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Feminist Criminology
1 –23
© The Author(s) 2016
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DOI: 10.1177/1557085116668990
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Article
Being Assigned Work in
Prison: Do Gender and Race
Matter?
Courtney A. Crittenden1, Barbara A. Koons-Witt2,
and Robert J. Kaminski2
Abstract
With a majority of inmates being assigned some type of work while incarcerated,
work assignments are a staple of U.S. prisons. These work assignments are likely to
impact not only prisoner behavior while in prison, but also may impact their ability
to obtain gainful employment after prison. Historically, it has been noted that work
in prison has been influenced by gender and racial norms and stereotypes. These
stereotypical assignments may not be beneficial for inmates, especially in a time when
work assignments are increasingly providing the only work skills inmates may receive
while incarcerated. Using a nationwide data set of prisoners incarcerated facilities, the
current study uses multilevel modeling to examine the nature of work assignments
for male and female state prisoners and whether these assignments are based on
gender and/or racial stereotypes. Results indicate that there are indeed lingering
stereotypes influencing work assignments for men and women in U.S. prisons.
Keywords
female inmates, institutional corrections, intersections of race/class/gender, prison
programs, survey research
Introduction
Work assignments are highly common across U.S. prisons with over one half of
inmates being assigned some type of work during their incarceration (Stephan, 2008).
First introduced in penitentiaries as a way to keep inmates busy based on the premise
1The University of Tennessee at Chattanooga, USA
2University of South Carolina, Columbia, USA
Corresponding Author:
Courtney A. Crittenden, The University of Tennessee at Chattanooga, 615 McCallie Avenue,
Chattanooga, TN 37403, USA.
Email: courtney-crittenden@utc.edu
668990FCXXXX10.1177/1557085116668990Feminist CriminologyCrittenden et al.
research-article2016
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2 Feminist Criminology
that “idle hands are the devil’s playground,” this idea still holds true today. Idleness
among inmates has been claimed to be destructive to rehabilitation (Batchelder &
Pippert, 2002), and it is believed that when inmates are kept busy the amount of mis-
conduct problems in an institution will decline (Roberts, 1997). Additionally, when
inmates are busy, the stress among staff within a facility tends to decrease (Batchelder
& Pippert, 2002). Work helps offset the expenses of running prisons because inmates
can complete many of the tasks needed to help with prison operations and can help
lower maintenance costs as well (Batchelder & Pippert, 2002; Flanagan, 1989;
National Institute of Corrections, 1992). Work might also provide viable work skills
for inmates once they are released from prison (Flanagan, 1989), depending on the
type of work an inmate performs. Thus, it is no surprise that work assignments are
usually found in contemporary prisons.
As these work assignments are so common, they may also be the only work experi-
ences that individuals receive during their incarceration. Arguably, work assignments
are provided in prisons to give inmates an opportunity to gain meaningful employment
skills that may increase their abilities to find jobs upon release (Thompson, 2011).
This idea is especially important because vocational programs along with other reha-
bilitative programs have been cut in prisons due to budget shortages (Batchelder &
Pippert, 2002; Porter, 2011). As more prison programming options are eliminated or
scaled back, work assignments may become the only work experience an inmate might
receive. Considering that work skills have been identified as influential factors in suc-
cessful rehabilitation and reintegration (Cullen & Jonson, 2011), the types of work
inmates are assigned and the skills they are learning with this work are increasingly
important. Additionally, literature has shown that many inmates lack job skills or have
unstable employment histories (Ramakers, van Wilsem, Nieuwbeerta, & Dirkzwager,
2015) which make reentry more difficult and the need for programs and job skills even
greater.
Current literature regarding work assignments in contemporary prisons shows that
assignments are divided into three principle activities: prison industry, institutional
maintenance or service tasks, and agriculture (Flanagan, 1989). The most common
work assignments in prisons consist of facility support (e.g., office administration,
food service, and building maintenance) followed by public works (Cullen & Jonson,
2011), both of which involve institutional maintenance or service tasks. Historically,
and even more recently, research on prison work has noted that too often work duties,
and other correctional policies, programs, and services in prison are influenced by
stereotypes and controlling images (Franklin, 2008; Grana, 2010; Lee, 2000; Morash,
Haarr, & Rucker, 1994; Morash & Robinson, 2002), meaning that frequently people
are grouped into work areas based on what are perceived to be “appropriate tasks” for
certain gender and racial groupings. For example, work such as sewing, cooking, and
domestic tasks have been assigned to women (Franklin, 2008; Grana, 2010; Lee, 2000;
Morash et al., 1994), whereas men have been assigned tasks such as public works or
farming (Morash et al., 1994). This highlights the belief that women should be
reformed through domestic training (Labelle & Kubiak, 2004; Rafter, 1990), whereas
men are capable of more skilled and labor-based tasks. However, these examinations
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Crittenden et al. 3
of prison work have rarely focused on the intersections of race and gender in how they
affect work, even though there is evidence in labor market research that shows that
even in more feminine lines of work, women of color are more apt to have jobs such
as cleaning work while White women are more apt to take on professional roles such
as nursing (Duffy, 2011). As prison work seems to mirror divisions in the general labor
market, one may assume that examining it through an intersectional lens is well
advised. The similarities between the labor market and prison labor are discussed
below.
Women and Labor
Both historically and at present, scholars point to labor for women, in and out of
prison, as being influenced by stereotypes. In general society, women have been
expected to participate in feminized labor, or labor that emphasizes their role as pas-
sive, nurturing, and domestic (Goffman, 1977; Simpson, 2005; West & Zimmerman,
1987). For instance, women have often been steered toward domestic work or nurtur-
ing positions such as nursing (Browne & Misra, 2003; Duffy, 2011). However, even in
more feminized labor, there are divisions, typically based on race and class (Browne
& Misra, 2003; Duffy, 2011). As noted by Duffy (2011), when looking at nurturant
labor (e.g., nursing homes, assisted living care facilities) White women and women of
color seem to take on very different roles. White women are more likely to have pro-
fessional positions or to be nurses (Browne & Misra, 2003), whereas women of color
are more likely to take on “dirty work” or cleaning, laundry, and food services (Duffy,
2011). This has been found in other studies as well, for example Nakano Glenn reports
that “backroom jobs” (e.g., janitors, laundry workers, and cafeteria workers) are typi-
cally relegated to women of color (Duffy, 2011). Additionally, the literature notes that
domestic work is deeply imbedded in hierarchies of class, gender, race, ethnicity, and
nationality. Not only are domestic tasks associated with one gender (women), but
gendered norms of childcare and housework being seen as “natural” for women devalue
domestic work and workers. (Browne & Misra, 2003, p. 502)
Domestic work has typically been carried out by minority women who earn low
wages, which allows White women (and men) to leave the home and work as profes-
sionals (Browne & Misra, 2003). Traditionally, the minority women who completed
domestic work were Black women; however, more recently Latinas have been slowly
moving into these roles (Browne & Misra, 2003; Duffy, 2011). Consequently, not only
are Black women often relegated to lower status labor, this labor may be harder and
harder for them to come by, making employment opportunities for Black women espe-
cially limited.
