research paper on gender discrimination in the workplace

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Research Article

Justifying gender discrimination in the workplace: The mediating role of motherhood myths

Contributed equally to this work with: Catherine Verniers, Jorge Vala

Roles Conceptualization, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Paris Descartes University, Sorbonne Paris Cité, Paris, France, Institute of Social Sciences, University of Lisbon, Lisbon, Portugal

Roles Conceptualization, Funding acquisition, Writing – original draft, Writing – review & editing

Affiliation Institute of Social Sciences, University of Lisbon, Lisbon, Portugal

• Catherine Verniers, 

• Published: January 9, 2018
• https://doi.org/10.1371/journal.pone.0190657
• Reader Comments

18 Jul 2018: Verniers C, Vala J (2018) Correction: Justifying gender discrimination in the workplace: The mediating role of motherhood myths. PLOS ONE 13(7): e0201150. https://doi.org/10.1371/journal.pone.0201150 View correction

The issue of gender equality in employment has given rise to numerous policies in advanced industrial countries, all aimed at tackling gender discrimination regarding recruitment, salary and promotion. Yet gender inequalities in the workplace persist. The purpose of this research is to document the psychosocial process involved in the persistence of gender discrimination against working women. Drawing on the literature on the justification of discrimination, we hypothesized that the myths according to which women’s work threatens children and family life mediates the relationship between sexism and opposition to a mother’s career. We tested this hypothesis using the Family and Changing Gender Roles module of the International Social Survey Programme. The dataset contained data collected in 1994 and 2012 from 51632 respondents from 18 countries. Structural equation modellings confirmed the hypothesised mediation. Overall, the findings shed light on how motherhood myths justify the gender structure in countries promoting gender equality.

Citation: Verniers C, Vala J (2018) Justifying gender discrimination in the workplace: The mediating role of motherhood myths. PLoS ONE 13(1): e0190657. https://doi.org/10.1371/journal.pone.0190657

Editor: Luís A. Nunes Amaral, Northwestern University, UNITED STATES

Received: October 6, 2017; Accepted: December 18, 2017; Published: January 9, 2018

Copyright: © 2018 Verniers, Vala. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are available from the GESIS Data Archive (doi: 10.4232/1.2620 and doi: 10.4232/1.12661 ).

Funding: This work was conducted at the Institute of Social Sciences, University of Lisbon, Portugal, and supported by a travel grant of the European Association for Social Psychology, http://www.easp.eu/ , and a travel grant of the Association pour la Diffusion de la Recherche en Psychologie Sociale, http://www.adrips.org/wp/ , attributed to the first author. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The latest release from the World Economic Forum—the Gender Gap Report 2016 [ 1 ]–indicates that in the past 10 years, the global gender gap across education and economic opportunity and politics has closed by 4%, while the economic gap has closed by 3%. Extrapolating this trajectory, the report underlines that it will take the world another 118 years—or until 2133 –to close the economic gap entirely. Gender inequalities are especially blatant in the workplace. For instance, on average women are more likely to work part-time, be employed in low-paid jobs and not take on management positions [ 2 , 3 ].

There is evidence that gender inequalities in the workplace stem, at least in part, from the discrimination directed against women. Indeed, several studies have documented personal discrimination against women by decision makers (for meta-analyses see [ 4 , 5 ], some of them having more specifically examined the role of the decision makers’ level of sexist attitudes on discriminatory practices. For instance, Masser and Abrams [ 6 ] found in an experimental study that the higher the participants scored in hostile sexism, the more they were likely to recommend a male candidate rather than a female one for a managerial position. In spite of consistent evidence that higher sexism is related to greater bias toward working women [ 7 ], little is known regarding the underlying processes linking sexism to discrimination. This question remains an important one, especially because the persistence of gender discrimination contradicts the anti-discrimination rules promoted in modern societies. In fact, the issue of gender equality in employment has given rise to numerous policies and institutional measures in advanced industrial countries, all aimed at tackling gender discrimination with respect to recruitment, promotion and job assignment. In the USA, for instance, the 1964 Civil Rights Act and the 1963 Equal Pay Act provided the legal foundation for the implementation of anti-discrimination laws within the workplace. The Treaty on the European Union and the Charter of Fundamental Rights of the EU, all contain provisions relating to the promotion of equality between women and men in all areas, and the prohibition of discrimination on any ground, including sex. The member states of the European Union must comply with these provisions [ 8 ]. In this respect, some countries have incorporated legislation on equal treatment of women and men into general anti-discrimination laws (e.g., Austria, Bulgaria, Czech Republic, Germany, Ireland, Poland, Slovenia, Sweden, Great Britain), while other countries have opted for a specific gender equality act (e.g., Spain). Comparable policies have been implemented in the Asian-Pacific area, with countries including gender equality into broad anti-discrimination laws (e.g., Australia), and other countries having passed laws especially dedicated to addressing discrimination against women (e.g., Japan, the Philippines). The purpose of this research is to further explore the psychosocial process involved in the stubborn persistence of gender discrimination in the workplace, using a comparative and cross-sectional perspective of national representative samples.

Psychosocial processes involved in justified discrimination

According to several lines of research [ 9 – 13 ], the expression of prejudice in contexts where social and political anti-discrimination values are prevalent implies justifications. Crandall and Eshleman [ 10 ] defined justifications as “any psychological or social process that can serve as an opportunity to express genuine prejudice without suffering external or internal sanction”. According to social dominance theory, justification of practices that sustain social inequality arises through the endorsement of legitimizing myths [ 13 ]. Moreover, research conducted in the field of system justification theory has extensively documented an increased adherence to legitimizing ideologies (including social stereotypes, meritocracy, political conservatism, etc.) in contexts where motivation to justify unequal social arrangements is heightened [ 14 – 17 ]. Relying on this literature Pereira, Vala and Costa-Lopes [ 18 ] provided evidence of the mediational role of myths about social groups on the prejudice-support for discriminatory measures relationship. Specifically, they demonstrated that the myths according to which immigrants take jobs away from the host society members and increase crime rates mediated the relationship between prejudice and opposition to immigration (see also [ 19 ]). We assume that an equivalent mediational process underlies the justification of gender discrimination in the workplace or, put differently, that the sexism-opposition to women’s career relationship is mediated by legitimizing myths. Glick and Fiske [ 20 ] conceptualised sexism as a multidimensional construct that encompasses hostile and benevolent sexism, both of which having three components: paternalism, gender differentiation and heterosexuality. We suspect that the gender differentiation component of sexism in particular may be related to gender discrimination in the workplace, because the maintenance of power asymmetry through traditional gender roles is at the core of this component [ 20 ]. Accordingly, it is assumed that the higher the endorsement of sexist attitudes regarding gender roles in the family, the higher the opposition to women’s work. In support of this assumption, Glick and Fiske [ 21 ] stated that gender roles are part of the more general interdependence between women and men occurring in the context of family relationships and, importantly, that these traditional, complementary gender roles shape sex discrimination. However, given that the expression of hostility towards women became socially disapproved [ 22 , 23 ] and that gender discrimination in the workplace is subjected to sanctions (see for instance [ 24 ]), the release of sexism with regard to women’s role in the family and women’s professional opportunities may require justification [ 10 , 19 ].

Motherhood myths as a justification for gender discrimination

Compared with other intergroup relations, gender relations present some unique features (e.g., heterosexual interdependence; [ 25 , 26 ] and accordingly comprise specific myths and ideologies aimed at maintaining the traditional system of gender relations [ 27 – 29 ]. For instance, the belief that marriage is the most meaningful and fulfilling adult relationship appears as a justifying myth, on which men and women rely when the traditional system of gender relations is challenged by enhanced gender equality measured at the national level [ 30 ]. Drawing on this literature, we propose that beliefs that imbue women with specific abilities for domestic and parental work ensure that the traditional distribution of gender roles is maintained. In particular, we suggest that motherhood myths serve a justification function regarding gender discrimination against women in the workplace. Motherhood myths include the assumptions that women, by their very nature, are endowed with parenting abilities, that at-home mothers are bonded to their children, providing them unrivalled nurturing surroundings [ 31 , 32 ]. Conversely, motherhood myths pathologised alternative mothering models, depicting employed mothers as neglecting their duty of caring, threatening the family relationships and jeopardizing mother-children bondings (see [ 33 ] for a critical review of these myths). Motherhood myths have the potential to create psychological barriers impairing women’s attempt to seek power in the workplace [ 34 ] and men’s involvement in child care [ 35 – 37 ]. We suggest that beyond their pernicious influence at the individual level of parental choices, motherhood myths might operate more broadly as justifications for gender discrimination regarding career opportunity. This question is of particular relevance given that equal treatment in the workplace appears even more elusive for women with children—the maternal wall [ 38 ] (see also [ 39 – 45 ]). At the same time, recognizing the pervasive justifying function of motherhood myths may help understand the psychosocial barriers faced not only by women who are mothers, but by women as a whole since "women are expected to become mothers sooner or later" (Dambrin & Lambert [ 46 ], p. 494; see also [ 47 ]). Relying on previous work documenting the mediational role of legitimizing myths on the prejudice—discrimination relationship [ 18 , 19 ] we suggest that the myths according to which women pursuing a career threaten the well-being of the family mediates the relationship between sexist attitudes regarding gender roles and opposition to women’s work.

Exploring gender and time as possible moderators of the hypothesized mediation

Besides the test of the main mediational hypothesis, the present research sought to explore time and gender as possible moderators of the assumed relationship between sexism, motherhood myths and discrimination. A review of the historical development of gender equality policies confirms that the implementation of laws and regulations aimed at eliminating gender discrimination in the workplace is a lengthy process (e.g., for the European countries see [ 48 ]; for the USA see [ 49 ]). In fact, although the basic principle of anti-discrimination has been enacted by many countries in the second half of the 20 th century, some measures are still adopted nowadays, such as the obligation for employers to publish information by 2018 about their bonuses for men and women as part of their gender pay gap reporting, a provision recently taken by the UK government. As egalitarian principles have gradually progressed in societies, it is likely that the expression of intergroup bias has become steadily subjected to social sanction. Thus, “as with racism, normative and legislative changes have occurred in many industrialized societies that make it less acceptable to express sexist ideas openly” (Tougas, Brown, Beaton, & Joly, [ 50 ], p. 843; see also [ 51 ]). Accordingly, gender discrimination within organizations became less intense and more ambiguous [ 52 – 54 ]. In line with this reasoning, the use of motherhood myths as a justification for unequal career opportunities may have increased over time. Conversely, it has been suggested that along with the increasing female participation in the labour market over the last decades, a positive attitude regarding the government-initiated women-friendly policies now coexists with an adherence to traditional family values and norms [ 55 ]. There is a possibility that the coexistence of contradictory norms in the same culture may leave some room for the expression of gender bias (i.e., a normative compromise, [ 56 ]), reducing slightly the need to rely on justifications to discriminate against working women. The present research will examine these possibilities by studying the role of motherhood myths on the sexism—discrimination relationship in 1994 and 2012.

