Constructing the Racial Hierarchy of Labor: The Role of
Race in Occupational Prestige Judgments*
Lauren Valentino
, The Ohio State University
Sociologists of culture are interested in processes of valuation, such as the way we
value the division of labor. Typically measured through occupational prestige, prior
research on this topic has largely neglected the potential role of race in the construction
of the status hierarchy. This study asks whether and how race shapes judgments of
occupational prestige, drawing on key insights from the sociology of race and ethnicity
(Whiteness as a credential, strategic assimilation) to test key predictions about racial
composition and a person’s own racial identity in this process. Combining data from the
2012 General Social Survey with federal administrative data, I find that Whiter jobs are,
in fact, seen as more prestigious, even after taking into account an occupation’s level of
required education/training, pay, industry, and gender composition. Further analyses
demonstrate that this pattern is primarily driven by White and Asian raters and by raters
with a college degree. Overall, then, this study indicates that the racial segregation of
occupations impacts not only wages but also the status they confer to their incumbents.
Introduction
A central topic of study in the sociology of culture is “valuation”—how
we make decisions about worth, merit, and value, and how these decisions are
socially mediated (Brekhus and Ignatow 2019; Lamont 2012; Zelizer 2011;
Zuckerman 2012). The fundamentally cultural process of valuation plays a critical role in the (re)production of social inequality and the construction of social
hierarchies (Lamont, Beljean, and Clair 2014). In particular, the way we value
labor and its divisions represents the defining feature of modern social stratification systems (Durkheim 1997; Hechter 1978). Yet, most research on the valuation of labor has focused on its material aspects—namely pay—while
overlooking its symbolic aspects—such as status (Weber 1978).
Sociologists have traditionally measured status by examining an occupation’s prestige—the perceived social standing of an occupation relative to
others. However, much existing research on occupational prestige suffers from
two limiting assumptions about the way people perceive and construct the
occupational hierarchy: the materialist assumption, which presumes that only
an occupation’s requirements and rewards determine where it falls in the hierarchy, and the homogeneity assumption, which presumes that all individuals view
Sociological Inquiry, Vol. 92, No. 2, May 2022, 647–673
© 2021 Alpha Kappa Delta: The International Sociology Honor Society
DOI: 10.1111/soin.12466
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the hierarchy the same way, regardless of their own social identities. Drawing
on core insights from the sociology of race and ethnicity, I seek to challenge
these two assumptions. I then derive and test three predictions about the role of
race in judgments of occupational prestige, revealing how the racial hierarchy
of labor is constructed in the United States.
The prestige of a person’s occupation frames how others interact with
them: the deference they are accorded, the benefit of the doubt they receive,
the authority they can draw upon, and the power they have at their disposal.
Furthermore, the effects of occupational prestige as status extend far beyond
the workplace: occupation-derived status shapes health and well-being
(Fujishiro, Xu, and Gong 2010), civic participation (Sobel 1993), marriage and
family formation (Kalmijn 1994), and interactions with the criminal justice system (Lizotte 1978).1 Thus, it is critically important for social scientists to
understand the individual, micro-level cultural process by which occupational
prestige judgments are made. If race is part and parcel of the way we accord
status to individuals on the basis of their profession, then that micro-level process can further entrench meso- and macro-level patterns of racial disparities in
the contemporary United States.
Challenging the Materialist Assumption
Earlier perspectives on occupational prestige generally presumed that prestige is entirely determined by an occupation’s pay and educational/training
requirement (Bukodi, Dex, and Goldthorpe 2011; Featherman and Hauser
1976; Hauser and Warren 1997; Lin and Xie 1988). This is what I term the
materialist assumption: the notion that only the material factors associated with
a job influence where people place it in the occupational status hierarchy.
Emerging research has instead suggested the importance of non-material factors
in occupational prestige judgments, such as the affective qualities of a job
(Freeland and Hoey 2018; MacKinnon and Langford 1994), an occupation’s
level of authority and autonomy (Zhou 2005), and the gender composition of
an occupation (Valentino 2020).
Race, however, has been largely missing from this picture. This is a surprising oversight given three important dynamics that are often highlighted by
scholars of race and ethnicity: (1) the racial segregation of occupations, (2) the
racialized nature of work, labor, and the occupational structure, and (3) the role
of racial segregation and composition in other types of valuation processes. I
now consider each of these dynamics in turn and their potential role in the construction of the status hierarchy of occupations.
Although occupational racial segregation has declined since the passage of
the 1964 Civil Rights Act which outlawed labor market discrimination, it has
remained stubbornly persistent (Tomaskovic-Devey et al. 2006). As of 1988,
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
649
29.3% of either Black or White workers would need to change jobs in order to
achieve an equitable racial distribution across occupations (King 1992). The
most recent analyses available indicate that Hispanic and Asian workers are
even more likely than African Americans to work in racially segregated jobs
(Alonso-Villar, Del Rio, and Gradin 2012), leading to what some scholars refer
to as “brown-collar occupations”—poorly paid, unreliable jobs in which workers of color are overrepresented (Catanzarite 2000, 2002). Meanwhile, as of
2020, 93.2% of Fortune 500 CEOs are White, a figure that has hardly budged
in the last two decades (Zweigenhaft 2021). Unsurprisingly, then, racial segregation in the labor market is linked to racial inequities in pay (Catanzarite
2000; Huffman and Cohen 2004; Tomaskovic-Devey 1993a). Given the relationship between racially segregated labor and material valuation (e.g., pay),
we might also expect that there is a relationship between racially segregated
labor and symbolic valuation (e.g., prestige).