In prisons, women have often been viewed stereotypically (Dell, Fillmore, & Kilty,
2009; Franklin, 2008; Grana, 2010; Lee, 2000; Morash et al., 1994; Morash &
Robinson, 2002). In fact, when feminine stereotypical work (e.g., domestic tasks) was
first introduced in reformatories, it was done so to help wayward women get back on
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4 Feminist Criminology
the right track by teaching them to be “good women” (i.e., wives and mothers; Dell
et al., 2009; Grana, 2010; Koons-Witt & Crittenden, 2013; Rafter, 1990). However, as
is true for women in the labor market, women in prison were often treated differently
because of their race. This differential treatment has been explained through the idea
of “controlling images” or views of inmates based on gender and race (Collins, 2000).
For example, a view of African American women as asexual Mammies is one type of
controlling image for them (Collins, 2000). The use of controlling images is especially
prominent for women prisoners in the old Southern prison leasing system. In this sys-
tem, White women were given domestic tasks inside the home/plantation, though
Black women were forced out into the fields to work alongside men (both White and
Black; LeFlouria, 2011; Rafter, 1990). Black women were also expected to perform
jobs such as mining, turpentine production, blacksmithing, machine operation, and
some domestic work, and they were subject to working on chain gangs, a punishment
that was also likely for White and Black men, but rarely, if ever, applied to White
women (LeFlouria, 2011). Hence, the history of differential treatment for women due
to race is long standing within the correctional field. Even more recently, when com-
pared with men, women tend to work in more feminine assignments such as facility
services or laundry (Morash et al., 1994; Rafter, 1990); while this more recent com-
parison of prison work has typically focused more on gender differences than gen-
dered and racial differences, it indicates that prison work may still be influenced by
stereotypical views of women. More specifically, given the current literature on the
labor force, it may be assumed that these views of women may have a racialized lens.
Men and Labor
Similar to women, the labor field for men seems to be divided both by gender and race.
While women are expected to work in labor fields that emphasize their nurturing and
passive behaviors, men are stereotypically assumed to be more capable of hard labor
and tasks that require trained skill sets (Goffman, 1977). Additionally, men, particu-
larly White men, have always had access to the public sphere (Furnham & Mak, 1999;
Goffman, 1977), which allows them to complete such labor. As noted, work for men
also seems to be divided along racial lines. For instance, White men are more apt to be
in a professional field and are more likely to receive good blue collar jobs (Royster,
2007) compared with minority males. Even in low-wage jobs, research indicates that
White men hold an advantage over other men (Holzer, Raphael, & Stoll, 2006; Pager,
Western, Bonikowski, 2009; Royster, 2007). The discussion of low-wage jobs is of
particular importance for this research, because this is the type of labor that is more
available to prisoners once they have been released from prison (Pager et al., 2009).
Studies examining low-wage labor have shown that not only are White men without
criminal records at an advantage, White men who have been previously incarcerated
are just as likely as men of color with no criminal record to gain employment in these
jobs (Pager et al., 2009; Royster, 2007), and Latinos are somewhat more apt to obtain
these jobs than Black males. When minority males, both with and without criminal
records, do obtain low-wage jobs, they are typically pushed into positions where they
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Crittenden et al. 5
have limited contact with the public and require more manual labor (Pager et al.,
2009). Studies have indicated that one reason minority males, particularly Black
males, are less likely to be hired and more likely to be pushed to “the back of the
house” is that employers may assume that young Black men are felons, lazy, or dan-
gerous (Browne & Misra, 2003; Holzer et al., 2006). In fact, when employers conduct
background checks, they are more likely to hire Black candidates than when they do
not, thus furthering the stereotypical argument (Holzer et al., 2006). Finally, while
Black males appear to be at the bottom of the labor hierarchy for men, it seems that
they are also less likely than Black women to be considered for positions (Holzer
et al., 2006). Labor prospects for minority males, and Black males in particular, seem
to be very much racialized and gendered with them performing tasks that are out of the
public eye and require manual labor.
Regarding men and prison labor, there is a dearth of research examining the racial-
ized nature of it. Typically, studies focusing on prison labor compare men and women
(Morash et al., 1994), or discuss the ethics of forcing inmates to do work in prison
(Davis, 1997; Thompson, 2011). Davis (1997) has even likened the use of prisoner
labor to slavery, because inmates cannot demand rights or unionize. Historically, we
know that in the South, the prison leasing system was quickly developed after the Civil
War and inmates replaced slave labor (Johnson, 2000). These prisons were overpopu-
lated with Black males and females who had short life expectancies due to the egre-
gious conditions (Johnson, 2000; LeBaron, 2012). Again, as is the case with women,
more recent literature examining differences in work assignments has tended to focus
on gender rather than race and gender. For example, Morash and colleagues (1994)
noted that a higher proportion of men had work assignments involving farming and
forestry and maintenance and repair. However, they failed to note differences between
men of different races. Considering the extant research noting a racialized treatment of
men in the general labor force, an examination of prison labor assignments is essential
to understand if this differential treatment of men extends into correctional treatment.
Intersectionality
Over the last several decades, the correctional system has seen a dramatic increase in
the population it supervises, with one of the more rapidly growing incarcerated groups
consisting of women of color (Davis & Shaylor, 2001), while men of color are still
disproportionately represented (Carson, 2015). During this time of rapid expansion,
there has been a significant increase in research conducted examining the field of cor-
rections, yet little of that research has focused on work completed by inmates, espe-
cially on a national-level scale (for an example, see Morash et al., 1994). While the
study by Morash and her colleagues showed that stereotypical practices remained in
how women and men were assigned prison work, it did not examine if involvement in
work varied by race for men and women, or the intersections of race and gender.