Another possible moderator examined in the present study is the respondents' gender. Basically, the reason why people rely on justifications is to express their genuine prejudices without appearing biased. Consistent evidence, however, suggests that the perpetrator’s gender affects people’s perception of sexism towards women: given that sexism is generally conceived as involving a man discriminating against a woman, men are perceived as prototypical of the perpetrator [ 57 , 58 ]. As a consequence, sexist behaviours carried out by males are perceived as more sexist than the same behaviours enacted by females [ 59 , 60 ]. Moreover, the expression of sexism by women may go undetected due to the reluctance of women to recognize that they might be harmed by a member of their own gender group [ 22 ]. Taken together, these findings suggest that a woman is more likely than a man to express sexist bias without being at risk of appearing sexist. In line with this reasoning, one could assume that men need to rely on justifications to discriminate to a greater extent than women do. Alternatively, women expressing sexism against their ingroup members are at risk of being negatively evaluated for violating the prescription of feminine niceness [ 61 , 62 ]. As a consequence, women might be inclined to use justifications to discriminate in order to maintain positive interpersonal evaluations. An additional argument for assuming that women may rely on motherhood myths lies in the system justification motive. According to system justification theory [ 63 , 64 ], people are motivated to defend and justify the status quo, even at the expense of their ingroup. From this perspective, the belief that every group in society possesses some advantages and disadvantages increases the belief that the system is balanced and fair [ 29 , 65 ]. Motherhood myths imbue women with a natural, instinctual and biologically rooted capacity to raise children that men are lacking [ 66 ]. In addition, they convey gender stereotype describing women in positive terms (e.g., considerate, warm, nurturing) allowing a women-are-wonderful perception [ 27 ]. As a consequence, women are likely to rely on motherhood myths to restore the illusion that, despite men structural advantage [ 67 , 68 ], women as a group still possess some prerogatives [ 34 ].

The aim of the present study is to test the main hypothesis (H1) that motherhood myths are a justification that mediates the relationship between sexism and opposition to women’s work following the birth of a child. Additionally, two potential moderators of this mediational process are considered. The present research tests the exploratory hypotheses that (H2) the assumed mediational process is moderated by time and (H3) by participants’ gender. We tested these hypotheses using the Family and Changing Gender Roles module of the International Social Survey Programme [ 69 , 70 ]. This international academic project, based on a representative probabilistic national sample, deals with gender related issues, including attitudes towards women’s employment and household management. Hence this database enables a test of the proposed mediational model on a large sample of female and male respondents and data gathered 18 years apart.

We used the 2012 and 1994 waves of the ISSP Family and Changing Gender Roles cross-national survey [ 69 , 70 ]. The ISSP published fully anonymized data so that individual survey participants cannot be identified. The two databases slightly differed regarding the involved countries, some of which did not participate in the two survey waves. In order to maintain consistency across the analyses, we selected 18 countries that participated in both survey waves (i.e., Austria, Australia, Bulgaria, Canada, Czech Republic, Germany, Great Britain, Ireland, Israel, Japan, Norway, Philippines, Poland, Russia, Slovenia, Spain, Sweden and the USA). The data file for the 2012 survey wave included 24222 participants (54.4% female participants), mean age = 49.38, SD = 17.54, and the data file for the 1994 survey wave included 27410 participants (54.4% female participants), mean age = 44.26, SD = 17.07.

The main variables used in this study are the following:

One indicator was used to capture sexism: “A man's job is to earn money; a woman's job is to look after the home and family”. This item taps into the gender differentiation component of sexism [ 20 , 25 ]. Participants answered on a 5 point likert scale ranging from 1 = strongly agree to 5 = strongly disagree. Data was recoded so that the higher scores reflected higher sexism.

Motherhood myths.

Two indicators were used that capture the myths about the aversive consequence of mother’s work for her child and the family: “A preschool child is likely to suffer if his or her mother works” and “All in all, family life suffers when the woman has a full-time job”. Participants answered on a 5 point likert scale ranging from 1 = strongly agree to 5 = strongly disagree. Data was recoded so that the higher scores reflected higher endorsement of motherhood myths.

Opposition to women’s career.

Two indicators were used to capture the opposition to women’s professional career following the birth of a child: “Do you think that women should work outside the home full-time, part-time or not at all when there is a child under school age?” and “Do you think that women should work outside the home full-time, part-time or not at all after the youngest child starts school?” Participants answered on a scale ranging from 1 = work full time, 2 = work part-time, 3 = stay at home.

In addition, the first step of our analyses involved the following control variables: participant’s gender and age, partnership status, educational level, subjective social status, attendance of religious services and political orientation.

The following section presents the results of a four-step analysis: The first step consists of a preliminary hierarchical regression analysis to establish the respective contributions of demographical variables, sexism and motherhood myths to opposition to women’s work. The second step is dedicated to a test of the construct validity of the proposed measurement model using Confirmatory Factor Analyses. The third step involves a test of the hypothesized mediation. Finally, the last step is a test of the hypothesized moderated mediations.

Step 1: Hierarchical regression analysis

Inspection of the correlation matrix ( Table 1 ) indicates that all the correlations are positive, ranging from moderate to strong. The pair of items measuring motherhood myths presents the strongest correlation ( r (48961) = .633), followed by the pair of items measuring opposition to women’s career ( r (45178) = .542).

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https://doi.org/10.1371/journal.pone.0190657.t001

We conducted a hierarchical regression analysis to establish the respective contributions of demographical variables, sexism and motherhood myths to opposition to women’s work. In block 1, participant’s gender (male = -1, female = 1) and partnership (no partner = -1, partner = 1) were entered together with standardized scores of age, years of schooling, subjective social status, attendance of religious services and political orientation. Block 2 included sexism, the myths about the aversive consequence of mother’s work for her child and for family (all standardized). Predictors in block 1 accounted for 9% of the variance, F (7, 10140) = 157.89, p < .001. The analysis revealed the significant effects of participant’s gender ( B = -.033, SE = .006, p < .001), age ( B = .058, SE = .006, p < .001), years of schooling ( B = -.135, SE = .007, p < .001), subjective social status ( B = -.057, SE = .007, p < .001), religiosity ( B = .076, SE = .006, p < .001) and political orientation ( B = .04, SE = .006, p < .001). Partnership was unrelated to opposition to women’s career ( B = .002, SE = .006, p = .77). Taken together the results indicate that the higher the time of education and the subjective social status, the lower the opposition to women’s work. Conversely, the higher the age, religiosity and political conservatism, the higher the opposition to women’s work. Finally, results indicate that opposition to women’s work is more pronounced amongst men than amongst women. When entered in block 2, sexism and motherhood myths accounted for an additional 18% of the variance, indicating that these variables significantly improved the model’s ability to predict opposition to women’s work, over and above the contributions of gender, partnership, education, social status, religiosity and political orientation (Δ R 2 = .18), Δ F (3, 10137) = 854.04, p < .001. Specifically, the analysis revealed the significant effects of sexism ( B = .151, SE = .006, p < .001), myth about the aversive consequence of mother’s work for her child ( B = .10, SE = .007, p < .001) and myth about the aversive consequence of women’s work for family ( B = .09, SE = .007, p < .001). It should be noted that the effect of participant’s gender virtually disappeared after controlling for sexism and motherhood myths ( Table 2 ). In addition, we performed this hierarchical regression analysis separately for the two waves and consistently found that the variables of our model (sexism and the motherhood myths) explained more variance than the demographical variables.

https://doi.org/10.1371/journal.pone.0190657.t002

Step 2: Confirmatory factor analyses

We conducted a CFA to check the construct validity of the proposed measurement model. CFA and subsequent analyses were all performed using R. 3.4.1 and the Lavaan package [ 71 ]. The loading of the single indicator of the sexism variable and the loading of the first indicator of the motherhood myths and opposition variables were constrained to 1.00 [ 72 ], and the three variables were allowed to correlate. Results show a good fit to the data, χ 2 (3, N = 42997) = 400.36, p < .001, CFI = .993, RMSEA = .05 [90% CI = .05, .06], SRMR = .01, AIC = 540804. In addition, we estimated an alternative model in which all items loaded on a unique latent variable. This alternative model shows a poorer fit to the data, χ 2 (5, N = 42997) = 8080.28, p < .001, CFI = .867, RMSEA = .19 [90% CI = .19, .19], SRMR = .07, AIC = 548480. The comparison of the two models indicates that the proposed measurement model fits the data better than the alternative one, Δ χ 2 (2, 42997) = 7679.9, p < .001. We repeated this comparison in each country and results confirm that the proposed measurement model fits better in all countries (see S1 Table for comparative test of the goodness of fit of the hypothesized measurement model vs. alternative measurement model in each country).

We tested the measurement invariance of the CFA model across the two survey waves. To do this, we conducted a model comparison to test for configural and metric invariances. Results indicate that the configural invariance can be retained, χ 2 (6, N = 42997) = 513.05, p < .001, CFI = .991, RMSEA = .06 [90% CI = .05, .06], SRMR = .01, AIC = 537580. When constraining the loadings to be equal across waves fit indices remain satisfactory, χ 2 (8, N = 42997) = 679.58, p < .001, CFI = .989, RMSEA = .06 [90% CI = .05, .06], SRMR = .02, AIC = 537743. The change in CFI is below the cutpoint of .01, indicating that the metric invariance can be retained and that further comparisons of the relationships between constructs across survey waves can be performed [ 73 , 74 ]. Furthermore, we repeated this comparison in each country and results support the configural invariance of the CFA model across survey waves in all countries. In addition, the full metric invariance is obtained in all but three countries—Poland, Slovenia and the USA. In these countries, the CFIs are larger than the cutpoint of .01, indicating a lack of full metric invariance. Nonetheless, we were able to retain a partial metric invariance of the CFA model across the survey waves by setting free one non-invariant loading [ 75 ], (see S2 Table for the test of the invariance of the measurement model across survey waves by country).

We tested the measurement invariance of the CFA model across gender groups using the same procedure as for the test of the measurement invariance across survey waves. The baseline model constraining the factor structure to be equal in the two gender groups shows good fit to the data, χ 2 (6, N = 42943) = 440.95, p < .001, CFI = 0.993, RMSEA = .05 [90% CI = .05, .06], SRMR = .01, AIC = 539573, indicating that the configural invariance is achieved for the two groups. Then we fitted a more restricted model in which the factor loadings were constrained to be equal across groups. This model allows testing for the metric invariance (equal loadings) of the model across gender. Once again, the results indicate that this constrained model show good fit to the data, χ 2 (8, N = 42943) = 469.14, p < .001, CFI = 0.992, RMSEA = .05 [90% CI = .04, .05], SRMR = .01, AIC = 539598. Furthermore, the Δ CFI is below the cutpoint of .01, indicating that the metric invariance can be retained [ 75 ]. This result confirms that cross gender comparisons of the relationships between constructs can reasonably be performed. Furthermore, we repeated this procedure in each country. Once again, the Δ CFIs are below the cutpoint of .01, indicating that the configural invariance of the CFA model across gender groups is achieved in all countries (see S3 Table for the test of the invariance of the measurement model across gender groups by country).

Step 3. Mediation analysis

Overview of the analysis strategy..

This study main hypothesis is that (H1) the more people hold sexist attitude regarding gender roles, the more they endorse motherhood myths, which in turn enhances the opposition to women’s career after the birth of a child. In order to test this assumption, we ran mediational analyses using structural equation modelling. First, we examined the goodness of fit of the hypothesized mediational model and compared it with the goodness of fit of two alternative models. In the first alternative model, motherhood myths predict sexism that, in turn, predicts opposition. In the second alternative model, opposition to women’s career predicts motherhood myths. After having established that the hypothesized model adequately fit the data, we examined the coefficients for the hypothesized relationships between variables.

Goodness of fit of the models.

Inspection of the fit indices indicates that the hypothesized model fits the data better than the first alternative model in 16 out of the 18 analysed countries ( Table 3 ). Thus, in these countries the data is better accounted for by a model stating motherhood myths as a mediator of the sexism-opposition to women’s career relationship, rather than by a model stating sexism as a mediator of the myths-opposition to women’s career relationship. The comparison of the fit indices indicates that the two models fit the data to almost the same extent in the two remaining countries (i.e., Czech Republic, and Philippines). Finally, the second alternative model—where opposition to women’s career predicted motherhood myths and sexism—shows very poor fit to the data in all countries. This result suggests that endorsement of motherhood myths is not a mere consequence of discrimination.

https://doi.org/10.1371/journal.pone.0190657.t003

Test of the relationships between variables.