Furthermore, scholars of race and ethnicity have observed the tendency to
associate certain jobs with particular ethnoracial groups. Maldonado (2006, 2009)
finds that employers in the agriculture industry mentally categorize menial jobs
using race essentialist ideas about Latinos/as and their suitedness for this type of
work. In an audit study, Pager, Western, and Bonikowski (2009) find that
employers steer Black and Latino applicants toward occupations with greater
physical demands and lower customer service components than the ones they initially applied to, a process they term “race-based channeling.” Wingfield and
Alston (2013) find evidence for the existence of “racial tasks,” specific types of
labor that workers of color are often expected to fulfill in the workplace. Alegria
(2019) finds that White women in the tech field are presumed to have strong
social and soft skills, unlike men and women of color, and they are moved into
managerial positions termed “glass step stools.” Given the persistent cultural
associations between type of work and ethnoracial groups, we therefore should
expect race to play a role in the way an occupation is evaluated. As TomaskovicDevey (1993b:6) argued, “the typical sex or race of a class of jobs in workplaces
becomes a fundamental aspect of the jobs, influencing the work done as well as
the organizational evaluation of the worth of the work.” Indeed, Ray (2019) has
theorized that organizations produce and sustain a racialized hierarchy of jobs.
Finally, the role of racial segregation in other processes—such as the valuation of neighborhoods and schools—reveals that racial composition plays a
particularly important role in these judgments. For instance, a large body of
work suggests that the racial composition of a neighborhood (both real and perceived)—in particular, its percentage of minority inhabitants—is an important
determinant of how “good,” desirable, or safe that neighborhood is judged to
be. Quillian and Pager (2001) find that perceptions of crime in Chicago, Seattle, and Baltimore are positively associated with the percentage of young Black
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men living in the neighborhood. Chiricos, McEntire, and Gertz (2001) have
shown that the perceived proximity to both Black and Latino neighbors
increased Floridians’ perceptions that they might become a crime victim. Sampson and Raudenbush (2004) find that a neighborhood’s racial composition predicts residents’ perceptions of disorder, both physical and social. Furthermore,
St. John and Bates (1990) conducted a vignette study which revealed that
hypothetical neighborhoods with higher proportions of Black residents—even
with crime, cleanliness, housing quality, and other characteristics held constant
—are judged as less desirable by Whites. Building on their work, Emerson,
Yancey, and Chai (2001) find that White Americans are less likely to buy a
home when a hypothetical neighborhood has a higher proportion of African
American neighbors (but are unaffected by the proportion of Asian or Hispanic
neighbors). Lastly, there is considerable evidence that the mere existence of
Black and Latinx residents in a neighborhood leads to decreased property values and lower appraisals (Harris 1999; Howell and Korver-Glenn 2018, 2020).
Racial composition of schools is also an important factor in how people
perceive the quality of those schools and their willingness to enroll their children there. Goyette, Farrie, and Freely (2012) investigated this phenomenon
among White residents of the Philadelphia area. They found that parents were
more likely to perceive their child’s school quality as having declined when the
number of Black students enrolled in the school increased—even when quantifiable measures of school quality showed no such decreases. In a vignette
study, Billingham and Hunt (2016) asked White parents to consider where they
would enroll their hypothetical five-year-old child for kindergarten. They found
that the percent of students who are Black at the hypothetical neighborhood
school was an important predictor of school choice, net of other manipulated
school characteristics (e.g., state ranking, physical condition, and level of security). Overall, then, scholarship on racial inequalities has demonstrated the role
of racial segregation in everyday instances of material and symbolic valuation.
All three of these key insights from scholars of race and ethnicity point
toward the potential role of race—specifically, racial composition—in shaping
the hierarchy of jobs. Therefore, the first research question this study will
answer is how does an occupation’s racial composition impact its perceived
level of prestige? Only two studies have directly examined this question. Wu
and Leffler (1992) found that racial composition is a more important determinant of occupational prestige than gender composition and that occupations
composed of White men reap the highest prestige rewards. Nevertheless, their
analysis only looked at 52 occupations, and did not adjust for other factors
(such as education/training or pay) that are known to influence perceptions of
prestige. We cannot know whether the apparent effect of racial composition on
an occupation’s prestige is in fact driven by other occupational characteristics.
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
651
More recently, Crawley (2014) conducted a survey experiment among
undergraduates at a university and asked them to rate a hypothetical occupation
in terms of status. She did not find that altering the racial composition of the
hypothetical occupation impacted its perceived status. However, this approach
required participants to make judgments about a single unfamiliar occupation—
a much more unusual task than asking participants to make judgments about an
unfamiliar neighborhood or school (something which most of us have done or
will do in our lifetimes)—thereby limiting its external validity. Furthermore, it
relied on a convenience sample of mostly White college students, limiting its
generalizability to the broader U.S. population. Thus, we need data, which will
allow us to examine judgments of prestige from a racially diverse sample about
a broad range of occupations.
