in which wages may reflect earning thresholds in the region. Location is a primary factor used in benchmarking pay rates and developing salary ranges for most non-executive jobs (Bureau of Labor, 2017; Culpepper and Associates, 2011). Wages, especially minimum wages, are only as valuable as what they can buy, which varies by geography (Chokshi, 2015). For most ex-offenders, even with higher minimum wages, the value of higher minimum wages is low because the purchasing power is less due to the cost of housing and other goods and services.

In the present study, White male ex-offenders earned significantly higher hourly wage than their non-Hispanic Black and Hispanic counterparts; while Hispanic ex-offenders earned significant higher hourly wages than Non-Hispanic Black ex-offenders. Similar findings were found for female ex-offenders. For example, White female ex-offenders earned significantly higher hourly wages than their non-Hispanic Black counterparts; while, Hispanic ex-offenders earned significantly higher hourly wages than Non-Hispanic Black ex-offenders. To understand the differences in wages, the researcher delved into the data further to determine whether this result occurred across regions. The results revealed that there were no significant racial ethnic disparities in hourly wage for the Northeast and Western regions. In the Midwestern region, however, non-Hispanic Whites earned significantly higher hourly wages than non-Hispanic Blacks by $1.44. In the Southern region, both Non-Hispanic White and Hispanic ex-offenders earned higher hourly wages than Non-Hispanic Black ex-offenders.

7.1 Limitations

There are several limitations to this study. The reliance of this study on archival data could have an element of miscoding, which may have contaminated the collection and sequent data analysis. An inherent weakness in ex-post-facto studies are the threats of internal validity, specifically, manipulation of the independent variable. That is, an individual cannot be assigned a race or gender. Since manipulation of the independent variable does not occur, a cause and effect outcome cannot be assumed. The categorical classification of race either as African American/Black, Hispanic/Latino, and White excluded multi-race individuals who may identify as “other”. The exclusion of the increasing number of multi-race individuals, which may also consist in part of African Americans, Latinos, and Whites, may underestimate the number of ex-offenders applying for VR services.

A second limitation is the use of the RSA-911 variable living arrangement at application that does not necessarily allow for specificity in identification of an applicant or customer as an ex-offender. Additionally, this variable does not account for the transitional or transitory nature of ex-offenders with regard to place of residence. Applicants had to identify a source of living arrangement, which would exclude homeless ex-offenders not living in a homeless shelter from any of the other types of living arrangements.

A third limitation is the inability to monitor consumer compliance and follow through. According to the current practice (at the time of this study), it is possible for consumers to apply for VR services and not follow through; thus, the data could inaccurately identify more consumers as ex-offenders than the actual number of those receiving services. It should be noted, historically marginalized (i.e. Black and Latino) consumers tend to prematurely terminate services or be prematurely terminated (Abel & Horney, 2017). Finally, the RSA-911 database may have contained duplication of applicants depending on the number of times they may have applied for services over the time span of the dataset (i.e., 2004–2013). Given the high rate of recidivism of ex-offenders, it is likely that duplication may inflate the number of ex-offenders applying for VR services.

7.2 Implications

The purpose of this study has been to discuss employment barriers for racially/ethnically marginalized ex-offenders with disabilities and the disparities in their wage earnings compared to their White counterparts. Racial statuses of African American and Latino ex-offenders were compared to their White counterparts controlling for other variables, the advantages of African American ex-offenders being most likely to be employed disappeared. In some ways, the results from the present study supports the results of previous studies that reported racial and ethnically marginalized consumers (Mwachofi et al., 2009; Olney & Kennedy, 2002) and African American ex-offenders were less likely to be employed at higher wages than Whites (Decker et al., 2014; Western & Pettit, 2010).