The goodness of fit of the proposed mediational model having been established in 16 countries out of 18, we next examined the coefficients for the hypothesized relationships in these countries. Table 4 shows the results of the mediation analysis in the 16 retained countries. The total effect of sexism on opposition to women’s career is positive and significant in all countries. The direct effect is reduced in all countries when controlling for the indirect effect through motherhood myths. As recommended in the literature, the indirect effects were subjected to follow-up bootstrap analyses using 1000 bootstrapping resamples [ 76 ]. The null hypothesis is rejected and the indirect effect is considered significant if the 95% confidence intervals (CI) do not include zero. All bias corrected 95% CI for the indirect effect excluded zero, indicating that in line with H1, endorsement of motherhood myths is a significant mediator of the relationship between sexism and opposition to women’s career in all countries.

https://doi.org/10.1371/journal.pone.0190657.t004

In order to provide an overview of the proposed mediational model, we next present the analyses conducted on the total of the 16 countries retained. The hypothesized mediational model shows acceptable fit to the data, χ 2 (4, N = 38178) = 971.09, p < .001, CFI = .983, RMSEA = .08 [90% CI = .07, .08], SRMR = .04, AIC = 473476. Inspection of the fit indices of the first alternative model where endorsement of motherhood myths predicted sexism that, in turn, predicted opposition confirms that this alternative model shows poorer fit to the data than the proposed model, χ 2 (4, N = 38178) = 7583.1, p < .001, CFI = .870, RMSEA = .22 [90% CI = .21, .22], SRMR = .13, AIC = 480088. The second alternative model, where opposition to women’s career predicted motherhood myths shows poor fit to the data, χ 2 (5, N = 38178) = 14224.61, p < .001, CFI = .756, RMSEA = .27 [90% CI = .26, .27], SRMR = .21, AIC = 486728, and accordingly fits the data less well than the proposed mediational model, Δ χ 2 (1, 38178) = 13254 p < .001. As can be seen in Fig 1 , the standardized regression coefficient for the direct effect of sexism on opposition to women’s career is significant ( β = .16, p < .001). In addition, the unstandardized estimate for the indirect effect excludes zero (.13, SE = 0.003, bias corrected 95% CI [.12, .13]) and, therefore, is significant. Taken together, analyses conducted on the whole sample, as well as on each country separately, support our main assumption that endorsement of motherhood myths is a significant mediator of the relationship between sexism and opposition to women’s career.

The coefficient in parentheses represents parameter estimate for the total effect of prejudice on opposition to women’s career. *** p < .001.

https://doi.org/10.1371/journal.pone.0190657.g001

Step 4. Moderated mediation analyses

Indirect effect through survey waves..

The moderated mediation model was estimated using a multiple group approach. This model exhibits good fit to the data, χ 2 (6, N = 38178) = 438.88, p < .001, CFI = .992, RMSEA = .06 [90% CI = .05, .06], SRMR = .01. The standardized coefficients for the total effect are .50 in the 2012 survey, and .52 in the 1994 survey. The unstandardized estimates for the indirect effect is .10, SE = 0.003, bias corrected 95% CI [.10, .11] in the 2012 survey, and .11, SE = 0.003, bias corrected 95% CI [.10, .11] in the 1994 survey. The intervals do not include zero, indicating that motherhood myths are a significant mediator of the relationship between sexism and opposition to women’s career in both survey waves. The difference between the indirect effect in 2012 and 1994 is not significant (-.003, SE = 0.004, bias corrected 95% CI [.-.01, .00]). We repeated the moderated mediation analysis in each country. As can be seen in Table 5 , the indirect effect reaches significance in each survey wave in all countries. The indirect effect is not moderated by the survey year, except in Great Britain where the indirect effect, although still significant, decreased between 1994 and 2012, and Bulgaria, Poland, and Russia where the indirect effect slightly increased between 1994 and 2012.

https://doi.org/10.1371/journal.pone.0190657.t005

Indirect effect as a function of the respondents’ gender.

The moderated mediation model exhibits good fit to the data, χ 2 (6, N = 38124) = 402.46, p < .001, CFI = .993, RMSEA = .06 [90% CI = .05, .06], SRMR = .01. The total effect of sexism on opposition to women’s career is positive and significant for both men ( β = .52, p < .001) and women ( β = .50, p < .001). The standardized indirect effect of sexism on opposition to women’s career through motherhood myths is .27 in the male subsample, and .29 in the female subsample. The unstandardized estimates for the indirect effect is .11, SE = 0.003, bias corrected 95% CI [.10, 12] in the male sample, and .10, SE = 0.003, bias corrected 95% CI [.09, .10] in the female sample. The intervals do not include zero, indicating that motherhood myths are a significant mediator of the relationship between sexism and opposition to women’s career among both men and women respondents. The difference between the indirect effect among men and women is not statistically significant (.01, SE = 0.004, bias corrected 95% CI [.00, .01]). We repeated this analysis in each country separately (see Table 6 ). Results confirm that the indirect effect of sexism on opposition to women’s career through motherhood myths is not moderated by the respondents’ gender in 15 out of the 16 countries. The only exception is Poland. In this country, the indirect effect is stronger for the female than for the male respondents.

https://doi.org/10.1371/journal.pone.0190657.t006

Using a large representative sample of respondents from various countries the present research documented a psychosocial process of justification of discrimination against working women with children. As a preliminary step, hierarchical regression analysis established that sexism and motherhood myths predict opposition to women’s work, over and above gender, partnership, education, social status, religiosity and political orientation. Furthermore, structural equation modellings on the whole sample, as well as on each country separately, confirmed our main hypothesis that endorsement of motherhood myths mediates the relationship between sexism and opposition to women’s career following a birth. In addition, test of the moderated mediation indicated that the indirect effect reaches significance in each survey wave in almost all countries examined without substantial difference. Only in Bulgaria, Poland, and Russia did the indirect effect slightly increase between 1994 and 2012, suggesting that motherhood myths is more a justification for the expression of sexism nowadays than in the late 20 th century. Great Britain shows a reverse pattern with a slight decrease of the indirect effect between the two waves. However, besides these minor variations, it should be noted that motherhood myths remain a significant mediator of the sexism-opposition to women’s career relationship in all countries. The present research also considered participants' gender as a potential moderator of the indirect effect, and results indicated that the process of justification of discrimination against working women does not differ as a function of the respondents' gender. The only exception to this finding is Poland where the indirect effect is indeed stronger among women than among men. An examination of the specific features of female employment in this country sheds some light on this result. Young women in Poland are better educated than young men and are more likely to have permanent employment than men [ 77 ]. At the same time however, working women spend on average two and a half hours per day on unpaid work more than men—which is reflected by the fact that more than 1 in 3 women reduce their paid hours to part-time, while only 1 in 10 men do the same—and are predominant users of parental leave [ 3 ]. It is noteworthy that reduced working hours (and long periods of leave) hinders female career progression through less training, fewer opportunities for advancement, occupational segregation, and lower wages [ 78 , 79 ]. Accordingly, in Poland women earn 9% less than men (one of the lowest gender pay gap in OECD) but the pay gap reaches 22% by presence of children (above the OECD average of 16%; [ 77 ]). The fact that women appear even more inclined than men to rely on motherhood myths to justify gender discrimination is consistent with a system justification perspective [ 63 ]. Drawing on the logic of cognitive dissonance theory, system justification theory in its strong form posits that members of disadvantaged groups may be even more likely than members of advantaged groups to support existing social inequalities [ 64 ]. The rational is that members of disadvantaged groups would experience psychological discomfort stemming from the concurrent awareness of their ingroup's inferiority within the system, and of their ingroup's contribution to that system. Justification of the status quo would therefore reduce dissonance [ 80 ]. The finding that women strongly rely on motherhood myths to justify gender discrimination precisely in a country with strong motherhood penalty can be regarded as an expression of this system justification motive.

The present research sheds new light on the effect of macrolevel inequality on the justification of discrimination, and more broadly on the process of legitimation of gender inequalities [ 9 , 81 ]. In a recent study, Yu and Lee [ 82 ] found a negative association between women’s relative status in society and support for gender equality at home. More specifically, the authors found that although respondents in countries with smaller gender gaps express greater support for women’s participation in the labour force, they still exhibit less approval for egalitarian gender roles within the household, in particular regarding the share of domestic chores and childcare. As an explanation, the authors argued that the less traditional the gender division of labour is in a society, the more people need to express their freedom of maintaining these roles and to defend the gender system, leading to the endorsement of gender differentiation in the private sphere. However, the present research allows an alternative explanation for this seemingly paradoxical finding to be suggested. At a macrolevel, higher gender equality conveys strong suppressive factors (which reduce the expression of prejudice) by demonstrating that the society promotes egalitarianism between women and men. In parallel, the gender specialization in the division of the household responsibilities and especially regarding childcare provides a strong justifying factor (which releases prejudice) by emphasising essential differences between gender groups [ 26 ]. Thus, the counterintuitive finding that the more egalitarian a society is, the less people support gender equality at home may indeed reflect an attempt to justify the release of genuine sexism. Conversely, it is likely that a less egalitarian society brings with it some degree of tolerance towards gender discrimination, reducing the need to rely on justifications to express sexism. A closer look at our results regarding Norway and Japan supports this view. Norway and Japan appears as especially contrasted regarding gender equality, in particular with regard to economic participation and opportunity [ 1 ]. According to the World Economic Forum, Norway has the second smallest gender gap in the world. In addition, gender equality promotion is frequently mobilised both in political debates and in mainstream society [ 55 ]. For its part, Japan ranks 101 st on the overall gender gap index, which makes Japan well below average compared to other advanced industrial countries [ 83 ]. Besides this gender gap, consistent research reports a unique trivialisation of anti-gender equality discourses in the media [ 84 ] and of gender-based discriminatory behaviours in the workplace, including sexual harassment [ 85 ]. Comparing the strength of the indirect effect of sexism on opposition to women’s career through motherhood myths in these two countries ( Table 4 ), it is noteworthy that the coefficient is larger in Norway than in Japan. This result gives support to the assumption that macrolevel gender (in)equality affects the psychological process of justification at the individual level. Future studies should clarify how macrolevel inequalities impact societal norms, which in turn influence legitimation processes.

It is also worth noting that the justifying function of motherhood myths is established in all analysed countries despite some notable differences between parental leaves policies and practices. For instance, the United States are the only OECD country to offer no nationwide entitlement to paid leave, neither for mothers nor for fathers [ 86 ]. On the other hand, the Nordic nations, with Norway and Sweden in the lead, are in the vanguard of progressive policy-making regarding shared parental leave entitlement: Sweden was the first country in the world in 1974 to offer fathers the possibility of taking paid parental leave, quickly joined by Norway in 1978 [ 87 ]. More recently in 2007, Germany introduced a new law aiming at encouraging shared parental leave. In practice, the length of the financial support for parental leave can increase from 12 to 14 months provided that fathers use the parental benefit for at least 2 months. Recent research aiming at investigating whether German men who take parental leave are judged negatively in the workplace revealed that, in contrast with women who experience penalty for motherhood [ 40 ], fathers do not face backlash effect when they take a long parental leave [ 88 ]. The authors concluded that "gender role attitudes have changed". Tempering this view, the present study indicates that even in countries promoting incentives for fathers to take parental leave, motherhood myths—and specifically the belief that mother's work threatens the family—are still a justification for gender discrimination in the workplace. With regard to practices, it should be noted that shared parental leave policies, whose purpose is to foster gender equality in the labor market, often fail to meet this objective, with the majority of fathers actually taking the minimum length of leave entitlement, or no parental leave at all, and the majority of mothers still facing the majority of childcare [ 88 ]. Once again, more research is needed to document the process of mutual influences between changing family policies and the maintenance of the gender status quo via justifying beliefs.