What specifically might we expect the relationship between an occupation’s
racial composition and prestige to look like? Research on racial segregation and
pay indicates that predominantly White jobs tend to pay more, and in the domain
of housing, predominantly White neighborhoods receive higher property appraisals. Beyond material valuation, Ray (2019) argues that Whiteness functions as a
credential, legitimizing work-related hierarchies that place White work and workers at the top. Furthermore, the prior research on judgments and perceptions
about neighborhood and schools overwhelmingly finds that Whiter neighborhoods and schools are seen as more desirable. I therefore expect that occupations
with more White incumbents will be seen as more prestigious, net of other
known occupation-level characteristics that shape prestige judgments (such as
required level of education/training, pay, industry, and gender composition).
Hypothesis 1
The percentage of White incumbents in an occupation is positively related
to the occupation’s perceived prestige.
Challenging the Homogeneity Assumption
Much research on occupational prestige presumes that everyone views the
occupational hierarchy the same way—regardless of their own social identity,
such as what country they live in (Lin and Xie 1988; Tiryakian 1958; Treiman
1977) or what social groups they belong to (Hodge, Siegel, and Rossi 1964;
Nakao and Treas 1992; Stevens and Featherman 1981). Yet, emerging research
has highlighted the role of a person’s level of education (Lynn and Ellerbach
2017; Zhou 2005) and gender (Hinze 2005; Valentino 2020) in shaping the
way they perceive the occupational hierarchy. Once again, however, the role of
race in this process has gone largely unnoticed.2
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Therefore, the second research question this study will answer is does the
impact of an occupation’s racial composition on occupational prestige judgments depend on a rater’s own race? In other words, should we expect that all
racial groups rely on racial composition—and in the same way—when they are
making judgments about where an occupation falls in the status hierarchy?
Existing scholarship in race and ethnicity provides suggestive evidence that the
answer to this question will be yes. Specifically, research on strategic assimilation and research on racial segregation in perceptions of neighborhoods and
schools provide clues as to why we might expect this to be the case. I now
briefly consider both of these strands of work.
Strategic assimilation captures the idea that minoritized racial and ethnic
groups may reject “standard” (often White) perceptions of the status hierarchy,
and instead create alternatives that allow them to valorize their own cultural spaces
and practices. Lacy (2004, 2007) finds that middle class African Americans view
Black spaces as valuable sites for socialization, even if they live in a predominantly White neighborhood. Banks (2019) finds a similar process at work regarding Black donations to African American museums, as does Karam (2019) in
terms of Muslim Americans and their parenting practices and Tatum and Browne
(2019) vis-a-vis Dominican immigrants and their consumption patterns. Furthermore, different ethnoracial groups may hold different reference groups for what is
considered high status. For instance, the late nineteenth- and early twentiethcentury occupation of Pullman porter was an exclusively Black job and was seen
as solidly middle class occupation among the African American community at a
time when they were outright barred from holding many other occupations (Frazier 1930). Strategic assimilation, along with the legacy of de jure racial segregation of occupations, suggests that racial and ethnic minorities do not automatically
accept and espouse the prevailing status hierarchies of the White majority.
Only four of the aforementioned studies of racial composition effects on
perceptions of schools and housing were able to investigate the possibility of
differences between individuals on the basis of racial identity.3 Three out of
four found different relationships between racial composition and the outcome,
depending on an individual’s own race. Quillian and Pager (2001) found that
the effect of racial composition on perceptions of residential crime was stronger
for White residents than Black residents. Chiricos McEntire and Gertz (2001)
found that the (perceived) proportion of Black neighbors and Latino neighbors
led White and Latino residents to perceive higher levels of crime victimization,
but neither proportion impacted Black residents’ perceptions. Sampson and
Raudenbush (2004) did not find a difference between Black residents and
White residents in terms of racial composition’s relationship to perceived
neighborhood disorder. Lastly, St. John and Bates (1990) found a negative, linear relationship for Whites between the percentage of Black residents and a
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
653
neighborhood’s desirability, while for Black respondents, the relationship was
non-linear (they preferred more Black neighbors, up to a point).
The preponderance of evidence from this work and theories on strategic
assimilation thus lead me to expect that there will be a dependency between a
rater’s own race and the relationship between an occupation’s racial composition and prestige judgments. In particular, I predict that White raters will rely
more on racial composition than raters of color in their assessment of an occupation’s prestige, net of all other occupational characteristics.
Hypothesis 2
The relationship between the percentage of White incumbents in an occupation and an occupation’s perceived prestige depends on a rater’s race.
Finally, the third research question of this study asks does education mitigate or enhance the relationship between an occupation’s racial composition
and how prestigious it is judged to be? In the racial attitudes literature, two different perspectives point toward competing predictions.
On the one hand, many studies find that people with lower levels of education
have more prejudicial and less tolerant racial attitudes. Bobo and Kluegel (1993)
find that education has a positive effect on a respondent’s support for race-targeted
policies aimed at ameliorating inequality. Sniderman and Piazza (1993) find a
strong negative relationship between number of years of schooling and number of
negative characterizations about Black Americans. Bobo and Kluegel (1997) find
that education has an overall negative effect on both “Jim Crow”-style racism and
endorsement of Black stereotypes among Whites, and has a positive effect on
Whites’ support for government helping improve the standard of living for Black
Americans. Sears, Van Laar and Carillo (1997) similarly find that education is
negatively related to anti-Black attitudes in three out of four datasets under consideration. In a review looking at 40 years of GSS data, Bobo, Charles and Krysan
(2012) find lower education is consistently related to more negative racial attitudes
among Whites. Overall, then, this group of studies indicates that education may
serve to enlighten people to have more progressive racial views. This leads to the
prediction that higher educated individuals should be less likely to draw on racial
composition as a factor in their judgments of an occupation’s prestige.
