Black–White mean differences in job satisfaction: A meta-analysis

    Black–White mean differences in job satisfaction: A meta-analysis Wee Koh Chee, Winny Shen, Tiffany Lee PII: DOI: Reference:

S0001-8791(16)30019-7 doi: 10.1016/j.jvb.2016.02.009 YJVBE 2983

To appear in:

Journal of Vocational Behavior

Received date: Revised date: Accepted date:

24 November 2015 12 February 2016 16 February 2016

Please cite this article as: Chee, W.K., Shen, W. & Lee, T., Black–White mean differences in job satisfaction: A meta-analysis, Journal of Vocational Behavior (2016), doi: 10.1016/j.jvb.2016.02.009

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BLACK-WHITE DIFFERENCES IN JOB SATISFACTION

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Black-White Mean Differences in Job Satisfaction: A Meta-Analysis

Department of Psychology

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a

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Chee Wee Koha, Winny Shenb, and Tiffany Leea

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University of South Florida 4202 E Fowler Ave.

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Tampa, FL USA 33620

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b

Department of Psychology University of Waterloo

200 University Avenue West

Waterloo, ON Canada N2L 3G1 519-888-4567 ext. 31576

[email protected] (Corresponding Author)

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TITLE

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Black-White Mean Differences in Job Satisfaction: A Meta-Analysis

ABSTRACT

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Studies examining Black-White mean differences in job satisfaction have provided little clarity

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regarding whether there are meaningful differences between the two racial/ethnic groups on this job attitude. The present study sought to reconcile prior inconsistent findings via a meta-analytic

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synthesis of this literature (N = 753,791; K = 63 independent samples from 55 studies) and

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examined whether moderators explained the observed variability in effects. Using Hedges and Vevea’s (1998) random-effects meta-analytic approach, we found that, on average, White

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workers were slightly more satisfied with their jobs than Black workers (gcorrected = .09; 95%

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credibility interval = -.21 to .39) and this effect was larger in more nationally representative samples (gcorrected = .24). The substantial true variability around this effect suggests the presence

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of moderators and the need for caution in interpreting the overall effect as it likely does not generalize across all work settings. Data collection year, geographic location within the U.S., job sector, and measure type were not found to moderate Black-White mean differences in job satisfaction. However, job complexity and sample demographic composition did significantly moderate this relationship. Our results show that the magnitude and direction of Black-White mean differences in job satisfaction are influenced by the context. KEYWORDS Job satisfaction; Black-White differences; race/ethnic group differences; meta-analysis; job complexity

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Black-White Mean Differences in Job Satisfaction: A Meta-Analysis Job attitudes can be considered “one of the oldest, most popular, and most influential

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areas of inquiry in all of organizational psychology” (Judge & Kammeyer-Mueller, 2012, p. 342). The present study focuses on the most frequently studied job attitude in the literature, job

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satisfaction. Job satisfaction is typically defined as a worker’s overall evaluation of his or her job

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(Locke, 1976). Given the long history of job attitude research in industrial/organizational

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psychology and organizational behavior, it is not surprisingly that there are a number of metaanalytic summaries that document the nomological network of job satisfaction (e.g., personality,

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Judge, Heller, & Mount, 2002; job performance, Judge, Thoreson, Bono, & Patton, 2001; turnover, Tett & Meyer, 1993). Yet, despite the substantial research literature uncovering

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correlates of job satisfaction, the extent to which racial/ethnic differences in job satisfaction exist is still not well understood. Thus, the purpose of the present study was to provide a

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comprehensive quantitative summary of racial/ethnic group differences in job satisfaction. The lack of attention devoted to understanding and uncovering racial/ethnic group differences in job satisfaction stands in direct contrast to the research literature on job performance, where there has been a long history of scholars investigating and finding racial/ethnic group differences, particularly Black-White differences (e.g., McKay & McDaniel, 2006; Roth, Huffcut, & Bobko, 2003). This gap in the research literature is particularly surprisingly given that previous research has found consistent links between job satisfaction and job performance (Judge et al., 2001). Furthermore, we believe that it is important to understand racial/ethnic group mean differences in job satisfaction in their own right, as job satisfaction serves as an important indicator of workers’ subjective well-being (Diener, 2000).

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Most existing studies conducted in the United States have focused on group differences between White and Black workers. This is due to historical reasons (e.g., Coates, 2014) and the

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fact that until relatively recently, Blacks or African-Americans have been the largest minority

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group in the United States (U.S. Census Bureau, 2010). Therefore, by necessity, in the current paper, we focus our discussion and efforts on summarizing the direction and magnitude of

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Black-White mean differences on job satisfaction. However, comparing Black-White differences

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in job satisfaction is meaningful in its own right. Prior research shows that Black-White mean differences in job performance are substantially larger than differences between the White

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majority group and other racial/ethnic minority groups (e.g., Roth et al., 2003) and recent work also demonstrates that African-Americans as a group are perceived to be of lower status than

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other racial/ethnic minority groups in the U.S. (i.e., Hispanics and Asians; Leslie, 2014). Thus, it appears that Black-White mean differences in job satisfaction may be larger than those between

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other minority racial/ethnic groups and the majority group and may, therefore, serve as an upperbound regarding the magnitude of racial/ethnic group differences in job satisfaction. 1. Black-White Mean Differences in Job Satisfaction 1.1. Theoretical Background

Two categories of explanations, structural and cultural, have been used to explain BlackWhite mean differences in job satisfaction. Structural explanations attribute group differences to differential treatment or experiences of Black and White employees in the employment context (e.g., Kashefi, 2011). In contrast, cultural explanations emphasize differences in predispositions between Black and White workers in beliefs, values, and psychological states that are shaped during their formative years, which then subsequently affect occupational choices and work outcomes (e.g., O’Reilly & Roberts, 1973). Thus, cultural explanations may explain why there

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are Black-White mean differences in job satisfaction even in the absence of structural differences between the two groups. Note that the two explanations are not mutually exclusive and both may

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contribute to the existence of Black-White mean differences in job satisfaction.

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In terms of structural theories, previous research has found that Black workers are more vulnerable to discriminative educational and occupational practices that limit their upward

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mobility than White workers (O’Connell, 2012). Despite significant progress, particularly since

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the Civil Rights movement, African-Americans as a group continue to lag behind the White majority group in education, employment, and income indicators in the United States (Caputo &

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Deprez, 2012). Examples of structural differences in organizational life between Black and White workers include differences in treatment (e.g., affirmative action programs; Buzawa, 1981)

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and experiences in organizations (e.g., being racially/ethnically dissimilar from one’s co-workers; Riordan & Shore, 1997), which are then expected to influence job satisfaction.