Limitations and future directions

Although the hypothesized mediational process is supported by the data, and is in line with previous experimental findings [ 19 ], conclusion regarding causality are necessarily limited due to the correlational nature of the research. We hope that these preliminary findings will open the way to experimental studies allowing for a conclusion on the direction of causality between variables and the further documenting of the behavioural consequences of the endorsement of motherhood myths. For instance, future studies should consider the extent to which motherhood myths interact with organizational norms to constrain the hiring and promotion of women. Castilla and Benard [ 89 ] showed that when an organization explicitly values meritocracy, managers favour a male employee over an equally qualified female employee. One explanation for this seemingly paradoxical results lies in the legitimation function of meritocracy [ 17 ] which is likely to release the expression of sexism. We suggest that when organizations promote egalitarian norms, or put differently, when organizations set suppression factors, then motherhood myths may serve as a justification for unequal gender treatment regarding career outcomes.

Due to constraints related to the availability of data in the ISSP base, only one indicator was used to capture sexism. This can be regarded as a limitation providing that sexism is typically defined as a complex construct [ 20 ]. We argue that measuring the gender differentiation component of sexism through a single item represents a valid approach, as suggested by previous research indicating that single-item measures may be as reliable as aggregate scales [ 90 – 94 ]. However, using a multiple-item measure of sexism in future studies would provide a more comprehensive examination of the relations between the different components of sexism and opposition to gender equality in the workplace.

The present research focused on opposition to mothers' work as an indicator of gender discrimination. However, evidence suggests that motherhood myths may justify discrimination towards women as a whole rather than mothers only. First, as previously mentioned social roles create gender expectations [ 95 ] so that all women are expected to become mothers [ 47 ]. Furthermore, research using implicit association test indicate that people automatically associate women with family role [ 96 ]. As a consequence, it is plausible that employers rely on motherhood myths to discriminate against women in general regarding recruitement, performance evaluation, and rewards, arguing that women will sooner or later be less involved in work and less flexible for advancement than men [ 97 ]. This justification is compatible with the employers' reluctance to hire women and promote them to the highest positions even in the absence of productivity differences [ 98 ].

Practical implications

In this study we were able to document that motherhood myths are a widespread justification for gender discrimination in the workplace, including in countries with anti-discrimination laws and advanced family policies. From this regard, the present findings help understand the paradoxical effects of family-friendly policies on women's economic attainment. Mandel and Semyonov [ 99 ], using data from 20 countries, found evidence that family policies aimed at supporting women's economic independence, and including provision of childcare facilities and paid parental leaves, increase rather than decrease gender earning gaps. This unexpected effect is due to the fact that family policies are disproportionally used by mothers rather than fathers, with the consequence that mothers are concentrated in part-time employment, female-typed occupations, yet underrepresented in top positions. The authors concluded that "there are distinct limits to the scope for reducing gender wage inequality in the labor market as long as women bear the major responsibility for household duties and child care" (p. 965). We would add that there are strong barriers to the scope for attaining gender equality at home as long as motherhood myths are uncritically accepted and used as justification for unequal gender arrangements. Recent works provided evidence of the efficiency of interventions aimed at reducing sexist beliefs [ 100 ] and at recognizing everyday sexism [ 101 ]. In the same vain, interventions aimed at informing people that motherhood myths are socially constructed and maintained [ 33 ], and that they affect women's advancement and fathers' involvement [ 35 ], would represent a first step towards the reduction of discrimination by depriving individuals of a justification for gender inequalities.

The present research builds on and extends past findings by demonstrating that men and women rely on the belief that women’s work threatens the well-being of youth and family to justify discrimination against working women. If, at an individual level, this process allows discrimination to be exhibited without appearing prejudiced [ 10 ], at the group and societal levels, such a process may contribute to the legitimation and reinforcement of the hierarchical power structure [ 63 ]. By documenting a pervasive process by which people invoke motherhood myths to hinder women’s economic participation, the present research emphasizes the need to be vigilant about any attempts to promote a return to traditional gender roles, an issue of central importance given the contemporary rollback of women’s rights in advanced industrial countries [ 102 ].

Supporting information

S1 table. comparative test of the goodness of fit of the hypothesized measurement model vs. alternative measurement model..

All differences are significant at p < .001.

https://doi.org/10.1371/journal.pone.0190657.s001

S2 Table. Test of the invariance of the measurement model across survey waves by country.

In Poland and Slovenia partial metric invariance of the measurement model was attained by setting free the loading of the item “ Do you think that women should work outside the home full-time , part-time or not at all after the youngest child starts school ?” on the “opposition” latent variable. This partly constrained model show good fit indices in Poland, χ 2 (7, N = 2248) = 36.18, p = .006, CFI = .990, RMSEA = .06 [90% CI = .04, .08], and Slovenia, χ 2 (7, N = 1867) = 12.92, p = .058, ns , CFI = .999, RMSEA = .03 [90% CI = .00, .05]. In the USA, partial metric invariance of the measurement model was attained by setting free the loading of the item “ All in all , family life suffers when the woman has a full-time job ” on the “motherhood myths” latent variable, χ 2 (7, N = 2117) = 11.08, p = .069, ns , CFI = .999, RMSEA = .02 [90% CI = .00, .04].

https://doi.org/10.1371/journal.pone.0190657.s002

S3 Table. Test of the invariance of the measurement model across gender groups by count.

https://doi.org/10.1371/journal.pone.0190657.s003

S1 Supplementary Information. Additional details concerning the way the research was conducted.

https://doi.org/10.1371/journal.pone.0190657.s004

Acknowledgments

The authors are grateful to Virginie Bonnot, Cícero Pereira, and several anonymous reviewers for their helpful comments on earlier versions of this paper.

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REVIEW article

Gender inequalities in the workplace: the effects of organizational structures, processes, practices, and decision makers’ sexism.

• Department of Psychology, University of Guelph, Guelph, ON, Canada

Gender inequality in organizations is a complex phenomenon that can be seen in organizational structures, processes, and practices. For women, some of the most harmful gender inequalities are enacted within human resources (HRs) practices. This is because HR practices (i.e., policies, decision-making, and their enactment) affect the hiring, training, pay, and promotion of women. We propose a model of gender discrimination in HR that emphasizes the reciprocal nature of gender inequalities within organizations. We suggest that gender discrimination in HR-related decision-making and in the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices. This includes leadership, structure, strategy, culture, organizational climate, as well as HR policies. In addition, organizational decision makers’ levels of sexism can affect their likelihood of making gender biased HR-related decisions and/or behaving in a sexist manner while enacting HR practices. Importantly, institutional discrimination in organizational structures, processes, and practices play a pre-eminent role because not only do they affect HR practices, they also provide a socializing context for organizational decision makers’ levels of hostile and benevolent sexism. Although we portray gender inequality as a self-reinforcing system that can perpetuate discrimination, important levers for reducing discrimination are identified.

Introduction

The workplace has sometimes been referred to as an inhospitable place for women due to the multiple forms of gender inequalities present (e.g., Abrams, 1991 ). Some examples of how workplace discrimination negatively affects women’s earnings and opportunities are the gender wage gap (e.g., Peterson and Morgan, 1995 ), the dearth of women in leadership ( Eagly and Carli, 2007 ), and the longer time required for women (vs. men) to advance in their careers ( Blau and DeVaro, 2007 ). In other words, workplace discrimination contributes to women’s lower socio-economic status. Importantly, such discrimination against women largely can be attributed to human resources (HR) policies and HR-related decision-making. Furthermore, when employees interact with organizational decision makers during HR practices, or when they are told the outcomes of HR-related decisions, they may experience personal discrimination in the form of sexist comments. Both the objective disadvantages of lower pay, status, and opportunities at work, and the subjective experiences of being stigmatized, affect women’s psychological and physical stress, mental and physical health ( Goldenhar et al., 1998 ; Adler et al., 2000 ; Schmader et al., 2008 ; Borrel et al., 2010 ),job satisfaction and organizational commitment ( Hicks-Clarke and Iles, 2000 ), and ultimately, their performance ( Cohen-Charash and Spector, 2001 ).

Within this paper, we delineate the nature of discrimination within HR policies, decisions, and their enactment, as well as explore the causes of such discrimination in the workplace. Our model is shown in Figure 1 . In the Section “Discrimination in HR Related Practices: HR Policy, Decisions, and their Enactment,” we explain the distinction between HR policy, HR-related decision-making, and HR enactment and their relations to each other. Gender inequalities in HR policy are a form of institutional discrimination. We review evidence of institutional discrimination against women within HR policies set out to determine employee selection, performance evaluations, and promotions. In contrast, discrimination in HR-related decisions and their enactment can result from organizational decision makers’ biased responses: it is a form of personal discrimination. Finally, we provide evidence of personal discrimination against women by organizational decision makers in HR-related decision-making and in the enactment of HR policies.

FIGURE 1. A model of the root causes of gender discrimination in HR policies, decision-making, and enactment.

In the Section “The Effect of Organizational Structures, Processes, and Practices on HR Practices,” we focus on the link between institutional discrimination in organizational structures, processes, and practices that can lead to personal discrimination in HR practices (see Figure 1 ). Inspired by the work of Gelfand et al. (2007) , we propose that organizational structures, processes, and practices (i.e., leadership, structure, strategy, culture, climate, and HR policy) are interrelated and may contribute to discrimination. Accordingly, gender inequalities in each element can affect the others, creating a self-reinforcing system that can perpetuate institutional discrimination throughout the organization and that can lead to discrimination in HR policies, decision-making, and enactment. We also propose that these relations between gender inequalities in the organizational structures, processes, and practices and discrimination in HR practices can be bidirectional (see Figure 1 ). Thus, we also review how HR practices can contribute to gender inequalities in organizational structures, processes, and practices.

In the Section “The Effect of Hostile and Benevolent Sexism on How Organizational Decision Makers’ Conduct HR Practices,” we delineate the link between organizational decision makers’ levels of sexism and their likelihood of making gender-biased HR-related decisions and/or behaving in a sexist manner when enacting HR policies (e.g., engaging in gender harassment). We focus on two forms of sexist attitudes: hostile and benevolent sexism ( Glick and Fiske, 1996 ). Hostile sexism involves antipathy toward, and negative stereotypes about, agentic women. In contrast, benevolent sexism involves positive but paternalistic views of women as highly communal. Whereas previous research on workplace discrimination has focused on forms of sexism that are hostile in nature, we extend this work by explaining how benevolent sexism, which is more subtle, can also contribute in meaningful yet distinct ways to gender discrimination in HR practices.

In the Section “The Effect of Organizational Structures, Processes, and Practices on Organizational Decision Makers’ Levels of Hostile and Benevolent Sexism,” we describe how institutional discrimination in organizational structures, processes, and practices play a critical role in our model because not only do they affect HR-related decisions and the enactment of HR policies, they also provide a socializing context for organizational decision makers’ levels of hostile and benevolent sexism. In other words, where more institutional discrimination is present, we can expect higher levels of sexism—a third link in our model—which leads to gender bias in HR practices.

In the Section “How to Reduce Gender Discrimination in Organizations,” we discuss how organizations can reduce gender discrimination. We suggest that, to reduce discrimination, organizations should focus on: HR practices, other closely related organizational structures, processes, and practices, and the reduction of organizational decision makers’ level of sexism. Organizations should take such a multifaceted approach because, consistent with our model, gender discrimination is a result of a complex interplay between these factors. Therefore, a focus on only one factor may not be as effective if all the other elements in the model continue to promote gender inequality.