Hypothesis 3a
The relationship between the percentage of White incumbents in an occupation and an occupation’s perceived prestige is weaker among higher educated
raters as opposed to lower educated ones.
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On the other hand, a number of scholars have suggested that the espousal
of progressive racial attitudes among the well-educated is a function of their
socialization into the belief that racial prejudice is unseemly—but that this
group may not necessarily truly hold racially progressive beliefs. Instead, these
scholars argue the well-educated are simply better at hiding their prejudicial
views, while also being more likely to espouse attitudes that seemingly justify
their social group’s dominance. Jackman and Muha (1984:751) encapsulate this
view based on their reading of GSS data: “We argue that dominant social
groups routinely develop ideologies that legitimize and justify the status quo,
and the well-educated members of these dominant groups are the most sophisticated practitioners of their group’s ideology.” Further evidence for this perspective can be found in the fact that there is no difference between educational
groups in terms of their likelihood of showing racial bias on the Implicit Association Test (Greenwald and Krieger 2006).
Most recently, Wodtke (2012) finds evidence of an attitude/policy divergence among the well-educated: Among Whites, Blacks, and Hispanics, more
education is related to a greater tendency to reject negative stereotypes about
the outgroup and an increased awareness of discrimination against racial
minorities, but more education is not related to an increased propensity to support racially progressive policies. In a related 2016 study that aimed to isolate
the effect of intelligence, Wodtke (2016) concluded that Whites with high verbal ability are less likely to report prejudicial attitudes toward minorities and
more likely to support racial equality in principle, but are not more likely to
support policies promoting racial equality. Mueller (2017, 2020) argues for a
theory of racial ignorance in which well-educated Whites adopt strategies to
promote color-blind ideology while avoiding confronting the reality of racial
inequality. Furthermore, acquiring more education has been shown to decrease
Americans’ willingness to support equitable policies for wealth distribution
(Bullock 2020). Specifically in regard to occupational prestige, Lynn and Ellerbach (2017) found that higher educated raters were more likely to draw on an
occupation’s required level of education as a criterion when evaluating its prestige. Overall, then, this competing perspective would suggest that education is
a means for ideological refinement and social closure, allowing individuals to
become more discriminating in their ability to discern and defend hierarchies—
of which racial composition is an important aspect.
Hypothesis 3b
The relationship between the percentage of White incumbents in an occupation and an occupation’s perceived prestige is stronger among higher educated raters as opposed to lower educated ones.
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
655
Because most of these prior studies have focused exclusively on the relationship between education and racial attitudes among Whites, I will examine
education effects separately for raters of different races.4
Data and Methodology
To test these hypotheses, I draw on a linked dataset that incorporates occupational prestige judgments with the characteristics of those occupations. Prestige judgment data were collected as part of the 2012 General Social Survey
module. Members of the 2008–2012 in-person portion of the rotating panel
were asked to rate a ballot of 90 occupations as part of the 2012 data collection
wave. Respondents were given one of twelve ballots with a set of 70 occupations unique to that ballot, while every ballot also contained 20 “core” occupations to rate. Respondents were instructed to rate each occupation on a scale of
1–9 in terms of its social standing, and ratings were not mutually exclusive, so
respondents could place as many occupations as they liked at the same place
on the scale, making it a true “rating” and not a “ranking.” Table 1 below
shows the demographic characteristics of raters in the sample.
I then linked the occupational prestige judgment data to information about
the occupations being rated. These occupational data were assembled from
Table 1 Demographic Characteristics of Raters
Proportion
Female
Bachelor’s or higher
White
Black
Hispanic
Asian
Working full-time
South
Age
Household incomea
a
.550
.315
.791
.142
.026
.026
.471
.360
Mean
SD
51.7
58109
16.3
42652
Min
22
0
Max
89
150000
Household income responses were provided in categories, so the category’s
midpoint value was used in these calculations.
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various federal sources. The key independent variable, racial composition, was
obtained from the U.S. Census’ Equal Employment Opportunity Report (2006–
2010), and is operationalized as the percentage of job incumbents who are
White. Gender composition also comes from this report and is operationalized
as the percentage of job incumbents who are female. Control variables include
an occupation’s required level of education/training (obtained from the U.S.
Department of Labor’s Occupational Network’s “job zone” index), an occupation’s mean pay (obtained from the Bureau of Labor Statistics’ 2012 employer
reports), and an occupation’s industry (using the North American Industry Classification’s system). Table 2 below shows descriptive statistics for the dataset
at the occupation level.
Occupations with the lowest proportions of White incumbents include
manicurist (46.3% White), English language translator (51.5% White), and barber (52.4% White). Occupations with among the highest proportions of White
incumbents include cattle rancher (95.2% White), veterinarian (92.6% White),
and meteorologist (91.1% White). Bivariate correlations between the
occupation-level variations are shown in Table 3 below.
Consistent with the prior literature on racial occupational segregation, we
can see that the percentage of an occupation’s incumbents who are White is
positively related to the occupation’s required education/training and mean pay.