Intersectionality in criminology is a growing body of research. Historically, intersec-
tional research has focused on the study of women of color (Browne & Misra, 2003;
Burgess-Proctor, 2006). Such research has noted that not only are there gendered
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6 Feminist Criminology
stereotypes, but that there are racialized and gendered stereotypical views, frequently
referred to as “controlling images” (Collins, 2000). For instance, White women have
typically been viewed in our society as passive and weak, whereas Black women have
been stereotyped as asexual Mammies and promiscuous Jezebels (Browne & Misra,
2003). Further, Black men have a long history of being and are still today stereotyped
as criminal (Barak, Leighton, Cotton, 2015; Browne & Misra, 2003; Holzer et al.,
2006), whereas White men are typically considered the norm in society (Barak,
Leighton, & Flavin, 2010). It is important to understand that our views of individuals
are not only based on gender or race, but are conditioned by both gender and race in
complex ways. Studies that examine race but ignore gender are insufficient in under-
standing the lives of women of color, and studies that explore gender but ignore race are
incomplete because they typically are describing the patterns of White men and women
(Browne & Misra, 2003). Additionally, most intersectional research has focused on
women of color; however, Browne and Misra (2003) note that “a consideration of inter-
sections of race and gender also needs to move beyond a focus on women of color and
pay attention to intersections for all groups” (p. 507). Therefore, more studies need to
be done examining how both gender and race affect treatments of individuals.
The current study examines the nature of work assignments in state correctional
facilities using this type of intersectional approach. Specifically, the current study
looks at whether or not certain types of inmates are participating in particular kinds of
work assignments based on traditional gender-role and racial expectations. Thus, we
are examining work areas based on the intersection of both inmate race and gender. We
consider several types of prison work assignments using the categorization from
Flanagan (1989): prison industry, institutional maintenance or service tasks, and agri-
culture. We do this because these assignments comprise the vast majority of work for
inmates within prison, so most facilities should offer such work. Many of the assign-
ments within these categorizations have been used in stereotypical treatment in the
past. Additionally, there are several assignments examined that may promote narrowly
defined gendered and racialized roles. For the current article, we specifically addressed
the following research question: Are men and women of different races involved in
certain work assignments, and are these differences informed by gender and racial
stereotypes?
Methods
Data
The primary sources of data for the analysis came from the 2004 Survey of Inmates in
State and Federal Correctional Facilities (hereafter referred to as the Survey)1 and the
2005 Census of State and Federal Adult Correctional Facilities (hereafter referred to
as the Census).2 The sample for the Survey was selected through a two-stage process.
Correctional facilities were selected in the first stage, whereas in the second stage
inmates housed within selected facilities were selected. As our interest is in state facili-
ties only, federal prisons were excluded.3 Additionally, given our focus on gender, we
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Crittenden et al. 7
did not include individuals who were housed in coed facilities, only inmates who were
housed in male only or female only institutions were included. This process resulted in
a total sample of 287 facilities and 14,042 respondents (951 women, 13,091 men).
Data for the Survey were gathered through computer-assisted personal interviews that
lasted approximately 1 hr and collected information on each inmate’s individual char-
acteristics and background, prior treatments, and prison life. The data were collected
between October 2003 and May 2004.4 Data from the Census provided facility-level
factors that might influence work assignments. The Survey and the Census were linked
through a common facility identification number.5 The 2000 enumeration of the
Census served as the sampling frame for the correctional facilities whose inmates were
included in the Survey. However, comparative regression model diagnostics indicated
that the 2005 enumeration provided more reliable results; therefore, this enumeration
was used for measuring facility-level control variables.
Measures
Outcome measures. The work assignments examined were chosen based on several
criteria. First and foremost, work assignments were selected for the study from those
that appeared and were consistently defined in both the Survey and Census (i.e., Cen-
sus data were used as controls for availability of work at the facility level). According
to previous research, most work assignments can be grouped into three principle activ-
ities: prison industry, institutional maintenance or service tasks, and agriculture (Fla-
nagan, 1989). Therefore, we examined programming within each of these groups,
which contained many types of programming that literature has identified as possibly
stereotypical based on race and gender. Each prison work assignment was coded as a
dichotomous indicator of participation (0 = no participation, 1 = participation).
For prison industry assignments, we included goods production and industry
assignments. As shown in Table 1, approximately 3% of males and females indicated
working in prison industries. Several work assignments were included under institu-
tional maintenance or service tasks, such as janitorial work, ground work and road
maintenance, food work and preparation, laundry, and maintenance or repair and con-
struction work. We examined two separate domains under institutional maintenance or
service tasks: facility services and public works. These categories were chosen for two
reasons. First, the Census defined institutional tasks into public works and facility
services, and second, these could be considered masculine and mostly feminine,
respectively. Facility services included janitorial services, food preparation, laundry,
and maintenance work. Thirty-seven percent of male and 41% of female inmates
reported being assigned this type of work. Public works included grounds work and
road maintenance and approximately 8% of male and 7% of female inmates were
assigned these tasks. Agriculture assignments involved work in farming, forestry, or
ranching. These were the least commonly reported assignments with only about 2% of
both male and female inmates being assigned this type of work. Whether or not inmates
were paid for their work was also examined, and approximately 38% of men and 33%
of women received payment for their labor.
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8 Feminist Criminology
Table 1. Descriptive Statistics for Variables.