The model we propose for understanding gender inequalities at work is, of course, limited and not intended to be exhaustive. First, we only focus on women’s experience of discrimination. Although men also face discrimination, the focus of this paper is on women because they are more often targets ( Branscombe, 1998 ; Schmitt et al., 2002 ; McLaughlin et al., 2012 ) and discrimination is more psychologically damaging for women than for men ( Barling et al., 1996 ; Schmitt et al., 2002 ). Furthermore, we draw on research from Western, individualistic countries conducted between the mid-1980s to the mid-2010s that might not generalize to other countries or time frames. In addition, this model derives from research that has been conducted primarily in sectors dominated by men. This is because gender discrimination ( Mansfield et al., 1991 ; Welle and Heilman, 2005 ) and harassment ( Mansfield et al., 1991 ; Berdhal, 2007 ) against women occur more in environments dominated by men. Now that we have outlined the sections of the paper and our model, we now turn to delineating how gender discrimination in the workplace can be largely attributed to HR practices.

Discrimination in HR Related Practices: HR Policy, Decisions, and their Enactment

In this section, we explore the nature of gender discrimination in HR practices, which involves HR policies, HR-related decision-making, and their enactment by organizational decision makers. HR is a system of organizational practices aimed at managing employees and ensuring that they are accomplishing organizational goals ( Wright et al., 1994 ). HR functions include: selection, performance evaluation, leadership succession, and training. Depending on the size and history of the organization, HR systems can range from those that are well structured and supported by an entire department, led by HR specialists, to haphazard sets of policies and procedures enacted by managers and supervisors without formal training. HR practices are critically important because they determine the access employees have to valued reward and outcomes within an organization, and can also influence their treatment within an organization ( Levitin et al., 1971 ).

Human resource practices can be broken down into formal HR policy, HR-related decision-making, and the enactment of HR policies and decisions. HR policy codifies practices for personnel functions, performance evaluations, employee relations, and resource planning ( Wright et al., 1994 ). HR-related decision-making occurs when organizational decision makers (i.e., managers, supervisors, or HR personnel) employ HR policy to determine how it will be applied to a particular situation and individual. The enactment of HR involves the personal interactions between organizational decision makers and job candidates or employees when HR policies are applied. Whereas HR policy can reflect institutional discrimination, HR-related decision-making and enactment can reflect personal discrimination by organizational decision makers.

Institutional Discrimination in HR Policy

Human resource policies that are inherently biased against a group of people, regardless of their job-related knowledge, skills, abilities, and performance can be termed institutional discrimination. Institutional discrimination against women can occur in each type of HR policy from the recruitment and selection of an individual into an organization, through his/her role assignments, training, pay, performance evaluations, promotion, and termination. For instance, if women are under-represented in a particular educational program or a particular job type and those credentials or previous job experience are required to be considered for selection, women are being systematically, albeit perhaps not intentionally, discriminated against. In another example, there is gender discrimination if a test is used in the selection battery for which greater gender differences emerge, than those that emerge for job performance ratings ( Hough et al., 2001 ). Thus, institutional discrimination can be present within various aspects of HR selection policy, and can negatively affect women’s work outcomes.

Institutional discrimination against women also occurs in performance evaluations that are used to determine organizational rewards (e.g., compensation), opportunities (e.g., promotion, role assignments), and punishments (e.g., termination). Gender discrimination can be formalized into HR policy if criteria used by organizational decision makers to evaluate job performance systematically favor men over women. For instance, “face time” is a key performance metric that rewards employees who are at the office more than those who are not. Given that women are still the primary caregivers ( Acker, 1990 ; Fuegen et al., 2004 ), women use flexible work arrangements more often than men and, consequently, face career penalties because they score lower on face time ( Glass, 2004 ). Thus, biased criteria in performance evaluation policies can contribute to gender discrimination.

Human resource policies surrounding promotions and opportunities for advancement are another area of concern. In organizations with more formal job ladders that are used to dictate and constrain workers’ promotion opportunities, women are less likely to advance ( Perry et al., 1994 ). This occurs because job ladders tend to be divided by gender, and as such, gender job segregation that is seen at entry-level positions will be strengthened as employees move up their specific ladder with no opportunity to cross into other lines of advancement. Thus, women will lack particular job experiences that are not available within their specific job ladders, making them unqualified for advancement ( De Pater et al., 2010 ).

In sum, institutional discrimination can be present within HR policies set out to determine employee selection, performance evaluations, and promotions. These policies can have significant effects on women’s careers. However, HR policy can only be used to guide HR-related decision-making. In reality, it is organizational decision-makers, that is, managers, supervisors, HR personnel who, guided by policy, must evaluate job candidates or employees and decide how policy will be applied to individuals.

Personal Discrimination in HR-Related Decision-Making

The practice of HR-related decision-making involves social cognition in which others’ competence, potential, and deservingness are assessed by organizational decision makers. Thus, like all forms of social cognition, HR-related decision-making is open to personal biases. HR-related decisions are critically important because they determine women’s pay and opportunities at work (e.g., promotions, training opportunities). Personal discrimination against women by organizational decision makers can occur in each stage of HR-related decision-making regarding recruitment and selection, role assignments, training opportunities, pay, performance evaluation, promotion, and termination.

Studies with varying methodologies show that women face personal discrimination when going through the selection process (e.g., Goldberg, 1968 ; Rosen and Jerdee, 1974 ). Meta-analyses reveal that, when being considered for male-typed (i.e., male dominated, believed-to-be-for-men) jobs, female candidates are evaluated more negatively and recommended for employment less often by study participants, compared with matched male candidates (e.g., Hunter et al., 1982 ; Tosi and Einbender, 1985 ; Olian et al., 1988 ; Davison and Burke, 2000 ). For example, in audit studies, which involve sending ostensibly real applications for job openings while varying the gender of the applicant, female applicants are less likely to be interviewed or called back, compared with male applicants (e.g., McIntyre et al., 1980 ; Firth, 1982 ). In a recent study, male and female biology, chemistry, and physics professors rated an undergraduate science student for a laboratory manager position ( Moss-Racusin et al., 2012 ). The male applicant was rated as significantly more competent and hireable, offered a higher starting salary (about $4000), and offered more career mentoring than the female applicant was. In summary, women face a distinct disadvantage when being considered for male-typed jobs.

There is ample evidence that women experience biased performance evaluations on male-typed tasks. A meta-analysis of experimental studies reveals that women in leadership positions receive lower performance evaluations than matched men; this is amplified when women act in a stereotypically masculine, that is, agentic fashion ( Eagly et al., 1992 ). Further, in masculine domains, women are held to a higher standard of performance than men are. For example, in a study of military cadets, men and women gave their peers lower ratings if they were women, despite having objectively equal qualifications to men ( Boldry et al., 2001 ). Finally, women are evaluated more poorly in situations that involve complex problem solving; in these situations, people are skeptical regarding women’s expertise and discredit expert women’s opinions but give expert men the benefit of the doubt ( Thomas-Hunt and Phillips, 2004 ).

Sometimes particular types of women are more likely to be discriminated against in selection and performance evaluation decisions. Specifically, agentic women, that is, those who behave in an assertive, task-oriented fashion, are rated as less likeable and less hireable than comparable agentic male applicants ( Heilman and Okimoto, 2007 ; Rudman and Phelan, 2008 ; Rudman et al., 2012 ). In addition, there is evidence of discrimination against pregnant women when they apply for jobs ( Hebl et al., 2007 ; Morgan et al., 2013 ). Further, women who are mothers are recommended for promotion less than women who are not mothers or men with or without children ( Heilman and Okimoto, 2008 ). Why might people discriminate specifically against agentic women and pregnant women or mothers, who are seemingly very different? The stereotype content model, accounts for how agentic women, who are perceived to be high in competence and low in warmth, will be discriminated against because of feelings of competition; whereas, pregnant women and mothers, who are seen as low in competence, but high in warmth, will be discriminated against because of a perceived lack of deservingness ( Fiske et al., 1999 , 2002 ; Cuddy et al., 2004 ). Taken together, research has uncovered that different forms of bias toward specific subtypes of women have the same overall effect—bias in selection and performance evaluation decisions.

Women are also likely to receive fewer opportunities at work, compared with men, resulting in their under-representation at higher levels of management and leadership within organizations ( Martell et al., 1996 ; Eagly and Carli, 2007 ). Managers give women fewer challenging roles and fewer training opportunities, compared with men ( King et al., 2012 ; Glick, 2013 ). For instance, female managers ( Lyness and Thompson, 1997 ) and midlevel workers ( De Pater et al., 2010 ) have less access to high-level responsibilities and challenges that are precursors to promotion. Further, men are more likely to be given key leadership assignments in male-dominated fields and in female-dominated fields (e.g., Maume, 1999 ; De Pater et al., 2010 ). This is detrimental given that challenging roles, especially developmental ones, help employees gain important skills needed to excel in their careers ( Spreitzer et al., 1997 ).

Furthermore, managers rate women as having less promotion potential than men ( Roth et al., 2012 ). Given the same level of qualifications, managers are less likely to grant promotions to women, compared with men ( Lazear and Rosen, 1990 ). Thus, men have a faster ascent in organizational hierarchies than women ( Cox and Harquail, 1991 ; Stroh et al., 1992 ; Blau and DeVaro, 2007 ). Even minimal amounts of gender discrimination in promotion decisions for a particular job or level can have large, cumulative effects given the pyramid structure of most hierarchical organizations ( Martell et al., 1996 ; Baxter and Wright, 2000 ). Therefore, discrimination by organizational decision makers results in the under-promotion of women.

Finally, women are underpaid, compared with men. In a comprehensive US study using data from 1983 to 2000, after controlling for human capital factors that could affect wages (e.g., education level, work experience), the researchers found that women were paid 22% less than men ( U.S. Government Accountability Office, 2003 ). Further, within any given occupation, men typically have higher wages than women; this “within-occupation” wage gap is especially prominent in more highly paid occupations ( U.S. Census Bureau, 2007 ). In a study of over 2000 managers, women were compensated less than men were, even after controlling for a number of human capital factors ( Ostroff and Atwater, 2003 ). Experimental work suggests that personal biases by organizational decision makers contribute to the gender wage gap. When participants are asked to determine starting salaries for matched candidates that differ by gender, they pay men more (e.g., Steinpreis et al., 1999 ; Moss-Racusin et al., 2012 ). Such biases are consequential because starting salaries determine life-time earnings ( Gerhart and Rynes, 1991 ). In experimental studies, when participants evaluate a man vs. a woman who is matched on job performance, they choose to compensate men more ( Marini, 1989 ; Durden and Gaynor, 1998 ; Lips, 2003 ). Therefore, discrimination in HR-related decision-making by organizational decision makers can contribute to women being paid less than men are.

Taken together, we have shown that there is discrimination against women in decision-making related to HR. These biases from organizational decision makers can occur in each stage of HR-related decision-making and these biased HR decisions have been shown to negatively affect women’s pay and opportunities at work. In the next section, we review how biased HR practices are enacted, which can involve gender harassment.