It is negatively related to the proportion of women in an occupation, which
reiterates earlier findings about patterns of social closure and status composition
that keep women and minorities siloed in particular jobs (Tomaskovic-Devey
1993b). Finally, we see some initial evidence to support Hypothesis 1: %
White is positively related to prestige when averaged across all raters. Nevertheless, models that control for other occupational characteristics and that
account for rater effects are necessary to isolate this effect.
Therefore, I model how different occupational characteristics are used by
different raters in the process of prestige judgments. I also account for raterspecific differences in scale usage and benchmarking, while simultaneously
employing the full range of occupational data, by scaling prestige judgment to
reflect person-specific deviations from their means. All regression models
include the aforementioned occupational characteristics as controls (required
education/training, mean pay, % female and % female squared, and industry
categories), as well as ballot fixed effects. All coefficients are x-standardized to
facilitate comparison of effect sizes across variables. All models also include
robust standard errors, which are clustered at the individual rater level.
Findings
To test Hypothesis 1—whether racial composition has a significant and
substantive effect on occupational prestige judgments—I test two models: one
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
657
Table 2 Descriptive Statistics at the Occupation Level
Education/training
Pay
% White
% female
Mean
SD
Min
Max
2.85
52374
74.7
37.8
1.05
29440
9.2
26.6
1
18720
41.3
1.1
5
230540
95.2
97.7
Industry
Proportion
Architecture and engineering
Arts, design, entertainment, sports, and media
Building and grounds cleaning and maintenance
Business and financial operations
Community and social service
Computer and mathematical
Construction and extraction
Education, training, and library
Farming, fishing, and forestry
Food preparation and serving-related
Healthcare practitioners and technical
Healthcare support
Installation, maintenance, and repair
Legal
Life, physical, and social science
Management
Office and administrative support
Personal care and service
Production
Protective service
Sales and related
Transportation and material moving
.028
.039
.009
.046
.015
.022
.062
.022
.025
.022
.051
.017
.059
.007
.034
.094
.087
.040
.157
.034
.044
.078
that predicts prestige as a function of the occupational control variables only
(education/training, mean pay, and gender composition)—Model 1; and one
that adds the racial composition variable to the prediction equation—Model 2.
As shown in Table 4 below, % White has a small but statistically significant
effect on prestige. Furthermore, model fit improves substantially by AIC and
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LAUREN VALENTINO
Table 3 Zero-Order Correlations among Occupation-Level Variables
Education/training
Mean pay
% White
% female
a
Prestigea
Education/training
.747
.702
.433
.031
.734
.460
.144
Mean pay
% White
.485
.131
.260
Prestige rating is presented here as an average across all raters.
Table 4 Models Without and With Racial Composition
Model 1
Education/training
Mean pay
% Female
% Female (squared)
% White
AIC
BIC
Log likelihood
N
.192***
.226***
.051***
.061***
202892
203236
101409
80,518
(.008)
(.008)
(.006)
(.004)
Model 2
.183*** (.008)
.221*** (.008)
.029*** (.006)
.048*** (.004)
.037*** (.004)
202810.9
203164.1
101367.4
80,518
Note: Unit of analysis is individual-occupation rating. Lower values of AIC
and BIC are preferred. *p < .05, **p < .01, and ***p < .001. Ballot fixed
effects, industry controls, and intercepts not shown to conserve space (available
upon request). Robust standard errors are clustered at the individual level.
BIC standards when racial composition is included as a criterion in the judgment process.
To give a better sense of the magnitude of this effect, I calculate relative
sizes based on predicted prestige values at varying levels of racial composition
benchmarked against another independent variable—mean pay. Increasing an
occupation’s racial composition from 50% White to 90% White leads to a corresponding boost in prestige of .158 standard deviations—equivalent to the
prestige boost that could be achieved by increasing an occupation’s pay by
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
659
-.15
-.1
-.05
prestige
0
.05
.1
approximately $21,250. The impact of racial composition on prestige can also
be illustrated from the predicted value plot, illustrated below in Figure 1.
All in all, we see that occupations below the mean racial composition of
75% White are seen as less prestigious, while occupations above 75% are seen
as more prestigious. This calculation takes into account effects of an occupation’s required education/training, pay, gender composition, and industry on
prestige judgments. White workers made up 80% of the labor force in 2012
(U.S. Bureau of Labor Statistics 2013), so the prestige boost for racial composition begins just short of this figure. This suggests that occupations that are
Whiter than the prototypical job in terms of the labor market’s overall racial
balance are those that are seen as the most prestigious. Hypothesis 1 is therefore supported: racial composition is indeed an important factor that people use
when making judgments about occupational prestige, and Whiter jobs are generally seen as more prestigious.
Next, I turn to Hypothesis 2, which examines whether the racial composition effect shown in Model 2 depends on a rater’s own race. To test this
hypothesis, I introduce separate racial composition effects for raters depending
45
50
55
60
65
70
75
% White in occupation
80
85
Figure 1 Effect of Racial Composition on Prestige.
90
95
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LAUREN VALENTINO
on their own ethnoracial identity into the model. This is specified as Model 3
in Table 5 below.