Name
Male (n = 11,210) Female (n = 2,930)
Description% yes % no % yes % no
Dependent variables
Prison industries 3.2 95.3 2.7 95.6 0 = no; 1 = yes
Facility services 37.3 61.3 40.6 57.7 0 = no; 1 = yes
Public works 7.9 90.7 6.6 91.7 0 = no; 1 = yes
Agriculture 2.3 96.2 1.7 96.7 0 = no; 1 = yes
Paid for work 37.5 62.5 33.3 64.9 0 = no; 1 = yes
Independent variables
Level 1
Race
White 44.8 55.2 52.3 47.7
Black 43.1 56.9 36.4 63.6
Other 12.1 87.9 11.3 88.7
Age (M/SD) 35.39 (10.69) 35.46 (9.31) Age in years
Job history 73.5 26.5 58.2 41.8 1 = employed prior to
incarceration
Criminal history
(M/SD)
1.56 (2.89) 1.19 (2.87) # of prior incarcerations
Current offense
Violent 48.7 50.0 28.2 70.7
Property 18.0 80.7 28.5 70.5
Drug 20.7 77.9 31.8 67.1
Other 11.3 87.4 10.4 88.6
Time served (M/SD) 51.41 (63.31) 26.74 (40.95) Time served in months
Rules violations 51.2 47.0 43.0 55.0 1 = at least 1 violation
Level 2 N = 207 N = 57 Facilities
Work availability
Prison industries 61.5 38.5 65.9 34.1 0 = no; 1 = yes
Facility services 94.4 5.6 97.6 2.4 0 = no; 1 = yes
Public works 48.7 51.3 61.0 39.0 0 = no; 1 = yes
Agriculture 28.7 71.3 22.0 78.0 0 = no; 1 = yes
Size (M/SD) 799.12 (987.36) 972.93 (1,324.00) Total inmate count
Region
South 42.6 57.4 51.2 48.8 0 = no; 1 = yes
West 20.0 80.0 14.6 85.4 0 = no; 1 = yes
Midwest 21.0 79.0 17.1 82.9 0 = no; 1 = yes
Northeast 16.4 83.6 17.1 82.9 0 = no; 1 = yes
Security level
Minimum 14.9 85.1 17.1 82.9 0 = no; 1 = yes
Medium 45.1 54.9 34.1 65.9 0 = no; 1 = yes
Maximum 40.0 60.0 48.8 51.2 0 = no; 1 = yes
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Crittenden et al. 9
Independent variables. For this study, there were two primary independent variables of
interest: gender and race. The vast majority of inmates in this sample were male
(11,210 or 93%). Race was measured using inmates’ self-reports of their racial cate-
gory being White, Black, or Other. Whites comprised the largest percentage for both
males and females (45% and 52%, respectively), and were also used as the reference
category in this analysis as shown in Table 1. Inmate age ranged from 16 to 84 years,
and the average age was approximately the same for both men and women (35 years).
Additionally, several control measures were included both at the individual- and
facility level including current confinement information, background information,
offense type, and facility characteristics. Previous literature has indicated that these
factors might influence access to work assignments (National Institute of Corrections,
1992). Several variables involving inmates’ backgrounds and current confinement
characteristics were examined as prisoners with serious criminal histories (i.e., longer
histories, violent offenses) might be limited in their work assignments either by being
allowed to work in general, or by being excluded from certain assignments (i.e., off-
site, less supervised work). Criminal history was a measure calculated as the number
of times an inmate had been incarcerated, excluding his/her current incarceration.
Male inmates were previously incarcerated 1.56 times on average, whereas female
inmates were previously incarcerated 1.19 times on average. Current offense indicated
whether or not the inmate was serving time for a violent, property, drug, or some other
type of crime6 (i.e., escape, parole violation, public disorder), with property offense
serving as the reference category. Approximately 49% of male and 28% of female
inmates were incarcerated for a violent offense, 18% of male and 29% of female
inmates for a property offense, 21% of male and 32% of female inmates for a drug
offense, and 11% of men and 10% of women were incarcerated for some other type of
offense. Time served represents the calculation of the difference between the inmates’
responses to their admission date to prison (month, date, and year of admission) and
the date that they were surveyed and was measured in terms of months served. The
average time served was 51 months for men and 27 months for women. Rules viola-
tions was measured through the inmates’ self-reports of any rules that were violated or
whether they had been charged by the corrections systems with violating rules during
their incarceration. A little over half of the male inmates (51%) and 43% of female
inmates reported that they had violated rules and/or been charged with violating rules.
Finally, several facility-level measures were included using the data from the 2005
Census: these are work availability, security level, location, and size. Work availability
indicated whether specific work assignments were offered in the facility in which the
inmates were housed (i.e., prison industries, facility services, public works, agricul-
ture). The most commonly offered assignment was facility services with 94% of male
and 98% of female facilities having these tasks, followed by prison industries (61.5%
male, 65.9% female), public works (48.7% male, 61.0% female), and finally agricul-
ture (28.7% male, 22.0% female). Security level indicated the level of security reported
by the facility. The largest percentage of male facilities were medium security (45.1%),
whereas the largest percentage of female facilities were maximum security (48.8%).
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10 Feminist Criminology
Location signified the region of the country where inmates were housed (U.S. Census
regional designation) with the largest percentage of both male and female facilities
being located in the south, and size represented the number of inmates housed in each
facility. The average size of male facilities was 799 whereas for female facilities the
average was 973 inmates.
Analytic Plan
To closely examine how gender and race affect work assignments, several types of
analyses were conducted. First, descriptive and bivariate analysis was used to see how
men and women were assigned to work using SPSS 23. Next, we utilized hierarchical
linear modeling (HLM 7.0) to examine the work assignments for inmates who were
nested within correctional facilities. HLM is designed to account for the shared vari-
ance between the two levels of data (inmate- and facility level) because it takes within-
and between-group regressions into account (Woltman, Feldstain, MacKay, & Rocchi,
2012). Male inmates and female inmates were examined separately, due to the nature
of the research question. For the first phase of our analyses, we examined the uncon-
strained (null) model to determine the amount of variance explained by facility-level
measures to ensure the necessity of using HLM. The results of these models indicated
that there was a significant variation in our work assignments across facilities. Next,
since our outcomes are dichotomous, we used hierarchical Bernoulli modeling in a
random coefficients model to examine the effects of our Level 1 and level 2 variables,
which indicated significant variations in our Level 1 variables with reasonable reli-
abilities. This study was mainly interested in the impact of inmates’ gender and race on
their work assignments; therefore, we focused on Level 1 predictors while controlling
for Level 2 (facility) variables. Due to the nature of our focus, we centered the Level
1 variables around the group mean and the availability of the assignment at Level 2
around the grand mean which reduces the likelihood of finding spurious effects at
Level 1 (Hox, 2010; Raudenbush & Bryk, 2002; Steiner & Wooldredge, 2015;
Woltman et al., 2012).
Findings
Bivariate Analysis
For the first set of analyses (see Table 2), work assignments by race were examined
separately for men and women prisoners using a chi-square analysis. The bivariate
analysis yielded notable results, mainly for males. The chi-square analysis did not
show any significant association between each of the work assignments and race for
women prisoners. It did however show a significant result for being paid for work by
race, with the highest percentage of women who were paid being a race other than
White or Black (41.4%) followed by White women (34.3%), and Black women (31%).