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Cultural theories typically emphasize that Black and White workers may hold different values. For example, some prior research has shown that Black workers tend to value extrinsic job rewards (i.e., income and security) over intrinsic job rewards (i.e., feelings of achievement; e.g., Shapiro, 1977), with some authors arguing that this is a legacy of slavery and Jim Crow laws that have made African-Americans insecure about material possessions. However, prior research has also argued that intrinsic job rewards should be more strongly linked to job satisfaction than extrinsic job rewards (e.g., Martin & Tuch, 1993), a proposition generally supported by Self-Determination Theory (Ryan & Deci, 2000). Thus, Black and White workers may be attuned to different aspects of the work environment due to cultural factors, resulting in differences in racial/ethnic group differences in job satisfaction. 1.2. Empirical Research

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Although both structural and cultural theories predict the existence of Black-White mean differences in job satisfaction in favor of White workers, empirical findings have been

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inconsistent. A number of studies reported higher levels of job satisfaction for White workers

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relative to Black workers (e.g., Niemann & Dovidio, 1998; Weaver, 1974), but other studies have found the converse (e.g., DeFour & Brown, 2006; Lopez & Greenhaus, 1978). In a

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qualitative review, Smith (1975) concluded that Black workers are more dissatisfied with their

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jobs than White workers. In contrast, in a later quantitative review, Brush, Moch, and Pooyan (1987) concluded that, on average, there were no Black-White mean differences in job

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satisfaction. Thus, it is currently unclear whether differences in results across studies regarding Black-White differences in job satisfaction are due to sampling error, are the result of substantive

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differences across samples that serve as moderators, or reflect systematic changes over time. Overall, existing theory and research suggests that there may be Black-White mean

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differences in job satisfaction. Furthermore, current theoretical explanations appear to favor the perspective that Black workers are likely to be more dissatisfied with their jobs than their White co-workers, for both structural and cultural reasons. Thus, we propose the following: Hypothesis 1: Black workers are less satisfied with their jobs than White workers. 2. Moderators of Black-White Mean Differences in Job Satisfaction The apparent variability in the direction and magnitude of Black-White mean differences in job satisfaction found in the literature may reflect the presence of moderators, which we examine in the present study using meta-analytic techniques. Specifically, we explored whether Black-White mean differences in job satisfaction is moderated by six variables: time period, racial/ethnic composition of the sample, location within the U.S., job sector, job complexity, and type of job satisfaction measure.

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2.1. Time Period In the United States, the Civil Rights movement expanded career opportunities and

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protections for Black workers (King, Avery, & Sackett, 2013). Although slavery was outlawed

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after the Civil War, various other forms of structural discrimination, such as racial and economic segregation, were still quite widespread in some states up until the enactment of the Civil Rights

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Act of 1964 and additional protections were only introduced with the Civil Rights Act of 1991.

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Given that the current meta-analysis includes studies published over a 60 year period (i.e., 1950 to 2014), we expect Black workers to have made relative gains in job satisfaction over time as

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working conditions and protections for minority workers in the United States improved. Thus, although Black workers may be more dissatisfied with their jobs than their White counterparts

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historically, we expect this gap to have decreased over time. Hypothesis 2: Time (i.e., data collection year) moderates Black-White mean differences in job

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satisfaction, such that these differences have become smaller over time. 2.2. Demographic Composition of the Sample Prior theory and research has argued that the racial/ethnic demographic composition of organizations impacts workplace outcomes. For example, Riordan and Shore (1997) found that similarity in race/ethnicity between oneself and one’s workgroup impacted one’s job attitudes toward the workgroup and one’s perceptions of advancement opportunities in the organization. Kanter’s (1977) seminal work on tokenism makes similar arguments. Subsequent empirical tests of Kanter’s propositions do indeed find that in highly compositionally skewed groups, minority individuals are more likely to be perceived as tokens, generally leading to greater performance pressure, social isolation, and role entrapment for these individuals and worse work and wellbeing outcomes (e.g., Jackson, Thoits, & Taylor, 1995; Spangler, Gordon, & Pipkin, 1978). Thus,

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we hypothesize that Black workers will be more satisfied in workplaces where they constitute a larger proportion of the workforce, resulting in smaller Black-White differences.

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Hypothesis 3: Demographic composition of the sample moderate Black-White mean differences

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in job satisfaction, such that the mean differences in favor of White workers are smaller in samples where there is a higher representation of Black workers.

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2.3. Location in the United States

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The southern states of the U.S. are a region with relatively high income inequality and low educational achievement (Ngarambe & Goetz, 2002). Even in recent years, the average

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county disparity in the African-American poverty rate relative to the White poverty rate remains greater in the South than in other parts of the United States (O’Connell, 2012). O’Connell argues

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that the legacy of slavery in the South shapes contemporary social structures and affects economic disparities through its influence on educational and political institutions, limiting

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Blacks’ access to political power and hampering their ability to bargain for higher wages and hindering their influence regarding the allocation and distribution of local resources. As such, we expect Black-White differences in job satisfaction in the U.S. to be exacerbated in the South. Hypothesis 4: Location moderates Black-White mean differences in job satisfaction, such that these differences are larger in favor of White workers in the South than elsewhere in the U.S. 2.4. Job Sector In 2011, nearly 20% of employed Blacks worked for state, local, or federal governments compared to 14.2% of employed Whites (U.S. Department of Labor, 2012). Thus, Black workers are more likely to be employed in the public sector than White workers. The government as an employer frequently acts to promote equal opportunities, thereby reducing disparities in state, local, and federal payrolls (Ngarambe & Goetz, 2002). The public sector has a high degree of

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standardization and formalization, in contrast to most private companies, which tend to have fewer formal safeguards against racial discrimination (e.g., Vinson & Holloway, 1977). Thus,

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we expect Black-White mean differences in job satisfaction in favor of White workers to be

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larger in the private sector than in the public sector.

Hypothesis 5: Job sector moderates Black-White mean differences in job satisfaction, such that

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these differences are larger in favor of White workers in the private than public sector.

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2.5. Job complexity

Job complexity refers to differences between jobs in their difficulty (i.e., requirements for

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problem solving and discretion). Black workers in high complexity jobs often report both lower autonomy and satisfaction than their White counterparts (e.g., Slocum & Strawser, 1972; Watson

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& Shealey, 2010). They also report being sidelined to less desirable roles and not being entrusted with the same responsibilities as their White colleagues (e.g., Fernandez, 1981; Tomaskovic-

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Devey & Stainback, 2007). Thus, Black-White mean differences in job satisfaction, in favor of White workers, may be particularly pronounced in high complexity jobs. In low complexity jobs, several studies have found either no Black-White mean differences in job satisfaction (e.g., Jones, James, Bruni, & Sells, 1977) or higher job satisfaction among Black workers relative to White workers (e.g., Gavin & Ewen, 1974). These findings can be explained by ‘relative deprivation’ (Moch, 1980); given that Black workers often face additional structural barriers in gaining employment, low-skilled Black workers may be more satisfied with their job compared to White workers in similar circumstances (Katzell, Ewen, & Korman, 1974). A related explanation is that low complexity jobs generally consist of more concrete and well-defined tasks, where employee compensation is based on directly observable performance episodes (Conway & Huffcutt, 1997). Therefore, performance evaluations are more

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objective and performance and pay gaps between high and low performers tend to be relatively small (Hunter, Schmidt, & Judiesch, 1990). Thus, issues of fairness may be less likely to come

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into play in low complexity jobs, which may lead to higher levels of job satisfaction for Black

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relative to their White workers, and the converse is likely true in high complexity jobs. Hypothesis 6: Job complexity moderates Black-White mean differences in job satisfaction, such

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that mean differences are in favor of White workers in high complexity jobs and mean

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differences are in favor of Black workers in low complexity jobs. 2.6. Job Satisfaction Measure Type

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In the literature, there appears to be two major types of job satisfaction scales. The first type asks respondents to indicate how satisfied they are with their job overall. The second type

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asks respondents how satisfied they are with various aspects of their job (e.g., the work itself, pay, co-workers, supervision, and advancement opportunities) and then combines across these

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different facets to represent the respondents’ level of job satisfaction. Prior work suggests that overall and combined facet measures of job satisfaction are not equivalent, as employees may consider aspects of the job outside of those domains typically assessed by facet measures of satisfaction (e.g., Highhouse & Becker, 1993). Furthermore, facet satisfaction measures typically simply average across domains to generate a single job satisfaction score, but workers may, in fact, differentially value or weight these domains in determining their overall job satisfaction. Although there is evidence that the two types of job satisfaction measures may not be isomorphic, it is unclear in what manner this would affect our estimates of Black-White mean differences. Thus, we examine moderation by measure type as a research question. Research Question 1: Does measure type (i.e., overall versus combined job satisfaction) moderate Black-White mean differences in job satisfaction?