Personal Discrimination in HR Enactment

By HR enactment, we refer to those situations where current or prospective employees go through HR processes or when they receive news of their outcomes from organizational decision makers regarding HR-related issues. Personal gender discrimination can occur when employees are given sexist messages, by organizational decision makers, related to HR enactment. More specifically, this type of personal gender discrimination is termed gender harassment, and consists of a range of verbal and non-verbal behaviors that convey sexist, insulting, or hostile attitudes about women ( Fitzgerald et al., 1995a , b ). Gender harassment is the most common form of sex-based discrimination ( Fitzgerald et al., 1988 ; Schneider et al., 1997 ). For example, across the military in the United States, 52% of the 9,725 women surveyed reported that they had experienced gender harassment in the last year ( Leskinen et al., 2011 , Study 1). In a random sample of attorneys from a large federal judicial circuit, 32% of the 1,425 women attorneys surveyed had experienced gender harassment in the last 5 years ( Leskinen et al., 2011 , Study 2). When examining women’s experiences of gender harassment, 60% of instances were perpetrated by their supervisor/manager or a person in a leadership role (cf. Crocker and Kalemba, 1999 ; McDonald et al., 2008 ). Thus, personal discrimination in the form of gender harassment is a common behavior; however, is it one that organizational decision makers engage in when enacting HR processes and outcomes?

Although it might seem implausible that organizational decision makers would convey sexist sentiments to women when giving them the news of HR-related decisions, there have been high-profile examples from discrimination lawsuits where this has happened. For example, in a class action lawsuit against Walmart, female workers claimed they were receiving fewer promotions than men despite superior qualifications and records of service. In that case, the district manager was accused of confiding to some of the women who were overlooked for promotions that they were passed over because he was not in favor of women being in upper management positions ( Wal-Mart Stores, Inc. v. Dukes, 2004/2011 ). In addition, audit studies, wherein matched men and women apply to real jobs, have revealed that alongside discrimination ( McIntyre et al., 1980 ; Firth, 1982 ; Moss-Racusin et al., 2012 ), women experience verbal gender harassment when applying for sex atypical jobs, such as sexist comments as well as skeptical or discouraging responses from hiring staff ( Neumark, 1996 ). Finally, gender harassment toward women when HR policies are enacted can also take the form of offensive comments and denying women promotions due to pregnancy or the chance of pregnancy. For example, in Moore v. Alabama , an employee was 8 months pregnant and the woman’s supervisor allegedly looked at her belly and said “I was going to make you head of the office, but look at you now” ( Moore v. Alabama State University, 1996 , p. 431; Williams, 2003 ). Thus, organizational decision makers will at times convey sexist sentiments to women when giving them the news of HR-related decisions.

Interestingly, whereas discrimination in HR policy and in HR-related decision-making is extremely difficult to detect ( Crosby et al., 1986 ; Major, 1994 ), gender harassment in HR enactment provides direct cues to recipients that discrimination is occurring. In other words, although women’s lives are negatively affected in concrete ways by discrimination in HR policy and decisions (e.g., not receiving a job, being underpaid), they may not perceive their negative outcomes as due to gender discrimination. Indeed, there is a multitude of evidence that women and other stigmatized group members are loath to make attributions to discrimination ( Crosby, 1984 ; Vorauer and Kumhyr, 2001 ; Stangor et al., 2003 ) and instead are likely to make internal attributions for negative evaluations unless they are certain the evaluator is biased against their group ( Ruggiero and Taylor, 1995 ; Major et al., 2003 ). However, when organizational decision makers engage in gender harassment during HR enactment women should be more likely to interpret HR policy and HR-related decisions as discriminatory.

Now that we have specified the nature of institutional gender discrimination in HR policy and personal discrimination in HR-related decision-making and in HR enactment, we turn to the issue of understanding the causes of such discrimination: gender discrimination in organizational structures, processes, and practices, and personal biases of organizational decision makers.

The Effect of Organizational Structures, Processes, and Practices on HR Practices

The first contextual factor within which gender inequalities can be institutionalized is leadership. Leadership is a process wherein an individual (e.g., CEOs, managers) influences others in an effort to reach organizational goals ( Chemers, 1997 ; House and Aditya, 1997 ). Leaders determine and communicate what the organization’s priorities are to all members of the organization. Leaders are important as they affect the other organizational structures, processes, and practices. Specifically, leaders set culture, set policy, set strategy, and are role models for socialization. We suggest that one important way institutional gender inequality in leadership exists is when women are under-represented, compared with men—particularly when women are well-represented at lower levels within an organization.

An underrepresentation of women in leadership can be perpetuated easily because the gender of organizational leaders affects the degree to which there is gender discrimination, gender supportive policies, and a gender diversity supportive climate within an organization ( Ostroff et al., 2012 ). Organizational members are likely to perceive that the climate for women is positive when women hold key positions in the organization ( Konrad et al., 2010 ). Specifically, the presence of women in key positions acts as a vivid symbol indicating that the organization supports gender diversity. Consistent with this, industries that have fewer female high status managers have a greater gender wage gap ( Cohen and Huffman, 2007 ). Further, women who work with a male supervisor perceive less organizational support, compared with those who work with a female supervisor ( Konrad et al., 2010 ). In addition, women who work in departments that are headed by a man report experiencing more gender discrimination, compared with their counterparts in departments headed by women ( Konrad et al., 2010 ). Some of these effects may be mediated by a similar-to-me bias ( Tsui and O’Reilly, 1989 ), where leaders set up systems that reward and promote individuals like themselves, which can lead to discrimination toward women when leaders are predominantly male ( Davison and Burke, 2000 ; Roth et al., 2012 ). Thus, gender inequalities in leadership affect women’s experiences in the workplace and their likelihood of facing discrimination.

The second contextual factor to consider is organizational structure. The formal structure of an organization is how an organization arranges itself and it consists of employee hierarchies, departments, etc. ( Grant, 2010 ). An example of institutional discrimination in the formal structure of an organization are job ladders, which are typically segregated by gender ( Perry et al., 1994 ). Such gender-segregated job ladders typically exist within different departments of the organization. Women belonging to gender-segregated networks within organizations ( Brass, 1985 ) have less access to information about jobs, less status, and less upward mobility within the organization ( Ragins and Sundstrom, 1989 ; McDonald et al., 2009 ). This is likely because in gender-segregated networks, women have less visibility and lack access to individuals with power ( Ragins and Sundstrom, 1989 ). In gender-segregated networks, it is also difficult for women to find female mentors because there is a lack of women in high-ranking positions ( Noe, 1988 ; Linehan and Scullion, 2008 ). Consequently, the organizational structure can be marked by gender inequalities that reduce women’s chances of reaching top-level positions in an organization.

Gender inequalities can be inherent in the structure of an organization when there are gender segregated departments, job ladders, and networks, which are intimately tied to gender discrimination in HR practices. For instance, if HR policies are designed such that pay is determined based on comparisons between individuals only within a department (e.g., department-wide reporting structure, job descriptions, performance evaluations), then this can lead to a devaluation of departments dominated by women. The overrepresentation of women in certain jobs leads to the lower status of those jobs; consequently, the pay brackets for these jobs decrease over time as the number of women in these jobs increase (e.g., Huffman and Velasco, 1997 ; Reilly and Wirjanto, 1999 ). Similarly, networks led by women are also devalued for pay. For example, in a study of over 2,000 managers, after controlling for performance, the type of job, and the functional area (e.g., marketing, sales, accounting), those who worked with female mangers had lower wages than those who worked with male managers ( Ostroff and Atwater, 2003 ). Thus, gender inequalities in an organization’s structure in terms of gender segregation have reciprocal effects with gender discrimination in HR policy and decision-making.

Another contextual factor in our model is organizational strategy and how institutional discrimination within strategy is related to discrimination in HR practices. Strategy is a plan, method, or process by which an organization attempts to achieve its objectives, such as being profitable, maintaining and expanding its consumer base, marketing strategy, etc. ( Grant, 2010 ). Strategy can influence the level of inequality within an organization ( Morrison and Von Glinow, 1990 ; Hunter et al., 2001 ). For example, Hooters, a restaurant chain, has a marketing strategy to sexually attract heterosexual males, which has led to discrimination in HR policy, decisions, and enactment because only young, good-looking women are considered qualified ( Schneyer, 1998 ). When faced with appearance-based discrimination lawsuits regarding their hiring policies, Hooters has responded by claiming that such appearance requirements are bona fide job qualifications given their marketing strategy (for reviews, see Schneyer, 1998 ; Adamitis, 2000 ). Hooters is not alone, as many other establishments attempt to attract male cliental by requiring their female servers to meet a dress code involving a high level of grooming (make-up, hair), a high heels requirement, and a revealing uniform ( McGinley, 2007 ). Thus, sexist HR policies and practices in which differential standards are applied to male and female employees can stem from a specific organizational strategy ( Westall, 2015 ).

We now consider institutional gender bias within organizational culture and how it relates to discrimination in HR policies. Organizational culture refers to collectively held beliefs, assumptions, and values held by organizational members ( Trice and Beyer, 1993 ; Schein, 2010 ). Cultures arise from the values of the founders of the organization and assumptions about the right way of doing things, which are learned from dealing with challenges over time ( Ostroff et al., 2012 ). The founders and leaders of an organization are the most influential in forming, maintaining, and changing culture over time (e.g., Trice and Beyer, 1993 ; Jung et al., 2008 ; Hartnell and Walumbwa, 2011 ). Organizational culture can contribute to gender inequalities because culture constrains people’s ideas of what is possible: their strategies of action ( Swidler, 1986 ). In other words, when people encounter a problem in their workplace, the organizational culture—who we are, how we act, what is right—will provide only a certain realm of behavioral responses. For instance, in organizational cultures marked by greater gender inequality, women may have lower hopes and expectations for promotion, and when they are discriminated against, may be less likely to imagine that they can appeal their outcomes ( Kanter, 1977 ; Cassirer and Reskin, 2000 ). Furthermore, in organizational cultures marked by gender inequality, organizational decision makers should hold stronger descriptive and proscriptive gender stereotypes: they should more strongly believe that women have less ability to lead, less career commitment, and less emotional stability, compared with men ( Eagly et al., 1992 ; Heilman, 2001 ). We expand upon this point later.

Other aspects of organizational culture that are less obviously related to gender can also lead to discrimination in HR practices. For instance, an organizational culture that emphasizes concerns with meritocracy, can lead organizational members to oppose HR efforts to increase gender equality. This is because when people believe that outcomes ought to go only to those who are most deserving, it is easy for them to fall into the trap of believing that outcomes currently do go to those who are most deserving ( Son Hing et al., 2011 ). Therefore, people will believe that men deserve their elevated status and women deserve their subordinated status at work ( Castilla and Benard, 2010 ). Furthermore, the more people care about merit-based outcomes, the more they oppose affirmative action and diversity initiatives for women ( Bobocel et al., 1998 ; Son Hing et al., 2011 ), particularly when they do not recognize that discrimination occurs against women in the absence of such policies ( Son Hing et al., 2002 ). Thus, a particular organizational culture can influence the level of discrimination against women in HR and prevent the adoption of HR policies that would mitigate gender discrimination.

Finally, gender inequalities can be seen in organizational climates. An organizational climate consists of organizational members’ shared perceptions of the formal and informal organizational practices, procedures, and routines ( Schneider et al., 2011 ) that arise from direct experiences of the organization’s culture ( Ostroff et al., 2012 ). Organizational climates tend to be conceptualized and studied as “climates for” an organizational strategy ( Schneider, 1975 ; Ostroff et al., 2012 ). Gender inequalities are most clearly reflected in two forms of climate: climates for diversity and climates for sexual harassment.

A positive climate for diversity exists when organizational members perceive that diverse groups are included, empowered, and treated fairly. When employees perceive a less supportive diversity climate, they perceive greater workplace discrimination ( Cox, 1994 ; Ragins and Cornwall, 2001 ; Triana and García, 2009 ), and experience lower organizational commitment and job satisfaction ( Hicks-Clarke and Iles, 2000 ), and higher turnover intentions ( Triana et al., 2010 ). Thus, in organizations with a less supportive diversity climate, women are more likely to leave the organization, which contributes to the underrepresentation of women in already male-dominated arenas ( Miner-Rubino and Cortina, 2004 ).