For men, many of the work assignments significantly differed according to inmate
race in the bivariate analysis. Interestingly, a significantly lower percentage of Black
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Crittenden et al. 11
men indicated working in prison industries. However, a significantly higher percent-
age of Black men (41.2%) reported working in facility services, compared with their
White (35.3%) and Other race (35.1%) counterparts. A slightly higher but significantly
different percentage of White men reported being assigned to public works (8.6%),
whereas 7.8% of Black men (7.8%) and men of Other races (6.5%) reported such
assignments. Men of a race other than White or Black also reported the lowest partici-
pation in agricultural assignments (i.e., farming, forestry, or ranching). For men, being
paid for work was fairly evenly distributed with approximately 38% of all men indi-
cating they were paid for their labor.
Hierarchical Linear Analysis
Prison industry. In the current portion of the analysis, we use Hierarchical Bernoulli
regression to examine the impact of inmate gender and race on their involvement in
particular types of work assignments including prison industry, institutional mainte-
nance or service tasks, and agriculture, controlling for individual and facility-level
measures (Raudenbush & Bryk, 2002). As noted in Table 3, while there were several
significant Level 1 and Level 2 effects on working in prison industries for both males
and females, race was not significant for either gender. At Level 1 for women, serving
time for a violent or drug offense significantly raised the odds of working in prison
industries compared with those serving time for a property offense. Also, as the age of
the female inmate increased, so did the odds of working in prison industries. As
expected, the Level 2 factor of whether or not the facility offered prison industry
assignments significantly increased the odds of participation for women; however, no
other facility-level factor did. For men, having a job in the 12 months prior to incar-
ceration significantly increased the odds of participation as did increased amounts of
Table 2. Work Assignments by Race for Male and Female Inmates.
% White % Black % other χ2Cramer’s V
Male inmates (n = 11,051)
Prison industries 3.7 2.8 3.6 7.534* 0.026*
Facility services 35.3 41.2 35.1 40.642*** 0.061***
Public works 8.6 7.8 6.5 7.430* 0.026*
Agriculture 2.1 2.8 1.8 6.671* 0.025*
Paid for Work 37.5 37.3 38.2 0.381 0.006
Female inmates (n = 2,882)
Prison industries 2.9 2.7 2.5 0.252 0.009
Facility services 39.4 43.3 44.0 4.917 0.041
Public works 7.2 5.9 7.1 1.706 0.024
Agriculture 1.8 1.5 2.2 0.631 0.015
Paid for work 34.3 31.2 41.4 11.617** 0.064***
*p < .05. **p < .01. ***p < .001.
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12 Feminist Criminology
time served and age. Additionally, men convicted of a violent offense compared with
a property offense had increased odds of participating in prison industries. Similar to
women, whether or not the facility offered prison industries significantly impacted
participation as did medium and maximum security levels. Inmates in these facilities,
compared with minimum security facilities, had increased odds of participation in
prison industries.
Institutional maintenance or service tasks. There were several significant Level 1 and
Level 2 effects on working in facility services for males and females as shown in
Table 4. For women, identifying as a race other than White or Black significantly
increased the odds of participating in a facility services assignment, when compared
Table 3. Hierarchical Bernoulli Regression of Prison Industries.
Males
β (SD)
Females
β (SD)
Level 1 factors
Intercept 0.53 (0.13)*** 0.50 (0.26)***
Whitea
Black −0.06 (0.12) 0.14 (0.25)
Other 0.06 (0.16) −0.61 (0.41)
Age 0.02 (0.00)** 0.05 (0.01)***
Job history 0.20 (0.13)* −0.06 (0.23)
Rules violation 0.01 (0.13) 0.21 (0.34)
Criminal history −0.01 (0.03) −0.11 (0.07)
Time served 0.00 (0.00)* 0.00 (0.00)
Property offensea
Violent offense 0.38 (0.16)* 0.92 (0.36)*
Drug offense 0.08 (0.20) 0.53 (0.26)*
Other offense −0.27 (0.21) 0.17 (0.42)
Level 2 factors
Intercept −3.79 (0.10)*** −3.82 (0.18)***
Work availability 1.40 (0.25)*** 1.02 (0.50)*
Size −0.00 (0.00) 0.00 (0.00)
Southa
West −0.09 (0.20) 0.22 (0.46)
Midwest −0.21 (0.21) −0.35 (0.37)
Northeast 0.14 (0.21) 0.06 (0.33)
Minimuma
Medium 1.60 (0.23)*** −0.08 (0.55)
Maximum 1.56 (0.29)*** 0.00 (0.53)
n9,504 2,298
aReference category.
*p < .05. **p < .01. ***p < .001.
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Crittenden et al. 13
with White women. No significant differences were found between Black women and
White women, and therefore their odds of working in facility support services were
similar to one another. No other Level 1 factors were significantly related to facility
service assignments for women. The prison security level was the only facility-level
measure that influenced female participation in facility services with inmates in both
medium and maximum security level prisons having a decreased odds of participation.
Race was significant for males as well, with Black men having significantly higher
odds of being assigned to facility services than White men. Other Level 1 factors for
Table 4. Hierarchical Bernoulli Regression of Institutional Maintenance or Service Tasks.
Facility services
males
β (SD)
Facility services
females
β (SD)
Public works
males
β (SD)
Public works
females
β (SD)
Level 1 factors
Intercept 0.31 (0.04)*** 0.01 (0.00)*** 0.73 (0.11)*** 0.21 (0.12)***
Whitea
Black 0.20 (0.05)*** 0.02 (0.02) −0.23 (0.07)*** −0.07 (0.15)
Other 0.06 (0.08) 0.08 (0.04)* −0.28 (0.12)* −0.11 (0.26)
Age 0.01 (0.00)*** −0.00 (0.00) −0.01 (0.00)* 0.00 (0.01)
Job history 0.18 (0.05)*** 0.03 (0.02) 0.11 (0.09) −0.19 (0.18)
Rules violation 0.02 (0.05) 0.04 (0.03) 0.19 (0.08)* 0.38 (0.18)*
Criminal history 0.01 (0.01) 0.00 (0.00) −0.06 (0.02)*** 0.01 (0.04)
Time served 0.00 (0.00) −0.00 (0.00) −0.00 (0.00)* −0.00 (0.00)
Property offensea
Violent
offense
0.10 (0.07) 0.01 (0.03) −0.34 (0.11)** −0.20 (0.23)
Drug offense 0.01 (0.07) −0.00 (0.03) 0.09 (0.11) 0.04 (0.20)
Other
offense
−0.01 (0.08) 0.03 (0.05) 0.05 (0.15) 0.21 (0.34)
Level 2 factors
Intercept −0.52 (0.04)*** 0.43 (0.02)*** −2.61 (0.08)*** −2.83 (0.11)***
Work
availability
0.10 (0.18) −0.07 (0.18) 0.11 (0.18) 0.80 (0.21)***
Size −0.00 (0.00) 0.00 (0.00) 0.00 (0.00)** 0.00 (0.00)*
Southa
West −0.63 (0.11)*** −0.06 (0.06) −0.96 (0.21)*** −0.78 (0.34)*
Midwest −0.06 (0.13) −0.01 (0.05) −0.64 (0.24)** −0.96 (0.33)**
Northeast 0.04 (0.11) 0.06 (0.04) −0.90 (0.19)*** −1.01 (0.30)**
Minimuma
Medium −0.09 (0.13) −0.19 (0.05)*** −0.50 (0.24)* 0.11 (0.38)
Maximum −0.33 (0.14)* −0.18 (0.05)*** −0.42 (0.26) 0.15 (0.23)
n9,504 2,298 9,504 2,298
aReference category.