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3. The Current Study The present meta-analysis on Black-White mean differences in job satisfaction serves

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two primary purposes. The first is to quantify differences between Black and White workers on

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job satisfaction. The use of meta-analysis allows us to statistically account for the impact of sampling error and unreliability across studies, providing a better estimate of true differences

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between these two racial/ethnic groups on this construct. The second purpose is to determine,

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after accounting for observed variability due to sampling error and unreliability, whether there are moderators of this relationship. Although a popular approach to studying Black-White mean

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differences in job satisfaction is to analyze archival data of broad samples (e.g., nationally representative samples; Bartel, 1981; Defour & Brown, 2006; Weaver, 1974), this approach is

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limited in that it generally cannot answer questions about moderating effects across work settings. In contrast, our meta-analysis synthesizes data from both these broad samples as well as from

4. Method

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more targeted samples, which better allows for the identification of moderating effects.

4.1. Literature Search and Inclusion Criteria We initially searched PsycINFO and GoogleScholar using the keywords: black AND white AND job satisfaction and race AND job satisfaction. If the abstract of an article appeared relevant, its reference section was then used to identify other potential articles for inclusion. We read the method and results section of the 119 studies thus identified and applied three criteria in sequence to evaluate each study for inclusion: (1) must measure both Black and White workers’ job satisfaction (excluded 69 studies); (2) sample must consist of working adults from the United States (excluded 2 studies), and (3) either must report or provide information for computing an

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effect size (excluded 21 studies). We also contacted authors for missing information. This resulted in an initial pool of 26 studies (after accounting for redundant samples).

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We then searched all volumes of the 48 journals which published the 119 articles that we

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initially identified (see Appendix A). We adopted this approach because it is more empiricallybased and comprehensive than the usual approach of searching a list of high-impact journals in a

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domain. This approach was also more appropriate given that studies on Black-White mean

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differences in job satisfaction were not necessarily concentrated in a particular journal or discipline. Articles with job satisfaction and any one of the following in-text keywords were

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shortlisted for further screening: race, racial, black, white, negro, cross-cultural, ethnic, Caucasian, or African-American. From this search, we uncovered seven additional studies.

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Finally, we searched ProQuest Dissertations and Theses using the same keywords as our initial database search to find unpublished studies on Black-White mean differences in job

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satisfaction and identified 428 studies for further screening: 158 studies did not measure both Black and White workers’ job satisfaction, 34 studies did not use working adults from the United States, and another 214 studies did not report or provide information to compute an effect size and were excluded. We retained 22 studies from this search that met our inclusion criteria. The entire search process resulted in a final pool of 55 studies and 63 independent effect sizes. 4.2. Coding Interrater reliability was examined by randomly selecting a subset (≈ 33%) of the total studies in our database and having two coders independently code this subset of articles. There was only one coding discrepancy between the coders, which resulted in an intraclass correlation (ICC) of .99 for sample size and an ICC of 1.00 for all other coded variables. Each remaining

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study was then coded independently by one coder, whose coding was subsequently doublechecked for accuracy by the other coder (see Appendix B for coded information for each article).

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4.2.1. Time period

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In operationalizing time period, we use year of data collection rather than year of publication because there is typically a non-trivial time lag between when data is collected and

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when a study is published. Moreover, several studies in our database reported results from

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independent samples surveyed in different years (e.g., Bartel, 1981; Modica & Mamiseishvili, 2010). Furthermore, we believe that data collection year is a more direct test of our moderating

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hypothesis than publication year.

Several samples included in our meta-analysis used data collected over a span of several

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years. If data were collected over a span of three years, then the median year of the data collection period was used, and if data were collected over a span of two years, then the later

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year of the data collection period was used. Samples where data collection year could not be verified (12 studies) or where the data collection period exceeded 3 years (3 studies) were excluded from this analysis, resulting in the inclusion of 46 effect sizes. The mean data collection year was 1990 (SD = 13.30 years; range = 1966 - 2009). 4.2.2. Demographic composition of samples The demographic composition of each sample was represented by the proportion of Black workers in the sample. Fifty-nine effect sizes were included in this analysis. The mean percentage of Black workers across samples was 28% (SD = .17; range = 3 - 61%). 4.2.3. Location in the United States A sample was coded as ‘South’ if data were collected from one or more of these 17 states: Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina,

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Virginia, West Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas (U.S. Census Bureau, 1994). Data collected from all other states were

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coded as ‘Non-South’. Studies that collected data across regions were excluded from this

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analysis, resulting in the inclusion of 32 effect sizes (14 South and 18 Non-South). 4.2.4. Job sector

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We differentiated between public sector workers (e.g., federal employees, public school

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teachers, police officers, and military personnel) and workers employed by private, for-profit organizations. Studies which collected data across sectors were excluded from this analysis,

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resulting in the inclusion of 38 effect sizes (30 public sector and 8 private sector). 4.2.5. Job complexity

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Job complexity was coded using the criteria reported in Hunter et al. (1990). Specifically, low complexity jobs included unskilled or semi-skilled positions, entry-level blue-collar jobs, or

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enlisted positions at the most junior ranks. Medium complexity jobs were jobs that require some specialized training (e.g., policing and teaching) or first-level supervisory positions in manufacturing settings. High complexity jobs included professional managers, school principals, and university faculty. Studies that included jobs across multiple job complexity levels were excluded from this analysis, resulting in the inclusion of 32 effect sizes (8 low complexity, 14 medium complexity, and 10 high complexity). 4.2.6. Job satisfaction measure type We distinguished between job satisfaction measures that focused on questions about participants’ overall satisfaction with their job (i.e., overall measures) from measures that asked participants about how satisfied they were with various specific aspects of their job (i.e., combined facet measures). By far the most common overall measures were various one-item

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measures asking participants to generate an overall evaluation of their job (e.g., "How do you feel about the job you have now?" Bartel, 1981), though our meta-analytic database also

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included multi-item overall job satisfaction measures (i.e., Brayfield & Rothe, 1951; Job-in-

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General scale). The most commonly used combined facet measures were the Job Descriptive Index (JDI) and the Minnesota Satisfaction Questionnaire. However, note that these two

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measures together still represent less than half of the combined facet satisfaction effects. Thus, a

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wide variety of job satisfaction measures have been employed in this domain, preventing us from directly examining specific measures as moderators. In total, 62 effect sizes were included in this

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analysis (34 overall and 28 combined facet measures). One study (Friday & Friday, 2003) was excluded because it only reported a subset of the JDI facet scores.