A climate for sexual harassment involves perceptions that the organization is permissive of sexual harassment. In organizational climates that are permissive of harassment, victims are reluctant to come forward because they believe that their complaints will not be taken seriously ( Hulin et al., 1996 ) and will result in negative personal consequences (e.g., Offermann and Malamut, 2002 ). Furthermore, men with a proclivity for harassment are more likely to act out these behaviors when permissive factors are present ( Pryor et al., 1993 ). Therefore, a permissive climate for sexual harassment can result in more harassing behaviors, which can lead women to disengage from their work and ultimately leave the organization ( Kath et al., 2009 ).

Organizational climates for diversity and for sexual harassment are inextricably linked to HR practices. For instance, a factor that leads to perceptions of diversity climates is whether the HR department has diversity training (seminars, workshops) and how much time and money is devoted to diversity efforts ( Triana and García, 2009 ). Similarly, a climate for sexual harassment depends on organizational members’ perceptions of how strict the workplace’s sexual harassment policy is, and how likely offenders are to be punished ( Fitzgerald et al., 1995b ; Hulin et al., 1996 ). Thus, HR policies, decision-making, and their enactment strongly affect gender inequalities in organizational climates and gender inequalities throughout an organization.

In summary, gender inequalities can exist within organizational structures, processes, and practices. However, organizational leadership, structure, strategy, culture, and climate do not inherently need to be sexist. It could be possible for these organizational structures, processes, and practices to promote gender equality. We return to this issue in the conclusion section.

The Effect of Hostile and Benevolent Sexism on How Organizational Decision Makers’ Conduct HR Practices

In this section, we explore how personal biases can affect personal discrimination in HR-related decisions and their enactment. Others have focused on how negative or hostile attitudes toward women predict discrimination in the workplace. However, we extend this analysis by drawing on ambivalent sexism theory, which involves hostile sexism (i.e., antagonistic attitudes toward women) and benevolent sexism (i.e., paternalistic attitudes toward women; see also Glick, 2013 ), both of which lead to discrimination against women.

Stereotyping processes are one possible explanation of how discrimination against women in male-typed jobs occurs and how women are relegated to the “pink ghetto” ( Heilman, 1983 ; Eagly and Karau, 2002 ; Rudman et al., 2012 ). Gender stereotypes, that is, expectations of what women and men are like, and what they should be like, are one of the most powerful schemas activated when people encounter others ( Fiske et al., 1991 ; Stangor et al., 1992 ). According to status characteristics theory, people’s group memberships convey important information about their status and their competence on specific tasks ( Berger et al., 1974 ; Berger et al., 1998 ; Correll and Ridgeway, 2003 ). Organizational decision makers will, for many jobs, have different expectations for men’s and women’s competence and job performance. Expectations of stereotyped-group members’ success can affect gender discrimination that occurs in HR-related decisions and enactment ( Roberson et al., 2007 ). For example, men are preferred over women for masculine jobs and women are preferred over men for feminine jobs ( Davison and Burke, 2000 ). Thus, the more that a workplace role is inconsistent with the attributes ascribed to women, the more a particular woman might be seen as lacking “fit” with that role, resulting in decreased performance expectations ( Heilman, 1983 ; Eagly and Karau, 2002 ).

Furthermore, because women are associated with lower status, and men with higher status, women experience backlash for pursuing high status roles (e.g., leadership) in the workplace ( Rudman et al., 2012 ). In other words, agentic women who act competitively and confidently in a leadership role, are rated as more socially deficient, less likeable and less hireable, compared with men who act the same way ( Rudman, 1998 ; Rudman et al., 2012 ). Interestingly though, if women pursue roles in the workplace that are congruent with traditional gender expectations, they will elicit positive reactions ( Eagly and Karau, 2002 ).

Thus, cultural, widely known, gender stereotypes can affect HR-related decisions. However, such an account does not take into consideration individual differences among organizational decision makers (e.g., managers, supervisors, or HR personnel) who may vary in the extent to which they endorse sexist attitudes or stereotypes. Individual differences in various forms of sexism (e.g., modern sexism, neosexism) have been demonstrated to lead to personal discrimination in the workplace ( Hagen and Kahn, 1975 ; Beaton et al., 1996 ; Hitlan et al., 2009 ). Ambivalent sexism theory builds on earlier theories of sexism by including attitudes toward women that, while sexist, are often experienced as positive in valence by perceivers and targets ( Glick and Fiske, 1996 ). Therefore, we draw on ambivalent sexism theory, which conceptualizes sexism as a multidimensional construct that encompasses both hostile and benevolent attitudes toward women ( Glick and Fiske, 1996 , 2001 ).

Hostile sexism involves antipathy and negative stereotypes about women, such as beliefs that women are incompetent, overly emotional, and sexually manipulative. Hostile sexism also involves beliefs that men should be more powerful than women and fears that women will try to take power from men ( Glick and Fiske, 1996 ; Cikara et al., 2008 ). In contrast, benevolent sexism involves overall positive views of women, as long as they occupy traditionally feminine roles. Individuals with benevolently sexist beliefs characterize women as weak and needing protection, support, and adoration. Importantly, hostile and benevolent sexism tend to go hand-in-hand (with a typical correlation of 0.40; Glick et al., 2000 ). This is because ambivalent sexists, people who are high in benevolent and hostile sexism, believe that women should occupy restricted domestic roles and that women are weaker than men are ( Glick and Fiske, 1996 ). Ambivalent sexists reconcile their potentially contradictory attitudes about women by acting hostile toward women whom they believe are trying to steal men’s power (e.g., feminists, professionals who show competence) and by acting benevolently toward traditional women (e.g., homemakers) who reinforce conventional gender relations and who serve men ( Glick et al., 1997 ). An individual difference approach allows us to build on the earlier models ( Heilman, 1983 ; Eagly and Karau, 2002 ; Rudman et al., 2012 ), by specifying who is more likely to discriminate against women and why.

Organizational decision makers who are higher (vs. lower) in hostile sexism should discriminate more against women in HR-related decisions ( Glick et al., 1997 ; Masser and Abrams, 2004 ). For instance, people high in hostile sexism have been found to evaluate candidates, who are believed to be women, more negatively and give lower employment recommendations for a management position, compared with matched candidates believed to be men ( Salvaggio et al., 2009 ) 1 . In another study, among participants who evaluated a female candidate for a managerial position, those higher in hostile sexism were less likely to recommend her for hire, compared with those lower in hostile sexism ( Masser and Abrams, 2004 ). Interestingly, among those evaluating a matched man for the same position, those higher (vs. lower) in hostile sexism were more likely to recommend him for hire ( Masser and Abrams, 2004 ). According to ambivalent sexism theorists ( Glick et al., 1997 ), because people high in hostile sexism see women as a threat to men’s status, they act as gatekeepers denying women access to more prestigious or masculine jobs.

Furthermore, when enacting HR policies and decisions, organizational decision makers who are higher (vs. lower) in hostile sexism should discriminate more against women in the form of gender harassment. Gender harassment can involve hostile terms of address, negative comments regarding women in management, sexist jokes, and sexist behavior ( Fitzgerald et al., 1995a , b ). It has been found that people higher (vs. lower) in hostile sexism have more lenient attitudes toward the sexual harassment of women, which involves gender harassment, in the workplace ( Begany and Milburn, 2002 ; Russell and Trigg, 2004 ). Furthermore, men who more strongly believe that women are men’s adversaries tell more sexist jokes to a woman ( Mitchell et al., 2004 ). Women also report experiencing more incivility (i.e., low level, rude behavior) in the workplace than men ( Björkqvist et al., 1994 ; Cortina et al., 2001 , 2002 ), which could be due to hostile attitudes toward women. In summary, the evidence is consistent with the idea that organizational decision makers’ hostile sexism should predict their gender harassing behavior during HR enactment; however, more research is needed for such a conclusion.

In addition, organizational decision makers who are higher (vs. lower) in benevolent sexism should discriminate more against women when making HR-related decisions. It has been found that people higher (vs. lower) in benevolent sexism are more likely to automatically associate men with high-authority and women with low-authority roles and to implicitly stereotype men as agentic and women as communal ( Rudman and Kilianski, 2000 ). Thus, organizational decision makers who are higher (vs. lower) in benevolent sexism should more strongly believe that women are unfit for organizational roles that are demanding, challenging, and requiring agentic behavior. Indeed, in studies of male MBA students those higher (vs. lower) in benevolent sexism assigned a fictional woman less challenging tasks than a matched man ( King et al., 2012 ). The researchers reasoned that this occurred because men are attempting to “protect” women from the struggles of challenging work. Although there has been little research conducted that has looked at benevolent sexism and gender discrimination in HR-related decisions, the findings are consistent with our model.

Finally, organizational decision makers who are higher (vs. lower) in benevolent sexism should engage in a complex form of gender discrimination when enacting HR policy and decisions that involves mixed messages: women are more likely to receive messages of positive verbal feedback (e.g., “stellar work,” “excellent work”) but lower numeric ratings on performance appraisals, compared with men ( Biernat et al., 2012 ). It is proposed that this pattern of giving women positive messages about their performance while rating them poorly reflects benevolent sexists’ desire to protect women from harsh criticism. However, given that performance appraisals are used for promotion decisions and that constructive feedback is needed for learning, managers’ unwillingness to give women negative verbal criticisms can lead to skill plateau and career stagnation.

Furthermore, exposure to benevolent sexism can harm women’s motivation, goals and performance. Adolescent girls whose mothers are high in benevolent (but not hostile) sexism display lower academic goals and academic performance ( Montañés et al., 2012 ). Of greater relevance to the workplace, when role-playing a job candidate, women who interacted with a hiring manager scripted to make benevolently sexist statements became preoccupied with thoughts about their incompetence, and consequently performed worse in the interview, compared with those in a control condition ( Dardenne et al., 2007 ). These findings suggest that benevolent sexism during the enactment of HR practices can harm women’s work-related motivation and goals, as well as their performance, which can result in a self-fulfilling prophecy ( Word et al., 1974 ). In other words, the low expectations benevolent sexists have of women can be confirmed by women as they are undermined by paternalistic messages.

Ambivalent sexism can operate to harm women’s access to jobs, opportunities for development, ratings of performance, and lead to stigmatization. However, hostile and benevolent sexism operate in different ways. Hostile sexism has direct negative consequences for women’s access to high status, male-typed jobs ( Masser and Abrams, 2004 ; Salvaggio et al., 2009 ), and it is related to higher rates of sexual harassment ( Fitzgerald et al., 1995b ; Mitchell et al., 2004 ; Russell and Trigg, 2004 ), which negatively affect women’s health, well-being, and workplace withdrawal behaviors ( Willness et al., 2007 ). In contrast, benevolent sexism has indirect negative consequences for women’s careers, for instance, in preventing access to challenging tasks ( King et al., 2012 ) and critical developmental feedback ( Vescio et al., 2005 ). Interestingly, exposure to benevolent sexism results in worsened motivation and cognitive performance, compared with exposure to hostile sexism ( Dardenne et al., 2007 ; Montañés et al., 2012 ). This is because women more easily recognize hostile sexism as a form of discrimination and inequality, compared with benevolent sexism, which can be more subtle in nature ( Dardenne et al., 2007 ). Thus, women can externalize hostile sexism and mobilize against it, but the subtle nature of benevolent sexism prevents these processes ( Kay et al., 2005 ; Becker and Wright, 2011 ). Therefore, hostile and benevolent sexism lead to different but harmful forms of HR discrimination. Future research should more closely examine their potentially different consequences.

Thus far, we have articulated how gender inequalities in organizational structures, processes, and practices can affect discrimination in HR policy and in HR-related decision-making and enactment. Furthermore, we have argued that organizational decision makers’ levels of hostile and benevolent sexism are critical factors leading to personal discrimination in HR-related decision-making and enactment, albeit in different forms. We now turn to an integration of these two phenomena.