*p < .05. **p < .01. ***p < .001.
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14 Feminist Criminology
males included job history and increased age, both of which increased the odds of
working in facility services. For men at Level 2, the size of the facility and being in a
maximum-level security facility decreased odds of participation.
As shown in Table 4, several individual and facility-level factors were significantly
related to participation in public works assignments. While race was not a significant
factor for women, it was for men with both Black men and men of other races having
lower odds of participation in public works than White men. Several other individual
factors for men were also significant including rules violations, criminal history, the
time served by the inmate, age of the inmate, and if the inmate was currently incarcer-
ated for a violent offense. For men, facility size increased the odds of participation,
and inmates housed in facilities in the West, Midwest, and Northeast regions had lower
odds of participation than those serving their time in the South. Additionally, men
housed in medium security facilities were less likely than those in minimum security
facilities to report assignments to public works. For women, only one Level 1 measure
was significantly related to participation: rules violations. Women with reported rules
violations had higher odds of being assigned to public works than those without.
Regarding Level 2 measures, women housed in prisons with available public works
assignments, as expected, and women in larger prison facilities increased the odds of
participation. Compared with facilities in the South, inmates in facilities located in the
West, Midwest, and Northeast regions had lower odds of being assigned to public
works.
Agriculture. As noted in Table 5, the race of men and women did not significantly
impact participation in agricultural assignments. For women, there were no individ-
ual-level factors that were significantly related to participation in these assignments,
and only two significant Level 2 factors. These two factors were facility size and as
expected work availability. Both of these factors increased the odds of participation.
For men, their increased age decreased odds of participation, but those convicted of a
drug offense had increased odds of participation compared with men convicted for a
property offense. At Level 2, availability of agricultural assignments was significantly
related to participation as well. Additionally, men housed in the South had signifi-
cantly higher odds than those in any other region of completing this assignment.
Finally, men housed in maximum-level security facilities were less likely to report
participation in agricultural assignments than those in minimum security.
Being paid for work. Finally, we examined whether men and women of varying races
were paid differently for their work (see Table 6). For both men and women, several
individual- and facility-level factors were related to being paid; however, inmate race
had a minimal impact on the odds of being paid. Men identifying as a race other than
White or Black had significantly reduced odds of being paid than White men. Other
significant factors related to being paid for men included age, employment prior to
incarceration, the length of time served, and being incarcerated for a violent offense.
All of these factors increased the odds of men being paid. For women, age and the
amount of time served significantly increased odds of being paid for their work
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Crittenden et al. 15
assignment at the individual level. At Level 2 for men and women, the location of the
facility was related to being paid, with facilities in the south having lower odds of
inmates being paid than any other region in the country.
Discussion
In the current study, we considered whether gender and race influence involvement in
prison work by examining three categories of work assignments found in prisons
across the United States, which did include some tasks that have historically been
related to either racial or gendered stereotypical treatment. First, we looked at bivari-
ate relationships between each work assignment and race separately for both male and
Table 5. Hierarchical Bernoulli Regression of Agricultural Assignments.
Males
β (SD)
Females
β (SD)
Level 1 factors
Intercept 1.78 (0.38)*** 1.14 (0.58)***
Whitea
Black 0.01 (0.12) −0.35 (0.38)
Other 0.02 (0.18) −0.26 (0.34)
Age −0.03 (0.00)*** −0.01 (0.01)
Job history 0.03 (0.12) 0.29 (0.18)
Rules violation −0.07 (0.10) 0.36 (0.30)
Criminal history −0.04 (0.03) −0.04 (0.03)
Time served 0.00 (0.00) −0.00 (0.00)
Property offensea
Violent offense −0.19 (0.15) −0.17 (0.37)
Drug offense 0.37 (0.16) −0.08 (0.28)
Other offense 0.26 (0.23) 0.14 (0.36)
Level 2 factors
Intercept −4.27 (0.11)*** −4.56 (0.29)***
Work availability 1.48 (0.20)*** 1.90 (0.52)***
Size −0.00 (0.00) 0.00 (0.00)**
Southa
West −1.27 (0.24)*** 1.14 (0.62)
Midwest −1.19 (0.22)*** −1.07 (0.63)
Northeast −1.14 (0.31)*** 0.22 (0.75)
Minimuma
Medium −0.16 (0.37) −0.51 (0.53)
Maximum −0.89 (0.36)* 0.39 (0.54)
n9,504 2,298
aReference category.
*p < .05. **p < .01. ***p < .001.
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16 Feminist Criminology
female inmates. We found that while there was only one significant relationship
between work and race for women (being paid for work), there were several signifi-
cant relationships for men by race in the following types of work: prison industries,
facility services, public works, and agriculture work. Specifically, Black men repre-
sented the highest percentage of men participating in agriculture and facility services
assignments, while a higher percentage of White men worked in public works and
prison industries.
To better explore the relationships between gender, race, and participation in prison
work, we conducted multilevel modeling to control for possible facility-level influ-
ences on assignments for inmates to prison industry, institutional maintenance or ser-
vice tasks, and agriculture work. We were interested in the extent to which these
assignments might be informed or related to gender and racial stereotypes. In this
Table 6. Hierarchical Bernoulli Regression of Being Paid for Work.