Unemployment is overwhelmingly seen as an important factor in increasing crime. Ex-offenders bear the direct cost of lower employment rates in the form of lower lifetime earnings (Schmitt & Warner, 2010). The collateral consequences of a criminal conviction extend far beyond punishment for the crime committed, and in many instances are not only sanctioned but mandated by the state (Holzer et al., 2003). For racially and ethnically marginalized ex-offenders, these consequences create disparities in labor markets, wages, housing, and physical and mental health issues compared with their White counterpart and the general population. The effects of incarceration have implications on job development and placement for VR counselors working with this population, especially because of the persistent racial disparity in labor market participation. As long as there is the mass incarceration and stigma of African Americans and Latinos, employment discrimination against ex-offenders will remain a major driver of African American and Latino unemployment (Segall, 2011; Simonson, 2006) and disincentives of positive VR outcomes. In addition, alcohol and drug addiction play an important role in ex-offenders’ efforts to secure social supports, their ability to comply with service providers’ expectations, and their capacity to gain and sustain employment. VR counselors need to be aware that conventional measures of involvement in drugs (e.g., whether a client has been convicted of a drug-related crime) understate the prevalence and significance of these addictions (Harding et al., 2014).

7.2.1 Training

Although all VR consumers should receive individualized placement, counselors working with racially and ethnically marginalized ex-offenders should consider using supported employment, specifically evidence-based Individualized Placement and Support (IPS), which is an effective approach to improving employment rates for persons facing substantial barriers (Becker & Drake, 2006). Counselor educators emphasize these points in the multicultural and social justice courses. Counselor educators are also encouraged to consider highlighting social justice when training future VR counselors as well. Budding counselors may need instruction and encouragement on how to take a lead role of advocacy when working with racially and ethnically marginalized ex-offenders, to promote self-advocacy, and to focus on success as opposed to failure. Counselor supervisors could help emphasize and maintain this position for those counselors who are currently in practice.

In addition to enhancing instruction in the multicultural course, counselor educators may wish to use the results from this study to supplement the career counseling and assessment courses. VR counselors could use additional preparation strategies for ex-offenders. Establishing goals in assisting ex-offenders to find employment could be balanced with appropriate counseling for post-incarceration adjustment and transition and referral for other presenting problems such as substance abuse.

7.2.2 Policy reform

In regards to services provided to the profession as well as advocacy for communities, the results of this study could inform policy makers. Those professionals who provide oversight to state vocational education agency are encouraged to consider a two-generation approach to supporting employment for reintegrating ex-offenders. These efforts would also possibly indirectly support the well-being and economic success for parents and children due to one in every 28 children in America having a parent who is incarcerated (Bureau of Labor, 2017). Given the disproportionate number of people of color behind bars, this is not only significant for ex-offenders and their families but also for the communities in which they live (Center for the Study of Social Policy, 2012). Strategies and policies on African American and Latino ex-offenders’ reintegration crimes should be developed within a context of the interface between race, socioeconomic status, inter-racial stressors, social distress, and culturally competent counseling practices.

8 Conclusion

African American and Latino ex-offenders with disabilities face many challenges upon community reintegration, however, employment and wages remain persistent challenges. Having stable employment with comparable wages to their White counterparts can serve as a beginning toward removal of barriers caused by disparities for African American and Latino ex-offenders with disabilities. Both individually and collectively, these groups require a VR counseling approach to employment that accounts for the multiple forms of intersecting institutional and systemic oppression that persist. Participating in these services can assist these individuals as they reintegrate in society and experience barriers.

The addition of a criminal history variable in the RSA-911 data set (Dowden et al., 2016) can assist in better tracking, recording, and supporting the specific needs of African American and Latino ex-offenders with disabilities. Developing specific employment models that target this population (Dowden et al., 2016; Fleming et al., 2012) has the potential to improve employability, wage earnings, and ultimately rate of reoffending.

Conflict of interest

None to report.

Footnotes

Acknowledgments

The financial support for this article was provided by the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number 90RT5024-01-00) to the Langston University Rehabilitation Research and Training Center (LU-RRTC) on Research and Capacity Building for Minority Entities through a collaborative subcontract with the University of Massachusetts Boston Institute for Community Inclusion (ICI). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this article do not necessarily represent the policy of NIDILRR, ACL, HHS, and you should not assume endorsement by the Federal Government.

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