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4.3. Data Analysis

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The effect size we cumulated was Cohen’s d, which is generally unaffected by unequal

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subgroup sizes within a sample (Laczo, Sackett, Bobko, & Cortina, 2005). Positive d-values indicate White workers reported higher levels of job satisfaction and negative values indicate Black workers reported higher levels of job satisfaction. First, we individually corrected each effect size and variance for unreliability in job satisfaction (Hunter & Schmidt, 1990). Among the 39 studies that employed multi-item job satisfaction measures, coefficient alpha was available for 34 studies and we used the reliability estimates for each corresponding sample for individual corrections. The mean coefficient alpha (α = .85) was then used for correcting the five remaining studies which did not report reliability estimates. For the 16 studies that employed single-item job satisfaction measures, the meta-analytic estimate of the reliability of single-item job satisfaction measure (α = .67; Wanous, Reichers, & Hudy, 1997) was used in the correction for attenuation. Corrected d-values were then converted to Hedges’ g (Borenstein, Hedges,

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Higgins, & Rothstein, 2009) because d has a slight bias towards overestimation of the mean difference (Hedges, 1981). Note that g is interpreted the same way as d (i.e., in standard

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deviation units), as an index of standardized mean difference.

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Our meta-analysis employed Hedges and Vevea’s (1998) random-effects model using the Comprehensive Meta-Analysis software package (Borenstein, Hedges, Higgins, & Rothstein,

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2005). We report both 95% confidence and credibility intervals; confidence intervals provide an

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estimate of the variability around the estimated mean difference that is due to sampling error, while credibility intervals provide an estimate of the variability of individual effect sizes in the

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population, across studies (Whitener, 1990). Moderator analyses for continuous moderators were performed using meta-regression with method of moments, and moderator analyses for

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categorical moderators were performed using mixed-effects subgroup analyses, where the studyto-study variance was computed within each subgroup. We also examined whether there was

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evidence of publication bias using funnel plots, Egger’s regression, and Duval and Tweedie’s (2000) trim-and-fill procedure.

Included among the studies in our meta-analysis was a prior meta-analysis of unpublished studies conducted in Michigan organizations (Brush et al., 1987) and a study with a very large sample size (N = 668,335; Whaley & Belhadjali, 2009). The variance associated with the mean effect size reported in a prior meta-analysis should be less than the variability reflected in the primary studies that it summarizes, and effect sizes in meta-analysis are weighted by their sample sizes. Thus, we conducted sensitivity analyses that excluded one or both of these studies, where applicable, to ensure that results were not biased by the inclusion of these studies. 5. Results 5.1. Overall Analyses

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The overall mean effect size for Black-White mean differences in job satisfaction was gcorrected = 0.09 (95% CI = [.04, .14], see Table 1). Thus, on average, White workers were slightly

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more satisfied than Black workers, supporting Hypothesis 1. However, the absolute magnitude of

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this effect was quite small. Note that this effect was robust and did not change when we conducted our sensitivity analyses (i.e., excluding Brush et al., 1987 and/or Whaley & Belhadjali,

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2009). Although Hypothesis 1 was generally supported, the 95% credibility interval (-.21 to .39),

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which included zero, as well as significant Q and I2 statistics shows that Black-White mean differences in job satisfaction may not generalize across all settings (i.e., there may be cases in

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which Black workers are more satisfied with their jobs than White workers). All three statistics highlight that there is substantial non-artifactual or true variability in the magnitude of Black-

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White mean differences in job satisfaction across situations (Borenstein et al., 2009). Given that our meta-analysis included both broad samples as well more targeted samples

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(e.g., focusing on workers in particular jobs or organizations), we also examined whether these different sampling strategies, which reflect different levels of analysis, resulted in different estimates of Black-White mean differences in job satisfaction (see Table 2). Among broader and more representative samples (i.e., 12 out of 14 were nationally representative samples of the U.S. working population), Black-White differences in job satisfaction still favored White workers and were, in fact, even larger than in our overall analysis (gcorrected = 0.24, 95% CI [0.11, 0.36]). In contrast, among more narrow or targeted samples, there were no differences in job satisfaction between Black and White workers (gcorrected = 0.02, 95% CI [-.04, 0.09]). Thus, these analyses suggest that across the entire U.S. working population, White workers are more satisfied with their jobs than Black workers, but this effect does not necessarily always hold within specific

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work settings. Sensitivity analyses indicate that findings were robust and did not change with the exclusion of Brush et al. (1987) and/or Whaley and Belhadjali (2009).

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A funnel plot (available from the first author upon request) shows that effect sizes did not

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converge toward the apex, which suggests the presence of moderators. Egger’s regression did not indicate publication bias (y-intercept = 0.64, t = 1.37, p = 0.18), which was corroborated by

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results from the trim-and-fill procedure (i.e., only two effect sizes were imputed to the right of

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the summary mean). Thus, publication bias does not appear to be an issue in this literature. 5.2. Moderator Analyses

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We first examined the effect of our two continuous moderators, time period and demographic composition of samples (i.e., % Black in sample; see Table 3). Data collection year

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did not moderate the magnitude or direction of Black-White mean differences in job satisfaction [Qmodel(1) = 2.48, p = 0.12; see Table 3]. Thus, Hypothesis 2 was not supported. Demographic

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composition of sample was found to moderate the magnitude of Black-White mean differences in job satisfaction [Qmodel(1) = 7.22, β = -.56, p < 0.01; see Table 3], supporting Hypothesis 3. Specifically, effect sizes increased (i.e., greater mean differences in job satisfaction in favor of White workers) as the proportion of Black workers decreased. A sensitivity analysis that excluded Whaley and Belhadjali (2009) yielded a similar pattern of results. We then examined the effect of our four categorical moderators, location in the United States (i.e., Southern or Non-Southern state), job sector (i.e., public or private), job complexity (i.e., low, medium, or high; see Table 2), and measure type (i.e., overall or combined facet). Location did not moderate Black-White mean differences in job satisfaction [Q(1) = .64, p = 0.42; see Table 3]. A sensitivity analysis which excluded Brush et al. (1987) did not change the observed pattern of results. Therefore, Hypothesis 4 was not supported. Job sector also did not

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moderate Black-White mean differences in job satisfaction [Q(1) = 1.34, p = 0.25; see Table 2]. Excluding Whaley and Belhadjali (2009) in a sensitivity analysis did not impact our findings.

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Thus, Hypothesis 5 was also not supported.

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Job complexity moderated Black-White mean differences in job satisfaction [Q(2) = 11.63, p < 0.01; see Table 2], supporting Hypothesis 6. In low complexity jobs, Black workers

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were more satisfied with their jobs than White workers (gcorrected = -0.25, 95% CI [-0.41, -0.09]).

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The opposite pattern was found in high complexity jobs, where White workers were more satisfied with their jobs than Black workers (gcorrected = 0.32, 95% CI [0.03, 0.61]). The 95%

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confidence interval included zero for the effect in medium complexity jobs, suggesting that Black and White workers did not meaningfully differ in their level of job satisfaction for these

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types of jobs (gcorrected = -0.18, 95% CI [-0.38, 0.02]). Finally, job satisfaction measure type (i.e., overall job satisfaction measures vs. combined

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facet satisfaction measures) did not moderate Black-White mean differences in job satisfaction [Q(1) = 0.28, p = .59; see Table 2]. Sensitivity analyses that excluded Brush et al. (1987) and/or Whaley and Belhadjali (2009) did not alter the pattern of results (Research Question 1). 6. Discussion

Prior research on Black-White mean differences in job satisfaction have yielded inconsistent results. This present meta-analysis makes three major contributions towards clarifying the nature of this relationship. First, our results show that White workers, on average, are slightly more satisfied with their jobs than Black workers (gcorrected = .09) and this difference is even larger when estimated among samples more representative of the United States’ working population (gcorrected = .24). Second, we find that there is substantial true variance in Black-White mean differences in job satisfaction across situations. Thus, it may not be very meaningful to

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make general statements about the typical magnitude of Black-White mean differences in job satisfaction, since in some settings Black workers may be more satisfied with their job than

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White workers. Third, we identify predictors of this variability in effects. Specifically,

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demographic composition of the sample and job complexity predicted this variation (i.e., moderated Black-White mean differences in job satisfaction). Thus, our results shed light on

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whether and when Black and White workers differ in their evaluations of job satisfaction.