Results indicate that model fit is indeed improved by allowing the racial
composition effect to depend on a rater’s own race (Model 3). This improvement is likely driven by the difference between White and Asian raters relative
to raters of other races: Black and Hispanic raters do not grant a premium to
Whiter jobs, while White and Asian raters do. This interpretation is bolstered
by results of the Wald tests for differences in coefficients. The difference
between White and Black raters in their usage of racial composition is significant (F(1, 985) = 6.13, p < .05). Asian raters are significantly different from
the other racial groups in how they use % White in their occupational prestige
judgments: White versus Asian (F(1, 985) = 22.49, p < .001), and Hispanic
versus Asian (F(1, 985) = 11.39, p < .001).
These differences can be summed up in Figure 2 below, which shows
how raters of different ethnoracial backgrounds use racial composition differently when making prestige judgments (again, net of other controlled
Table 5 Race-Specific Effects of Racial Composition on Prestige
Education/training
Mean pay
% Female
% Female (squared)
% White
% White (White rater)
% White (Black rater)
% White (Hispanic rater)
% White (Asian rater)
AIC
BIC
Log likelihood
N
Model 2
Model 3
.183*** (.008)
.221*** (.008)
–.029*** (.006)
.048*** (.004)
.037*** (.004)
–
–
–
–
202892
203236
101409
80,518
.183*** (.008)
.220*** (.008)
–.030*** (.006)
.048*** (.004)
–
.041*** (.004)
.002 (.014)
.009 (.030)
.123*** (.017)
202763.5
203154
101339.8
80,518
Note: Unit of analysis is individual-occupation rating. Lower values of AIC
and BIC are preferred. *p < .05, **p < .01, and ***p < .001. Ballot fixed
effects, industry controls, and intercepts not shown to conserve space (available
upon request). Robust standard errors are clustered at the individual level.
661
-.6
-.4
-.2
prestige
0
.2
.4
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
45
50
55
60
65
70
75
% White in occupation
80
85
White rater
Black rater
Hispanic rater
Asian rater
90
95
Figure 2 Race-Specific Effects of Racial Composition on Prestige.
occupational characteristics). Hypothesis 2 is therefore partially supported:
White raters and Asian raters rely on racial composition when assessing an
occupation’s prestige, while Black and Hispanic raters do not.
Finally, I test Hypotheses 3a and 3b by examining the possibility that
raters of different educational backgrounds use the racial composition criterion
differently. Because prior literature led me to expect that this relationship might
be different within different racial categories, I conducted these educationspecific analyses within ethnoracial groups. For ease of interpretation, I have
dichotomized the education variable into those who have a college degree or
higher (31.4% of the sample) and those who do not have a college degree
(68.6% of the sample).
Results of this test are shown in Model 4 of Table 6 below. Model 4 specifies racial composition coefficients that are unique to each group of raters in
terms of their race and education level.5 We see substantial improvement in
model fit between Models 3 and 4, suggesting that the added complexity of
race- and education-specific coefficients for racial composition is indeed warranted.
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LAUREN VALENTINO
Table 6 Race- and Education-Specific Effects of Racial Composition on
Prestige
Education/training
Mean pay
% Female
% Female (squared)
% White (White rater)
% White (White, no college rater)
% White (White, college rater)
% White (Black rater)
% White (Black, no college rater)
% White (Black, college rater)
% White (Hispanic rater)
% White (Hispanic, no college rater)
% White (Hispanic, college rater)
% White (Asian rater)
% White (Asian, no college rater)
% White (Asian, college rater)
AIC
BIC
Log likelihood
N
Model 3
Model 4
.183*** (.008)
.220*** (.008)
–.030*** (.006)
.048*** (.004)
.041*** (.004)
–
–
.002 (.014)
–
–
.009 (.030)
–
–
.123*** (.017)
–
–
202892
203236
101409
80,518
.184*** (.008)
.220*** (.008)
–.030*** (.006)
.048*** (.004)
–
.014* (.007)
.093*** (.010)
–
–.017 (.015)
.081* (.033)
–
.000 (.030)
a
–
.117*** (.033)
.126*** (.005)
202580.9
202999.3
101245.5
80,518
Note: Unit of analysis is individual-occupation rating. Lower values of AIC
and BIC are preferred. *p < .05, **p < .01, and ***p < .001. Ballot fixed
effects, industry controls, and intercepts not shown to conserve space (available
upon request). Robust standard errors are clustered at the individual level.
a
Cell size is too small to produce reliable estimates, so this coefficient is omitted.
Table 6 shows that there is substantial variation within racial groups—as
well as between them—in terms of how they use the racial composition criterion. Among Whites, those without a college degree rely very little on racial
composition, while those with a college degree place much greater weight on
it. The difference between the education coefficients is significant (F(1,
985) = 35.37, p < .001). These effects are depicted in Figure 3 below.
663
-.4
-.2
prestige
0
.2
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
45
50
55
60
65
70
75
% White in occupation
no college
80
85
90
95
college or higher
Figure 3 Education-Specific Effects of Racial Composition on Prestige for
White Raters.
Among Black raters, those without a college degree do not see Whiter
jobs as more prestigious. If anything, they may see Whiter jobs as less prestigious, although this coefficient is not significant. Black raters with a college
degree do see Whiter jobs as more prestigious, although this effect is smaller
in magnitude relative to White college-educated raters and Asian collegeeducated raters. The difference between the two education groups among Black
raters is significant (F(1, 985) = 7.10, p < .01). These effects are depicted in
Figure 4 below.