Males
β (SD)
Females
β (SD)
Level 1 factors
Intercept 3.17 (0.35)*** 3.69 (0.82)***
Whitea
Black −0.06 (0.06) −0.13 (0.12)
Other −0.19 (0.07)* −0.08 (0.18)
Age 0.01 (0.00)*** 0.01 (0.00)*
Job history 0.29 (0.05)*** 0.12 (0.09)
Rules violation 0.05 (0.06) −0.05 (0.11)
Criminal history −0.01 (0.01) −0.01 (0.02)
Time served 0.00 (0.00)*** 0.01 (0.00)**
Property offensea
Violent offense 0.13 (0.06)* 0.23 (0.12)
Drug offense 0.00 (0.07) 0.03 (0.13)
Other offense −0.09 (0.08) 0.22 (0.13)
Level 2 factors
Intercept −0.59 (0.11)*** −0.60 (0.25)*
Size −0.00 (0.00)** −0.00 (0.00)
Southa
West 0.65 (0.29)* 1.48 (0.61)*
Midwest 1.60 (0.28)*** 2.34 (0.50)***
Northeast 1.84 (0.30)*** 2.51 (0.48)***
Minimuma
Medium 0.11 (0.37) −1.21 (0.61)
Maximum −0.71 (0.39) −0.51 (0.65)
n9,454 2,295
aReference category.
*p < .05. **p < .01. ***p < .001.
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Crittenden et al. 17
regard, we found notable differences in work assignments for men and women by race.
One way we explored gendered expectations of inmates was through the work assign-
ments we examined. Facility support services might be indicative of mostly “femi-
nine” work because these tasks included food preparation, janitorial services (i.e.,
cleaning), laundry, and low-skilled maintenance. Historically, women prisoners, par-
ticularly White women, were assigned to more “domestic” oriented tasks (Franklin,
2008; Grana, 2010; Lee, 2000; Morash et al., 1994). Our descriptive analysis indicates
that women reported higher levels of participation in these types of work compared
with their male counterparts. Public works included ground work or road maintenance
which could be viewed as more “masculine” type work because it involves tasks that
take place outdoors and requires more manual skills. In fact, men in our sample
reported higher levels of participation than women in these assignments and agricul-
tural assignments as well—other outdoor assignments requiring manual labor. Our
descriptive findings, at the very least, demonstrate a fit with stereotypical behavior for
men, who have long been deemed as more capable of skilled and labor-based tasks
(Goffman, 1977).
When examining how race and gender intersect to influence assignment to prison
work, we found significant differences by race especially for male inmates. Black men
and men identifying as a race other than White or Black were less likely to be assigned
to public works (e.g., grounds work and road maintenance) than White men. This par-
ticular result is indicative of literature concerning labor divisions in general society
which finds that even in low-wage jobs, White men hold an advantage over other men
(Holzer et al., 2006; Pager et al., 2009; Royster, 2007). The finding that Black men are
more apt to work in facility services (or more menial tasks) also parallels studies
examining the general population labor division which indicate that men of color,
particularly Black men, are more likely to be pushed to “the back of the house” (Pager
et al., 2009), or in tasks where they will have little contact with the public.
Another notable finding in our multivariate analysis was that men who identified as
a race other than White or Black were less likely than White men to be paid for their
work assignment. Again, this may point to privilege for White male inmates, espe-
cially when coupled with our other findings that White men are more likely to be
assigned to public works and less likely to work in facility services. On a positive note,
our multilevel analysis failed to find race differences for male inmates (or female
inmates) and their assignment to prison industries. Instead, it would appear that all
inmates regardless of race have access to this type of work and the skills these assign-
ments might provide to prisoners. Skills gained from working in prison industries are
generally important and are likely to be useful to both female and male inmates who
are reentering the community after being incarcerated and looking for employment.
For women, the only significant relationship found in the multilevel analysis was
for facility services where women who identified as a race other than White or Black
were more likely than White women to participate in these types of jobs. This finding
corresponds with general labor studies which indicate that even in feminized labor,
there are divisions based on race (Browne & Misra, 2003; Duffy, 2011), and when this
occurs women of color are more likely to have “dirty work” or cleaning, laundry, and
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18 Feminist Criminology
food services (Duffy, 2011), or what is referred to in the current study as facility ser-
vices. The fact that our analysis found no other significant differences for women
regarding work assignments is interesting because historically, Black women have
been more likely to be assigned to work that might require hard labor than White
women (LeFlouria, 2011; Rafter, 1990). Therefore, it may be that divisions among
women due to race are decreasing, or at least decreasing in the types of work they are
assigned.
It is particularly remarkable that in our current study we found a more pronounced
division of labor by race for men than women, especially given the lack of attention
that men have received in the literature on prison work. This literature has primarily
focused on different types of work for women, especially in the South where Black
women were expected to perform jobs that included hard labor and potential danger
(LeFlouria, 2011; Rafter, 1990). Even in these prison systems, when men’s work was
described, there was an astonishing lack of variance, most men were assigned to hard
labor (LeFlouria, 2011). Still, the differences for men in our study seemingly mirror
differences in labor for the general population (Pager et al., 2009). Labor literature has
acknowledged that Black women have more of an advantage in the job market than
Black men (Holzer et al., 2006). This may be a reason why we found racial differences
for men but not women. Race may be more influential for men than women when it
comes to privileges of race—particularly in prison.
The distinctions for men may also be more pronounced because of the type of
assignments men tend to be working, particularly where they may be working (“in” vs.
“out” of prison). For instance, a larger percentage of men on average than women
work in public works. With more men working in these types of assignments, there
may be more discretion as to who fills these roles. Our findings seem to indicate that
White men are being put in these assignments, while Black men are being relegated to
tasks such as janitorial work and food preparation much like women. This could have
major impacts on inmates once they are released, considering the limited amount of
positions that are available to felons. Exposure to particular types of work and skills
that are valuable or marketable is limited in the prison setting, so being assigned to
certain work may be more advantageous to offenders once they are released back into
the community. If White men are working in assignments in prison that may lead to
better occupational options once released, this puts Black men in particular at a severe
disadvantage, especially considering that literature notes that White men with records
may be more likely to obtain a job than Black men without criminal histories to begin
with (Holzer et al., 2006).
Literature for women’s labor in general society indicates than in nurturing or
domestic work settings, White women tend to have more professional positions. For
example, in nursing homes, White women tend to be nurses while women of color
tend to work “dirty jobs” or those requiring cleaning (Browne & Misra, 2003; Duffy,
2011). Yet, in prison, these possible differences based on race may not occur because
there is not as much of a distinction between professional and unskilled work within
the prison setting. Therefore, it may be that all women prisoners are seen as capable of
completing these work assignments. Many women in prison, regardless of race, come
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Crittenden et al. 19
from lower socioeconomic statuses, so they are typically not coming from profes-
sional positions in the workforce. Indeed, many of the women in our sample were not
employed in the 12 months prior to incarceration (42%). This lack of class differential
and increased unemployment may be another reason why we saw a lack of distinction
for women in these more service related fields.