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Our finding regarding the moderating effect of job complexity suggest that while much progress may have been made in levelling the playing field in low and medium complexity jobs

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for Black workers in the United States, the same level of progress may not have occurred in high complexity jobs and this population may be in particular need of organizational intervention

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efforts. Perceptions of low autonomy, limited opportunities for career advancement, lack of Black role models, and tokenism may all contribute the lower levels of job satisfaction found for

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Black workers relative to White workers in high complexity jobs. In addition, these factors may also create a vicious cycle, such that lower levels of job satisfaction among Black professionals may contribute to higher turnover rates that disrupt the pipeline of future Black role models in high complexity jobs (e.g., Thomas, 1993). Although some may infer that these are common challenges encountered by many or most minority groups in the workplace, previous research has shown that race can predict job satisfaction above and beyond minority status. For example, Niemann and Dovidio (1998) surveyed professors in psychology departments and found that although minority (i.e., Black, Asian, and Hispanic) professors as a group reported lower job satisfaction than White professors, only the Black-White difference was statistically significant. Our study is also suggestive, though clearly not definitive, of organizational actions that may enhance the job satisfaction of Black workers relative to their White coworkers. Black

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workers in high complexity jobs, where career advancement is very competitive, may be particularly sensitive to disadvantages associated with race (Tomaskovic-Devey & Stainback,

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2007). Human resources policies and practices that promote greater transparency in performance

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evaluations and reward allocations may help allay some of these concerns. It could also be that Black workers in these high complexity jobs feel that they are tokens due to their general lack of

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numerical representation in these positions and may suffer negative workplace consequences as a

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result (e.g., Leslie, Mayer, & Kravitz, 2013). Organizations may be able to reduce feelings of isolation and marginalization for this group by enhancing organizational demographic

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representativeness (e.g., King et al., 2013), providing relatable mentors (e.g., Ross, 2010), or by promoting a climate of inclusion (e.g., Nishii, 2013).

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6. 1. Limitations and Future Research Directions Although our study has a number of strengths, like all studies it is not without limitations.

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One limitation of our current approach is that our comparisons are relative to the other group. Therefore, we cannot make any statements regarding absolute changes in job satisfaction within a racial/ethnic group over time. Thus, we do not know whether Black (or White) workers have become more satisfied, relative to previous generations. It could be that although there has not been any systematic change in the relative satisfaction of White and Black workers over time, there could still have been substantial changes in the absolute magnitude of job satisfaction for both racial/ethnic groups. A related issue is whether the job satisfaction measures used in the primary studies of our analyses demonstrated measurement invariance across the two groups (as well as over time). Although there is some evidence that supports the measurement equivalence of the JDI across different racial/ethnic groups in the United States (e.g., Drasgow & Kanfer, 1985; Smith et al., 1974), information regarding measurement equivalence of other job

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satisfaction measures is generally lacking. Previous research has highlighted the importance of establishing measurement equivalence prior to undertaking group comparisons (Vandenberg &

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Lance, 2000), and we encourage future research to examine issues of measurement equivalence

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between racial/ethnic groups on job attitudes empirically.

A second limitation is that we only meta-analyzed Black-White mean differences in job

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satisfaction and did not examine differences for other racial/ethnic minority groups (i.e.,

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Hispanic, Asian, or Native American). This was due to lack of available data comparing White workers to other minority groups or between racial/ethnic minority groups. Most existing

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research tends to treat all racial/ethnic minorities as a homogeneous group, which may not always be justified (e.g., Leslie, 2014; Niemann & Dovidio, 1998). Thus, more primary studies

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examining differences between specific racial/ethnic minority groups on job satisfaction or other job attitudes (e.g., organizational commitment and work engagement) are needed. Additional

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empirical research and theorizing should then be undertaken to explore whether the differences we have uncovered in the present study generalize to other racial/ethnic minority groups. Although we find a significant moderating effect due to demographic composition of the sample, why this variable moderates Black-White mean differences in job satisfaction is somewhat unclear. In the introduction, we posit that the racial/ethnic demographic composition of groups impacts work outcomes due to factors related to similarity, familiarity, and/or tokenism and use demographic composition of the sample as a proxy to represent this idea. However, many of the studies included in our study were not from a single organization and some studies did report over-sampling minority workers. Testing this relationship only among studies that were conducted within a given organization and did not engage in minority oversampling would be a more appropriate test of our hypothesis; however, this analysis would be

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based on a very small number of samples, making it unlikely that we would have the statistical power to detect effects. Thus, we encourage future research to continue to examine the role of

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organizational demographic composition on racial/ethnic group differences in job attitudes.

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Given prior work that suggests that cultural factors may lead White and Black workers to differentially focus on intrinsic versus extrinsic job rewards (e.g., Martin & Tuch, 1993), a final

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limitation of our study is our inability to test whether Black and White workers differ in their

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satisfaction with respect to intrinsic (e.g., the job itself) versus extrinsic (e.g., pay, supervision) aspects of their work. We were unable to examine this question because the majority of studies

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that used combined facet measures in this meta-analysis did not report facet-level results. Future research should investigate whether this distinction moderates Black-White mean differences in

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job satisfaction. Additionally, a better understanding of facet-level differences may also help organizations to better understand areas of particular (dis)satisfaction for different racial/ethnic

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groups and generate more effective targeted solutions or interventions. 6.2. Conclusion

Our comprehensive meta-analysis includes studies published over a span of more than 60 years and concludes that although, on average, White workers are slightly more satisfied with their jobs compared to Black workers, Black-White mean differences in job satisfaction varies substantively and somewhat predictably across settings. Specifically, this variation can be explained in part by differences in job complexity and the demographic composition of the sample. Our hope is that the present results will spur additional future research on predictors and consequences of racial/ethnic subgroup differences in job attitudes, which has been largely neglected in the literature. We also hope that this work will help organizations to hone in on workplace policies and practices that better engage, satisfy, and retain Black and other

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racial/ethnic minority workers. We believe that, ultimately, an engaged and satisfied workforce

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is a win-win situation for both employees and employers.