Finally, in terms of Asian raters, those without a college degree do see
Whiter jobs as more prestigious, but this effect is even larger for Asian raters
with a college degree. Nevertheless, this difference in coefficients is not statistically significant (F(1, 985) = 0.06, p = .804). These effects are shown in Figure 5 below.
Altogether, these results provide qualified support for Hypothesis 3b. For
White and Black raters, having more education means that they are more likely
to use the criterion of racial composition when making occupational prestige
judgments, and this is especially true for White raters. White and Black raters
LAUREN VALENTINO
-.4
-.2
0
prestige
.2
.4
664
45
50
55
60
65
70
75
% White in occupation
no college
80
85
90
95
college or higher
Figure 4 Education-Specific Effects of Racial Composition on Prestige for
Black Raters.
without a college degree only marginally (in the case of White raters) or do not
at all (in the case of Black raters) consider the number of White incumbents in
an occupation when assessing its prestige. For Asian raters, however, education
has a less discernible effect: raters with and without a college degree both similarly rate Whiter jobs as more prestigious.
Discussion and Conclusion
We know surprisingly little about how race relates to the symbolic rewards
of occupations: status—or, as it is commonly operationalized, occupational
prestige. Although prior research has examined the impact of racial composition on judgments and perceptions about other institutions in American society,
researchers have yet to fully investigate the impacts of racial composition on
judgments and perceptions about the occupational structure. I have argued that
this occurs because of two limiting assumptions about the way the hierarchy of
labor is constructed: the assumption that it is materialist—implying individuals
are color-blind as to the racial segregation and racialized nature of the occupational structure; and the assumption that is homogeneous—implying that a
665
-.6
-.4
-.2
prestige
0
.2
.4
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
45
50
55
60
65
70
75
% White in occupation
no college
80
85
90
95
college or higher
Figure 5 Education-Specific Effects of Racial Composition on Prestige for
Asian Raters.
person’s own identity (including their racial identity) has no bearing on the
way they perceive the occupational hierarchy. The purpose of this study has
been to shed light on this long-standing question by challenging these two
assumptions, drawing on key insights from scholarship in race and ethnicity.
The findings from this study demonstrate that racial composition is a salient cue that features prominently in people’s assessments of where an occupation falls in the status hierarchy. Much like when people make judgments
about neighborhoods and schools, I find that the proportion of White workers
in an occupation signals status—and the Whiter the occupation, the higher the
status. It is notable that these effects are visible even when accounting for other
known components of occupational prestige (such as a job’s required education/training, pay, gender composition, and industry). This finding aligns with
prior work, which found that employers often associate certain ethnoracial
groups with certain types of labor (Alegria 2019; Maldonado 2006, 2009; Pager
et al. 2009; Wingfield and Alston 2013). It also provides evidence in favor of
the theory of Whiteness as a credential (Ray 2019) and highlights the importance of processes through which organizations construct these hierarchies
(Tomaskovic-Devey 1993b).
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LAUREN VALENTINO
However, the story is not so simple. Not everyone relies on the cue of
racial composition when making occupational prestige judgments—or to be
more precise, not everyone relies on it in the same way or to the same degree.
White and Asian raters draw on the Whiteness of an occupation, rewarding
jobs with more White workers in them. Pande and Drzewiecka (2016) find that
some Asian Americans may engage in a process of strategic alignment with
Whites, rather than a process of strategic assimilation; the findings here support
that notion.6 Black and Hispanic raters, meanwhile, do not see Whiter jobs as
more prestigious, in accordance with the strategic assimilation perspective. Part
of these race differences in the usage of racial composition can be explained by
educational differences between racial groups: When comparing collegeeducated White and Black raters, there is a roughly similar reliance on an occupation’s Whiteness when judging prestige, although Black college-educated
raters are somewhat lower in the degree to which they reward occupational
Whiteness relative to White college-educated raters. Among non-collegeeducated raters, however, race differences are quite prominent: Whites give a
slight edge to Whiter occupations, and Asian raters reward Whiter occupations
with a very large prestige premium; meanwhile, Black raters without a college
degree do not reward Whiter occupations.
Overall, then, these findings reinforce the importance of social factors—
such as racial composition—in shaping occupational prestige judgments. Contra
the materialist assumption, an occupation’s “pure” material factors—such as
required education/training, pay, and industry—are not the only components of
work that impact perceptions of status in the occupational structure. Results
from this study also underline the fact that perceptual differences are not uniform across social groups, evidence against the homogeneity assumption: race
acts as a filter that influences the way people perceive and order their social
world. Finally, I have provided evidence in favor of the “ideological refinement
as social closure” theory regarding education’s role in shaping attitudes. No
matter a person’s race, having more education resulted in a rater relying more
on the cue of racial composition as a way of organizing the occupational status
hierarchy. Education in this case makes people more discriminating in how
they construct the racial hierarchy of labor.
Examining the role of racial composition in perceptions and judgments
provides a relatively unobtrusive way of examining racial attitudes, an approach
that is arguably less subject to the well-known social desirability bias that has
plagued traditional survey research about race and ethnicity (Krumpal 2013).7
The extent to which people are consciously aware of the occupational prestige
judgment-making process—especially their discursive beliefs about whether/
how they use criteria such as racial composition—represents an important next
step in this line of research, and would have implications for dual-process
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
667
theories of cognition and decision making (Miles, Charron-Chenier, and Schleifer 2019; Vaisey 2009). Nevertheless, the present study cannot distinguish
between what social psychologists refer to as first-order and third-order beliefs:
what social standing do I think a given occupation has, versus what social
standing do I think most people think a given occupation has (see Correll et al.