Given the continued importance of gender and race in the punishment and rehabili-
tation of prisoners in the United States, the purpose of the current study was to exam-
ine the possible influence of gender and race on inmate participation in prison work.
All prisons have some level of work assignments, whether inmates are working in jobs
to keep the prison operating (e.g., laundry, food service, etc.), or working in industries
learning skills and producing goods, or enduring long hours farming the fields and
growing crops, or working in the public areas maintaining roads and parks. A limited
number of state inmates receive opportunities to learn a new trade or participate in job
training programs; instead, for a larger number of inmates their only exposure to work-
ing and obtaining new skills comes in the form of prison work assignments. Future
research needs to be conducted to better understand how these limited resources are
used within the prison setting, based on race and gender.
In terms of data, it would be extremely beneficial if national data sets such as the
Survey and Census used in our study collected more consistent, in-depth information
about prison programming and work-related assignments to understand the types of
skills and experiences inmates are receiving, and how their involvement may or may
not benefit them once they are released into the community and try to successfully
transition back into society. The lack of in-depth information in these national data sets
is one of several limitations in the current study. The data in the Survey and Census
contain information on whether or not inmates were assigned a specific type of work
or if these assignments were utilized by facilities, but not on how long they performed
it or whether or not they had any choice in doing the assigned work. The information
provided in the Census also left us unable to determine the extent to which each of
these assignments were used by facilities, especially regarding how many inmates
were assigned to these types of work, which is why we relied on Survey information
to gauge the scope of work assignments within these institutions. It may be beneficial
for future research to examine prison work using individual facilities as the unit of
analysis to better understand how facilities utilize work assignments and if they assign
inmates differently within not only individual institutions, but also at the state level, a
level we know may have significant impacts on work and other programming.
Additionally, our data were cross-sectional; therefore, we do not know if the assign-
ment they reported working at the time of data collection was the only assignment they
ever worked.
While it is understandable that certain types of work assignments (i.e., facility ser-
vices) are more common because they increase the functioning of the correctional
facility and can help inmates learn the general attributes of being a good employee, the
consequences of learning these limited types of skills can limit inmates in their search
for gainful employment outside of prison (Solomon, Johnson, Travis, & McBride,
2004). This is particularly notable because of our findings that Black men are more
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20 Feminist Criminology
likely to be assigned these roles. The barriers or challenges to finding stable and long-
term employment for ex-prisoners and those still under community corrections super-
vision are well documented in the literature (Duwe, 2015; Solomon et al., 2004;
Visher, Debus-Sherrill, & Yahner, 2011). A 2004 report by the Urban Institute notes,
There is a missed opportunity to expand the skills sets and employment prospects of
prisoners during incarceration. If individuals emerged from prison with fortified skill
sets, solid work experience, and connections to legitimate jobs at market wages—wholly
better prepared to be more productive than when they entered prison—the prospects for
positive outcomes in terms of earnings, family support, self-esteem, and recidivism could
potentially offset the potential harms that a criminal record and limited skills might pose.
(Solomon et al., 2004, p. 6)
Our findings mirror this concern and the few skills inmates are acquiring may be a
result of being assigned to work during their incarceration that are being influenced by
both gender and racial stereotypes.
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.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of
this article.
Notes
1. U.S. Department of Justice, Bureau of Justice Statistics (2004).
2. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics (2005).
3. In the first stage, correctional facilities were separated into two sampling frames by gender
based on the universe sampling frame provided by the 2000 Census. Coed facilities were
included in both sampling frames and the final sampling frame included 1,401 male and
357 female facilities. Of these facilities, the 14 largest male and seven largest female facili-
ties were selected with certainty while the remaining facilities were grouped into eight
strata based on the U.S. Census regions. Facilities were then ordered by size of population
within each stratum and selected based on probability proportional size. This resulted in
225 male and 65 female facilities being selected. The Bureau of Justice Statistics then com-
piled information on prisons that had opened between the completion of the 2000 Census
and April 1, 2003 which resulted in 27 male, two female, and seven coed prisons that were
stratified the same as the sample from the Census. This resulted in six male and one female
facilities being added. The total sample size was 287, due to non-responsiveness or missing
data. In the second stage, inmates were selected from prisons by a list provided by the facil-
ity that contained all the inmates using a bed from the previous night. The inmates were
systematically selected from the list using a randomized starting point and predetermined
skip interval which resulted in 13,098 males and 3,054 females being sampled.
4. Due to the nature of data collection, a sampling weight, provided by the Survey, is used in
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Crittenden et al. 21
all analyses that is based on the inverse of each inmate’s chance of selection into the survey
sample and was normalized for the sample size to allow for proper inference back to the
population.
5. The facility identification number in the Census was manually matched to inmates in the
Survey using several identifying variables (i.e., state in which the facility was located,
gender housed in facility, size of facility, etc.).
6. While escapes are notably different from many of the “other” offenses (i.e., parole viola-
tions, public disorders), and the impact of escapes on work assignments may be more simi-
lar to that of violent offenses, we have retained escapes in the category of other because
only 0.21% (n = 30) inmates reported being charged with escape for their current offense.
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Author Biographies
Courtney A. Crittenden is an assistant professor of Criminal Justice in the Social, Cultural,
and Justice Studies Department at the University of Tennessee at Chattanooga. She has previ-
ously published work on gender and correctional programming, women prisoners, consensual
sex faculty/student relationships, and patriarchy. Her current research centers on prison pro-
gramming and how the intersection of social identities influence treatment within criminal
justice.
Barbara A. Koons-Witt is a professor in the Department of Criminology and Criminal Justice
at the University of South Carolina. She has previously published work on gender and correc-
tional programming, gender and sentencing decisions, and on women prisoners. She recently
completed a research project involving interviews with incarcerated mothers, focusing on their
motherhood identity, relationships with their children, and their thoughts about community
reentry. Her current research centers on incarcerated mothers and criminal desistance, prison
programming, and the influence of criminal records on the hiring practices of businesses.
Robert J. Kaminski is an associate professor in the Department of Criminology and Criminal
Justice, University of South Carolina. He earned his PhD from the University at Albany, State
University of New York. His research has appeared in a variety of scholarly journals, including
Criminology, Crime and Delinquency, the Journal of Quantitative Criminology, and Justice
Quarterly.
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