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Table 1. Random-effects meta-analysis of Black-White mean differences in job satisfaction I2(%)f

[.04,.14] 597.25(62)*** .02

[-.21,.39]

89.62

.09

[.03,.15] 589.22(61)*** .04

[-.30,.47]

89.65

85456

.08

[.02,.15] 582.71(61)*** .05

[-.36,.53]

89.53

75264

.08

[.01,.16]

[-.43,.60]

88.65

.09

Exclude Brush et al. (1987)

62

743599

Exclude Whaley & Belhadjali (2009)

62

Exclude both studies

61

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753791

d

RI

63

All studies

Q(df)c

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gcorrected

95% CIb

Ƭ2

95% Cred Inte

Ntotal

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ka

528.79(60)*** .07

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Note. a number of effect sizes involved in each analysis; b 95% confidence interval of g; c standardized measure of the total variance in the meta-analysis (attributable to both sampling error and variance in true effects); under the null hypothesis that all studies share a common effect size, Q will follow a central chi-square distribution with df = k-1, and a significant Q value indicates there are meaningful variations in the true effect sizes; d estimate of the variance of the true effect sizes; e 95% credibility interval for g, which indicates the dispersion of the true effect sizes in the population; f proportion of observed variance which is due to real differences in effect sizes; large (>75%) I2 suggests the presence of moderators. *p < .05, **p < .01, ***p < .001

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Table 2. Categorical moderator analyses of Black-White mean differences in job satisfaction Subgroup Broad samples Targeted samples

ka 14 49

Southern states Non-Southern states

14 18

14,549 3,586

.05 -.06

[-.18, .27] [-.21, .09]

0.64(1)

Public sector Private sector

30 8

694,893 2,513

-.03 .14

[-.11, .05] [-.15, .43]

1.34(1)

Low job complexity Medium job complexity High job complexity

8 14 10

2,473 13,172 3,131

-.25 -.81 .32

[-.41, -.09] [-.38, .02] [.03, .61]

11.63(2)**

Overall measures Combined facet measures

34 28

65,211 688,463

0.28(1)

Q(df) b 8.62(1)**

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95% CIg [.11, .36] [-.04, .09]

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[.03, .18] [-.02, .16]

Broad samples Targeted samples

13 49

MA

SC

Ntotal gcorrected 37,920 .24 715,871 .02

27,728 715,871

.26 .07

[.12, .40] [-.04, .09]

8.63(1)**

Southern states Non-Southern states

14 17

4,357 3,586

.05 -.09

[-.18, .27] [-.29, .12]

.73(1)

55,019 688,463

.10 .07

[.01, .19] [-.02, .16]

.26(1)

.10 .07

TE 33 28

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Overall measures Combined facet measures

D

Excluding Brush et al. (1987)

Excluding Whaley & Belhadjali (2009)

Broad samples Targeted samples

14 48

37,920 47,536

.24 .02

[.11, .36] [-.07, .11]

7.63(1)**

Public sector Private sector

29 8

26,558 2,513

-.06 .14

[-.16, .06] [-.15, .43]

1.49(1)

34 27

65,211 20,128

.10 .08

[.03, .18] [-.06, .21]

0.13(1)

Overall measures Combined facet measures

Excluding both studies Broad samples Targeted samples

13 48

27,728 47,536

.26 .02

[.12, .40] [-.07, .11]

7.82(1)**

Overall measures Combined facet measures

33 27

55,019 20,128

.10 .08

[.01, .19] [-.06, .21]

0.12(1)

Note. a number of effect sizes in each group; b dispersion explained by the moderator – significant p-value indicates significant moderation effect. *p < .05 **p < .01 ***p < .001

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Table 3. Continuous moderator analyses of Black-White mean differences in job satisfaction ka

N

Qmodel(df) b

Qtotal(df) c

Qresidual(df) d

βe

95% CIβ f

Data collection year

46

63,078

2.48(1)

71.28(45)**

68.81(44)**

.00

[-.00,.01]

% Black Workers in Sample

59 735,197

7.22(1)**

129.81(58)***

122.58(57)

-.49

[-.97, -.15]

58

4.97(1)*

88.75(57)

-.57

[-1.08, -.07]

RI

SC

83.78(56)

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66,862

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Exclude Whaley &Belhadjali (2009)

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Moderator

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Notes. a number of effect sizes involved in each analysis; b dispersion explained by the moderator; c total dispersion of effect sizes about the grand mean; d total dispersion of effect sizes about the regression line. e regression coefficient (slope); f 95% confidence interval around β. Statistically significant Qmodel and β (where 95% CIβ does not include zero) indicates a significant moderation effect. *p < .05 **p < .01 ***p < .001

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APPENDIX A LITERATURE SEARCH

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Journals searched that resulted in zero articles for inclusion: Academy of Management Journal, Administrative Science Quarterly, Career Development International, Criminology, Cultural

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Diversity & Ethnic Minority in Psychology, Group & Organization Studies, Journal of Black

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Studies, Journal of Business Ethics, Journal of Career Development, Journal of Occupational

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Behavior, Journal of Population Economics, Journal of Special Education, Management Information Systems Quarterly, Police Quarterly, Psychology of Women Quarterly, Public

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Personnel Management, Research in Higher Education, Signs, Social Behavior & Personality, Social Science & Medicine Journal, Sociometry, Stress & Health, Work & Occupations.

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Journals searched that resulted in articles for inclusion (and the # of articles included):

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Administration in Social Work (1), American Educational Research Journal (1), American

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Journal of Criminal Justice (1), Business Horizons (1), Education (1), Journal of African American Studies (1), Journal of Applied Psychology (1), Journal of Behavioral Economics (1), Journal of Business and Psychology (1), Journal of Criminal Justice (2), Journal of Academic and Business Ethics (1), Journal of Gerontological Social Work (1), Journal of Human Resources (1), Journal of Organizational Behavior (1), Journal of Management Development (1), Journal of Social Psychology (1), Journal of the National Medication Association (1), Journal of Vocational Behavior (3), Journal of Women in Culture & Society (1), Negro Educational Review (1), Personnel Psychology (4), Psychological Reports (1), Social Forces (1), Sociological Quarterly (2), Sociology of Education (1). Studies Included in the Present Meta-Analysis (K = 55 studies in total): Published Journal Articles (32, see above for journals included), Book Chapter (1), and Dissertations (22).

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APPENDIX B

Data year

2486 466 3222 2728 2515 274 74 96 140 10192 156 425 1044 154 128 512 1008 801 2577 95 50 8665 117 471 1683 89 203 298 1441 1617 188 N

0.32 0.20 0.17 0.03 -0.08 0.27 -0.59 1.30 -0.78 0.00 -0.56 0.58 0.13 0.23 0.10 -0.07 0.28 0.32 -0.22 0.44 -0.73 0.22 -0.37 -0.33 -0.06 -0.66 0.09 0.09 0.36 -0.11 -0.35 gcorrected

369.10 77.64 537.23 456.94 420.92 14.37 16.47 17.41 24.82 5790.33 28.61 71.00 94.96 27.20 28.03 109.00 119.63 85.48 226.97 19.52 5.19 859.35 25.35 97.94 47.95 11.26 45.84 41.06 83.11 342.86 39.03 W

1967 2005 1966 1969 1971 1989

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PT ED

Location

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W (=1/Vg)

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gcorrected

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Andrisani (1978)b, d Avery, McKay, Wilson, & Tonidandel (2007)b Bartel (1981) sample 1 b Bartel (1981) sample 2 b Bartel (1981) sample 3 b Bell (1989) a Berrian (2006) sample 1 a Berrian (2006) sample 2 a Brice (1998) a Brush, Moch, & Pooyan (1987) c Buzawa (1981) Cabrera (2000) a Carlan (2007) Chen (1986) a Clemens (1990) a Culver, Wolfle, & Cross (1990) Dalton & Marcis (1987) sample 1 b Dalton & Marcis (1987) sample 2 b DeFour & Brown (2006) b Dorr (1992) a Eubanks (1974) Fairchild (2009) a Friday & Friday (2003) e Gavin & Ewen (1974) Glymour, Saha & Bigby (2004) Gottlieb (1964) Gravett (1995) a Hoppe, Fujishiro, & Heaney (2014) Jones (2002) a Jones, James, Bruni, & Sells (1977) Katzell, Ewen, & Korman (1974) Study