2017; Melamed et al. 2019). Additional research collecting data on these two
types of occupational status judgments is vital to disentangle whether these
racial attitudes regarding status are truly held, or whether they may be a case
of pluralistic ignorance (i.e., believing—perhaps incorrectly—that most other
people think a given occupation is low status due to the preponderance of people of color who work in that job).
The fact that racial composition is further inscribed in subjective perceptions of status such as occupational prestige suggests that race casts a longer
shadow than has been previously acknowledged on status and its attendant outcomes. Gatekeepers use status to allocate material and symbolic resources in
ways that can both mitigate and exacerbate existing inequities between ethnoracial groups. Because occupations predominated by people of color are symbolically devalued, this further restricts the mobility and life chances of the people
working in these kinds of jobs. It is important for future work to understand
how these racially infused prestige judgments impact concrete outcomes. For
example, are people who work in occupations predominated by people of color
less likely than those who work in Whiter jobs to be recommended for a higher
starting salary or promotion, or to successfully obtain a mortgage or other loan?
Future research, particularly that which uses a survey–experimental and/or field
audit design, is critical for answering these questions.
The pattern of rewarding Whiteness with prestige likely has important
implications for social closure. Indeed, this may be a two-way process: Whites
may reward predominantly White occupations with prestige, but they may also
gatekeep predominantly White occupations on the basis of race in order to
maintain the status privilege of those positions. Royster (2003) finds evidence
for this type of gatekeeping among blue-collar workers, but future ethnographic
field research should examine these micro-level processes of racial exclusion
among white-collar workers and hiring managers. Overall, this study sheds new
light on the processes of valuation of labor, a fundamental concern of cultural
sociologists and scholars of inequality and stratification. Uniting insights from
often-too-disparate fields such as cognitive sociology and the study of race and
ethnicity (Brekhus, Brunsma, and Platts 2010), the present research illustrates
the complex ways that race informs perceptions of status. By challenging the
materialist and homogeneity assumptions of occupational prestige, this study has
shown that the construction of the hierarchy of labor is profoundly racialized.
668
LAUREN VALENTINO
Data Availability Statement
The data that support the findings of this study are openly available at the
Inter-university Consortium for Political and Social Research https://doi.org/10.
3886/ICPSR35478.v4.
ENDNOTES
*Please direct correspondence to Lauren Valentino, 1885 Neil Avenue Mall, Townshend Hall,
Columbus, OH 43210-1132, USA; e-mail: valentino.60@osu.edu
The author wishes to thank Chris Bail, Kieran Healy, Trish Homan, Jessi Streib, and Steve
Vaisey for their invaluable feedback on this article. An earlier version of this work was presented at
the “Jobs, Occupations, and Professions” session of the 2020 Annual Meeting of the American
Sociological Association.
1
Consider, for instance, the now-infamous case of Henry Louis Gates Jr. as he was harassed
by police for entering his own home in Cambridge, Massachusetts. Although we know that many
Black men are unduly stopped and harassed by police in the United States, it was Gates’ status as
a Harvard professor, which arguably sparked outrage and led to his invitation to the White House
in an attempt to discuss the relationship between Black America and the police. If Gates had instead
been a janitor at Harvard who was harassed for entering his own home, it is difficult to imagine that
he would have made headlines and been invited for a beer with the President and Vice President of
the United States.
2
Zhou (2005) finds that people of different races give differing weights to the role of knowledge, creativity, and authority in terms of how prestigious a job is, but does not examine racial variations in the role of racial composition in these perceptions.
3
Some of the research that has examined the role of racial composition in judgments has
focused solely on White individuals (e.g., Billingham and Hunt 2016; Goyette et al. 2012), and for
good reason: Whites generally control the majority of resources in terms of housing wealth and
educational credentials in the United States, and so their perceptions and resultant choices are arguably more influential on the distribution of material and symbolic rewards in American society
(Johnson and Shapiro 2003). At a more practical level, estimating rater-specific race effects can be
prohibitive due to small cell sizes among ethnoracial minorities, particularly in small-N studies.
4
Among studies of this nature that did include racial minorities, there is some evidence of a
strikingly different relationship between education and progressive racial attitudes between White
vs. minority respondents. Bobo and Kluegel (1993) found that increased levels of education have a
negative effect on progressive racial attitudes among Black Americans.
5
This specification assumes all other occupational characteristics are common across these
subgroups—an assumption that allows for model fit comparisons, but one that merits a fuller investigation in a future study.
6
In their study of Asian Americans in California, Jimenez and Horowitz (2013) find that some
of these individuals construct a hierarchy of academic achievement which places cultural associations regarding Asian-ness above Whites.
7
We also cannot know whether (in)accuracy in perceptions about racial composition drives
the difference between lesser and more-educated raters. Perhaps higher educated raters are simply
more aware of an occupation’s racial composition. This seems unlikely, however, given that it is
lower educated individuals who are most likely to work in occupations with those of another race:
CONSTRUCTING THE RACIAL HIERARCHY OF LABOR
669
Indeed, Table 3 above shows that there is a large positive correlation between the percentage of
White workers in an occupation and the required education/training of that job.
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