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Study

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STUDY SAMPLE SIZE, EFFECT SIZE, WEIGHT AND MODERATOR CODING

1998 1978 2000 1985 1986 1979 1979 2002 1991 1972 2004 1996 1969 1997 1993 2002 1973 1969 Data

Non-south South South South Non-south Non-south Non-south South Non-south Non-south South Non-south South Non-south Non-south Non-south Location

Job Job Sector Complexity

Sample

Proportion of Blacks

Measure Type

Public Private Public Public Public Public Public Public Public Public Public Public Private Public Private Private Public Job

Broad Broad Broad Broad Broad Targeted Targeted Targeted Targeted Broad Targeted Targeted Targeted Targeted Targeted Targeted Broad Broad Broad Targeted Targeted Targeted Targeted Targeted Targeted Targeted Targeted Targeted Targeted Targeted Targeted Sample

0.34 0.37 0.07 0.53 0.36 0.26 0.33 0.32 0.16 0.32 0.61 0.49 0.23 0.20 0.16 0.35 0.50 0.15 0.61 0.17 0.03 0.40 0.44 0.32 0.07 0.10 0.54 Proportion

Overall Overall Overall Overall Overall Combined Combined Combined Combined Overall Overall Combined Overall Combined Overall Combined Overall Overall Overall Combined Combined Overall Combined Overall Overall Combined Overall Combined Overall Combined Measure

Medium High High Medium Medium Medium Medium Medium Medium Medium Low High Medium Low Medium Low Job

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AC

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(=1/Vg) year Sector Complexity of Blacks Type Kaye, Alexander, & Kauffman (1999) 125 -0.75 19.04 1989 Non-south Low Targeted 0.52 Combined Kuhn (1981) a 461 -0.39 30.86 1981 South Public Medium Targeted 0.09 Combined Long (2006) a 134 0.17 29.07 2005 South Public Targeted 0.22 Overall Lopez & Greenhaus (1978) 523 -0.39 110.17 Non-south Public Targeted 0.46 Overall Lum (1997) a 354 -0.01 62.28 1992 Non-south Public High Targeted 0.32 Combined Mack (2000) a 130 0.47 30.19 1999 Public High Targeted 0.57 Combined Matteson (2008) a 888 0.34 116.38 2002 Public Targeted 0.21 Combined McNeely (1989) 1136 -0.29 169.55 1984 Public Targeted 0.23 Overall Mikell (1981) a 60 0.53 12.00 Public High Targeted 0.45 Combined Milutinovich (1975) sample 1 326 0.49 46.64 Non-south Private Targeted 0.20 Combined Milutinovich (1975) sample 2 711 -0.24 134.11 Non-south Private Low Targeted 0.30 Combined Modica & Mamiseishvili (2010) sample 1 4580 0.05 103.49 1993 Targeted 0.03 Overall Modica & Mamiseishvili (2010) sample 2 3970 0.19 96.70 1999 Targeted 0.04 Overall Modica & Mamiseishvili (2010) sample 3 5260 0.20 165.53 2004 Targeted 0.05 Overall Niemann & Dovidio (1998) 306 0.41 46.42 1993 High Targeted 0.24 Overall Ramere (2006) a 77 0.09 9.24 2005 South Public Medium Targeted 0.19 Combined Potts (2007) a 281 -0.17 46.92 2006 South Private Low Targeted 0.42 Overall Robinson (1995) a 213 0.15 5.34 1995 High Targeted 0.03 Overall Saenger & Gordon (1950) b 505 0.59 31.53 Non-south General 0.10 Overall Shiftlett (1988) 272 -0.47 34.76 Public Low Targeted 0.20 Combined Somers & Birnhaum (2001) 174 0.25 33.57 South Public High Targeted 0.42 Combined Tuch & Martin (1991) b 2517 0.31 161.62 Broad 0.11 Overall Turner (1997) a 308 0.34 67.79 1996 South Public Targeted 0.41 Combined Walter (2007) a, b 2902 0.42 471.97 2000 Broad 0.12 Overall Walker (2009) a 41 1.09 5.51 2009 South Public High Targeted 0.22 Combined Weaver (1974) b 5369 0.70 221.38 Broad 0.08 Overall Weaver (1977) b 632 0.46 43.05 1974 Broad 0.12 Overall Whaley & Belhadjali (2009) 668335 0.03 89954.7 Public Targeted 0.22 Combined White, Cooper, Saunders, & Raganella (2010) 116 -0.50 11.95 2008 Non-south Public Medium Targeted 0.19 Overall sample 1 White, Cooper, Saunders, & Raganella (2010) 30 -0.29 5.18 2008 Non-south Public Medium Targeted 0.57 Overall sample 2 Wilson & Butler (1978) 9013 0.06 954.50 1973 Public Targeted 0.16 Combined Zingraff & Schulman (1984) 127 0.19 21.22 1980 South Private Low Targeted 0.52 Overall Note. a dissertation; b involved samples from U.S. general working population; c quantitative summary of multiple samples; d reported longitudinal data - because one of our moderators was data collection year, we decided to use only data from the first time point instead of obtaining a composite effect across the time points; e this particular study reported only selected JDI subscale results, and we used the JDI work satisfaction score as a proxy for overall satisfaction because it is highly correlated with the JDI-JIG score (.78; Ironson, Smith, Brannick, Gibson, & Paul, 1989) .

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APPENDIX C REFERENCES INCLUDED IN THE META-ANALYSIS

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Andrisani, P. J. (1978). Job satisfaction among working women. Journal of Women in Culture and Society, 3, 588-607.

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Avery, D. R., McKay, P., Wilson, C., & Tonidandel, S. (2007). Unequal attendance: The

SC

relationships between race, organizational diversity cues, and absenteeism. Personnel

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Psychology, 60, 875-902.

Bartel, A. P. (1981). Race differences in job satisfaction: A reappraisal. The Journal of Human

MA

Resources, 16, 294-303.

Bell, A. T. (1989). Analysis of job satisfaction determinants in NATA-certified athletic trainers

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employed in different settings (Doctoral dissertation). Available from ProQuest

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Dissertations and Theses database. (UMI No. 9012906)

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Berrian, A. L. (2006). Job satisfaction, perceptions of fairness, and perceived departmental support among African-American and White faculty (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3238496) Brice, A. P. (1998). The relationship among school climate, teacher job satisfaction, and selected demographic variables in selected high schools in south Mississippi (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9901328) Brush, D. H., Moch, M. K., & Pooyan, A. (1987). Individual demographic differences and job satisfaction. Journal of Occupational Behaviour, 8, 139-155. Buzawa, E. S. (1981). The role of race in predicting job attitudes of patrol officers. Journal of Criminal Justice, 9, 63-77. Cabrera, L. (2000). Racial and ethnic influence on job satisfaction levels in subordinate-superior

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dyadic relationships: Does a difference make a difference? (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9970159)

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Carlan, P. E. (2007). The search for job satisfaction: A survey of Alabama policing. American

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Journal of Criminal Justice, 32, 74-86.

Chen, A. S. (1986). Perceived job satisfaction levels of federal employees in a Department of

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Defense organization (Doctoral dissertation). Available from ProQuest Dissertations and

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Theses database. (UMI No. 8713272)

Clemens, C. (1990). The relationship of measures of job satisfaction to work/nonwork

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preference, life satisfaction, and mental health in Black and White workers (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No.

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9024641)

Culver, S. M., Wolfle, L. M., & Cross, L. H. (1990). Testing a model of teacher satisfaction for

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Blacks and Whites. American Education Research Journal, 27, 323-349. Dalton, A. H., & Marcis, J. G. (1987). Gender differences in job satisfaction among young adults. Journal of Behavioral Economics, 16, 21-32. Defour, D. C., & Brown, T. M. (2006). Attitudes toward maternal roles and the effects on life satisfaction: Black, Hispanic, and White models. Journal of African American Studies, 10, 3-18. Dorr, B. W. (1992). Stereotypes and the perception of discrimination: Understanding minority work-related attitudes and behaviors (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9218968) Eubanks, E. E. (1974). A study of perceptions of Black and White teachers in de facto segregated high schools. Education, 95, 51-57. Police Quarterly, 8, 476-489.

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Fairchild, S. (2009). Determinants of White, non-Hispanic and Black, non-Hispanic urban school teachers’ job satisfaction: Does relational demography matter? (Doctoral

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dissertation). Available from ProQuest Dissertations and Theses database. (UMI No.

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3361967)

Friday, S. S., & Friday, E. (2003). Racioethnic perceptions of job characteristics and job

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satisfaction. Journal of Management Development, 22, 426-442.

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Gavin, J. F., & Ewen, R. B. (1974). Racial differences in job attitudes and performance: Some theoretical considerations and empirical findings. Personnel Psychology, 27, 455-464.

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Glymour, M. M., Saha, S., & Bigby J. (2004). Physician race and ethnicity, professional satisfaction, and work-related stress: Results from the physician worklife study. Journal

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of the National Medical Association, 96, 1283-1294. Gottlieb, D. (1964). Teaching and students: The views of Negro and White teachers. Sociology of

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Education, 37, 345-353.

Gravett, L. S. (1995). Career planning and development and career outcomes: Variations by race, sex, age and ethnicity (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9541636) Hoppe, A., Fujishiro, K., & Heaney, C. A. (2014). Workplace racial/ethnic similarity, job satisfaction, and lumbar back health among warehouse workers: Asymmetric reactions across racial/ethnic groups. Journal of Organizational Behavior, 35, 172-193. Jones, D. P. (2002). College housing officers' job satisfaction: A national study (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3041696) Jones, A. P., James, L. R., Bruni, J. R., & Sells, S. B. (1977). Black-White differences in work

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environment perceptions and job satisfaction and its correlates. Personnel Psychology, 30, 5-16.

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*Katzell, R. A., Ewen, R., & Korman, A. K. (1974). Job attitudes of Black and White workers:

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Male blue-collar workers in six companies. Journal of Vocational Behavior, 4, 365-376. Kaye, L. W., Alexander, L. B., & Kauffman, S. (1999). Factors contributing to job quality and

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Gerontological Social Work, 31, 143-166.

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satisfaction among ethnically diverse, lower income, elderly part-timers. Journal of

Kuhn, B. J. (1981). Teacher personality type and job satisfaction (Doctoral dissertation).

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Available from ProQuest Dissertations and Theses database. (UMI No. 8213669) Long, J. L. (2006). Relationships between personality type, job satisfaction, and job performance

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in the Mississippi State University Extension Service (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3211242)

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Lum, K. D. (1997). Determinants of institutional commitment among Black and White faculty at traditionally White state-owned and state-related universities in Pennsylvania (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9732028)

Mack, P. A. Jr. (2000). Perspectives of principals on job satisfaction (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9963686) Matteson, A. V. (2008). Role of work climate in job satisfaction and organizational commitment of women in a non-traditional career field: The case of women in the military (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3425488) McNeely, R. L. (1989). Race and job satisfaction in human service employment. Administration

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in Social Work, 13, 75-94. Mikell, V. T. (1981). Black-White differences in manifest needs and satisfactions in an

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Dissertations and Theses database. (UMI No. 8119780)

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affirmative action work environment (Doctoral dissertation). Available from ProQuest

Milutinovich, J. S. (1975). A comparative study of work attitudes of Black and White workers.

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In D. L. Ford, Jr. (Ed.), Readings in minority group relations (pp. 135-155). La Jolla, CA:

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University Associates, Inc.

Modica, J. L., & Mamiseishvili, K. (2010). Black faculty at research universities: Has significant

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progress occurred? The Negro Educational Review, 61, 107-122. Niemann, Y. F., & Dovidio, J. F. (1998). Relationship of solo status, academic rank, and

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perceived distinctiveness to job satisfaction of racial/ethnic minorities. Journal of Applied Psychology, 83, 55-71.

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Potts, H. (2007). The role of social capital in organizations: The precursors and effects of social capital among certified nurse aides in nursing homes (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3276458) Ramere, C. J. (2006). An examination of job satisfaction related to teacher turnover in selected North Carolina middle schools (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3219940) Robinson, M. J. (1995). Job satisfaction of National Collegiate Athletic Association Division III athletics directors (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 9600069) Saenger, G., & Gordon, N. S. (1950). The influence of discrimination on minority group

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members in its relation to attempts to combat discrimination. Journal of Social Psychology, 31, 95-120.

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Shiflett, S. (1988). Effects of race and criterion on the predictive ability of beliefs and attitudes.

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Psychological Reports, 62, 527-535.

Somers, M. J., & Birnbaum, D. (2001). Racial differences in work attitudes: What you see

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depends on what you study. Journal of Business and Psychology, 15, 579-591.

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Tuch, S. A., & Martin, J. K. (1991). Race in the workplace: Black/White differences in the sources of job satisfaction. The Sociological Quarterly, 32, 103-116.

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Turner, V. L. (1997). Career development concerns of African-American employees of Florida Community College at Jacksonville, Florida (Doctoral dissertation). Available from

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ProQuest Dissertations and Theses database. (UMI No. 9726473) Walker, C. Y. W. (2009). Factors related to job satisfaction of secondary principals in rural

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areas (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3374141)

Walter, R. J. (2007). An analysis of earnings and job satisfaction outcomes associated with subbaccalaureate educational attainment (Doctoral dissertation). Available from ProQuest Dissertations and Theses database. (UMI No. 3294147) Weaver, C. N. (1974). Negro-White differences in job satisfaction. Business Horizons, February 1974, 67-72. Weaver, C. N. (1977). Relationships among pay, race, sex, occupational prestige, supervision, work autonomy, and job satisfaction. Personnel Psychology, 30, 437-445. Whaley, G. L., & Belhadjali, M. (2009). A comparative analysis of ethnic groups in military and

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federal services on measures of perceived organizational EO climate, commitment and job satisfaction. Journal of Academic and Business Ethics, 2, 1-8.

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White, M. D., Cooper, J. A., Saunders, J., & Raganella, A. J. (2010). Motivations for becoming a

street. Journal of Criminal Justice, 38, 520–530.

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police officer: Re-assessing officer attitudes and job satisfaction after six years on the

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Wilson, K. L., & Butler, J. S. (1978). Race and job satisfaction in the military. The Societal

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Quarterly, 19, 626-638.

Zingraff, R., & Schulman, M. D. (1984). Social bases of class consciousness: A study of

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Southern textile workers with a comparison by race. Social Forces, 63, 98-116.

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HIGHLIGHTS We meta-analyzed Black-White mean differences in job satisfaction in the United States.



On average, White workers are slightly more satisfied with their jobs than Black workers.



The 95% credibility interval suggests that this effect does not generalize across all

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

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Job complexity and sample demographic composition moderated effects.

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

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settings.