The Effect of Organizational Structures, Processes, and Practices on Organizational Decision Makers’ Levels of Hostile and Benevolent Sexism

Organizational decision makers’ beliefs about men and women should be affected by the work environments in which they are embedded. Thus, when there are more gender inequalities within organizational structures, processes, and practices, organizational decision makers should have higher levels of hostile sexism and benevolent sexism. Two inter-related processes can account for this proposition: the establishment of who becomes and remains an organizational member, and the socialization of organizational members.

First, as organizations develop over time, forces work to attract, select, and retain an increasingly homogenous set of employees in terms of their hostile and benevolent sexism ( Schneider, 1983 , 1987 ). In support of this perspective, an individual’s values tend to be congruent with the values in his or her work environment (e.g., Holland, 1996 ; Kristof-Brown et al., 2005 ). People are attracted to and choose to work for organizations that have characteristics similar to their own, and organizations select individuals who are likely to fit with the organization. Thus, more sexist individuals are more likely to be attracted to organizations with greater gender inequality in leadership, structure, strategy, culture, climate, and HR policy; and they will be seen as a better fit during recruitment and selection. Finally, individuals who do not fit with the organization tend to leave voluntarily through the process of attrition. Thus, less (vs. more) sexist individuals would be more likely to leave a workplace with marked gender inequalities in organizational structures, processes, and practices. The opposite should be true for organizations with high gender equality. Through attraction, selection, and attrition processes it is likely that organizational members will become more sexist in a highly gender unequal organization and less sexist in a highly gender equal organization.

Second, socialization processes can change organizational members’ personal attributes, goals, and values to match those of the organization ( Ostroff and Rothausen, 1997 ). Organizational members’ receive both formal and informal messages about gender inequality—or equality—within an organization through their orientation and training, reading of organizational policy, perceptions of who rises in the ranks, how women (vs. men) are treated within the organization, as well as their perception of climates for diversity and sexual harassment. Socialization of organizational members over time has been shown to result in organizational members’ values and personalities changing to better match the values of the organization ( Kohn and Schooler, 1982 ; Cable and Parsons, 2001 ).

These socialization processes can operate to change organizational members’ levels of sexism. It is likely that within more sexist workplaces, people’s levels of hostile and benevolent sexism increase because their normative beliefs shift due to exposure to institutional discrimination against women, others’ sexist attitudes and behavior, and gender bias in culture and climate ( Schwartz and DeKeseredy, 2000 ; Ford et al., 2008 ; Banyard et al., 2009 ). These processes can also lead organizational decision makers to adopt less sexist attitudes in a workplace context marked by greater gender equality. Thus, organizational members’ levels of hostile and benevolent sexism can be shaped by the degree of gender inequalities in organizational structures, processes, and practices and by the sexism levels of their work colleagues.

In addition, organizational decision makers can be socialized to act in discriminatory ways without personally becoming more sexist. If organizational decision makers witness others acting in a discriminatory manner with positive consequences, or acting in an egalitarian way with negative consequences, they can learn to become more discriminatory in their HR practices through observational learning ( Bandura, 1977 , 1986 ). So, organizational decision makers could engage in personal discrimination without being sexist if they perceive that the fair treatment of women in HR would encounter resistance given the broader organizational structures, processes, and practices promoting gender inequality. Yet over time, given cognitive dissonance ( Festinger, 1962 ), it is likely that discriminatory behavior could induce attitude change among organizational decision makers to become more sexist.

Thus far we have argued that gender inequalities in organizational structures, processes, and practices, organizational decision makers’ sexist attitudes, and gender discrimination in HR practices can have reciprocal, reinforcing relationships. Thus, it may appear that we have created a model that is closed and determinate in nature; however, this would be a misinterpretation. In the following section, we outline how organizations marked by gender inequalities can reduce discrimination against women.

How to Reduce Gender Discrimination in Organizations

The model we present for understanding gender discrimination in HR practices is complex. We believe that such complexity is necessary to accurately reflect the realities of organizational life. The model demonstrates that many sources of gender inequality are inter-related and have reciprocal effects. By implication, there are no simple or direct solutions to reduce gender discrimination in organizations. Rather, this complex problem requires multiple solutions. In fact, as discussed by Gelfand et al. (2007) , if an organization attempts to correct discrimination in only one aspect of organizational structure, process, or practice, and not others, such change attempts will be ineffective due to mixed messages. Therefore, we outline below how organizations can reduce gender discrimination by focusing on (a) HR policies (i.e., diversity initiatives and family friendly policies) and closely related organizational structures, processes, and practices; (b) HR-related decision-making and enactment; as well as, (c) the organizational decision makers who engage in such actions.

Reducing Gender Discrimination in HR Policy and Associated Organizational Structures, Processes, and Practices

Organizations can take steps to mitigate discrimination in HR policies. As a first example, let us consider how an organization can develop, within its HR systems, diversity initiatives aimed at changing the composition of the workforce that includes policies to recruit, retain, and develop employees from underrepresented groups ( Jayne and Dipboye, 2004 ). Diversity initiatives can operate like affirmative action programs in that organizations track and monitor (a) the number of qualified candidates from different groups (e.g., women vs. men) in a pool, and (b) the number of candidates from each group hired or promoted. When the proportion of candidates from a group successfully selected varies significantly from their proportion in the qualified pool then action, such as targeted recruitment efforts, needs to be taken.

Importantly, such efforts to increase diversity can be strengthened by other HR policies that reward managers, who select more diverse personnel, with bonuses ( Jayne and Dipboye, 2004 ). Organizations that incorporate diversity-based criteria into their performance and promotion policies and offer meaningful incentives to managers to identify and develop successful female candidates for promotion are more likely to succeed in retaining and promoting diverse talent ( Murphy and Cleveland, 1995 ; Cleveland et al., 2000 ). However, focusing on short-term narrowly defined criteria, such as increasing the number of women hired, without also focusing on candidates’ merit and providing an adequate climate or support for women are unlikely to bring about any long-term change in diversity, and can have detrimental consequences for its intended beneficiaries ( Heilman et al., 1992 , 1997 ). Rather, to be successful, HR policies for diversity need to be supported by the other organizational structures, processes, and practices, such as strategy, leadership, and climate.

For instance, diversity initiatives should be linked to strategies to create a business case for diversity ( Jayne and Dipboye, 2004 ). An organization with a strategy to market to more diverse populations can justify that a more diverse workforce can better serve potential clientele ( Jayne and Dipboye, 2004 ). Alternatively, an organization that is attempting to innovate and grow might justify a corporate strategy to increase diversity on the grounds that diverse groups have multiple perspectives on a problem with the potential to generate more novel, creative solutions ( van Knippenberg et al., 2004 ). Furthermore, organizational leaders must convey strong support for the HR policies for them to be successful ( Rynes and Rosen, 1995 ). Given the same HR policy within an organization, leaders’ personal attitudes toward the policy affects the discrimination levels found within their unit ( Pryor, 1995 ; Pryor et al., 1995 ). Finally, diversity programs are more likely to succeed in multicultural organizations with strong climates for diversity ( Elsass and Graves, 1997 ; Jayne and Dipboye, 2004 ). An organization’s climate for diversity consists of employees’ shared perceptions that the organization’s structures, processes, and practices are committed to maintaining diversity and eliminating discrimination ( Nishii and Raver, 2003 ; Gelfand et al., 2007 ). In organizations where employees perceive a strong climate for diversity, diversity programs result in greater employee attraction and retention among women and minorities, at all levels of the organization ( Cox and Blake, 1991 ; Martins and Parsons, 2007 ).

As a second example of how HR policies can mitigate gender inequalities, we discuss HR policies to lessen employees’ experience of work-family conflict. Work-family conflict is a type of role conflict that workers experience when the demands (e.g., emotional, cognitive, time) of their work role interfere with the demands of their family role or vice versa ( Greenhaus and Beutell, 1985 ). Work-family conflict has the negative consequences of increasing employee stress, illness-related absence, and desire to turnover ( Grandey and Cropanzano, 1999 ). Importantly, women are more adversely affected by work-family conflict than men ( Martins et al., 2002 ). Work-family conflict can be exacerbated by HR policies that evaluate employees based on face time (i.e., number of hours present at the office), as a proxy for organizational commitment ( Perlow, 1995 ; Elsbach et al., 2010 ).

Formal family friendly HR policies can be adopted to relieve work-family conflict directly, which differentially assists women in the workplace. For instance, to reduce work-family conflict, organizations can implement HR policies such as flexible work arrangements, which involve flexible schedules, telecommuting, compressed work weeks, job-shares, and part-time work ( Galinsky et al., 2008 ). In conjunction with other family friendly policies, such as the provision of childcare, elderly care, and paid maternity leave, organizations can work to reduce stress and improve the retention of working mothers ( Burke, 2002 ).

Unfortunately, it has been found that the enactment of flexible work policies can still lead to discrimination. Organizational decision makers’ sexism can lead them to grant more flexible work arrangements to white men than to women and other minorities because white men are seen as more valuable ( Kelly and Kalev, 2006 ). To circumvent this, organizations need to formalize HR policies relating to flexible work arrangements ( Kelly and Kalev, 2006 ). For instance, formal, written policies should articulate who can adopt flexible work arrangements (e.g., employees in specific divisions or with specific job roles) and what such arrangements look like (e.g., core work from 10 am to 3 pm with flexible work hours from 7 to 10 am or from 3 to 6 pm). When the details of such policies are formally laid out, organizational decision makers have less latitude and therefore less opportunity for discrimination in granting access to these arrangements.

To be successful, family friendly HR policies should be tied to other organizational structures, processes, and practices such as organizational strategy, leadership, culture, and climate. A business case for flexible work arrangements can be made because they attract and retain top-talent, which includes women ( Baltes et al., 1999 ). Furthermore, organizational leaders must convey strong support for family friendly programs ( Jayne and Dipboye, 2004 ). Leaders can help bolster the acceptance of family friendly policies through successive interactions, communications, visibility, and role modeling with employees. For instance, a leader who sends emails at 2 o’clock in the morning is setting a different expectation of constant availability than a leader who never sends emails after 7:00 pm. Family friendly HR policies must also be supported by simultaneously changing the underlying organizational culture that promotes face time. Although it is difficult to change the culture of an organization, the leaders’ of the organization play an influential role in instilling such change because the behaviors of leaders are antecedents and triggers of organizational culture ( Kozlowski and Doherty, 1989 ; Ostroff et al., 2012 ). In summary, HR policies must be supported by other organizational structures, processes, and practices in order for these policies to be effective.

Adopting HR diversity initiative policies and family friendly policies can reduce gender discrimination and reshape the other organizational structures, processes, and practices and increase gender equality in them. Specifically, such policies, if successful, should increase the number of women in all departments and at all levels of an organization. Further, having more women in leadership positions signals to organizational members that the organization takes diversity seriously, affecting the diversity climate of the organization, and ultimately its culture ( Konrad et al., 2010 ). Thus, particular HR policies can reduce gender inequalities in all of the other organizational structures, processes, and practices.

Reducing Gender Discrimination in HR-Related Decision-Making and Enactment

A wealth of research demonstrates that an effective means of reducing personal bias by organizational decision makers in HR practices is to develop HR policies that standardize and objectify performance data (e.g., Konrad and Linnehan, 1995 ; Reskin and McBrier, 2000 ). To reduce discrimination in personnel decisions (i.e., employee hiring and promotion decisions) a job analysis should be performed to determine the appropriate knowledge skills and abilities needed for specific positions ( Fine and Cronshaw, 1999 ). This ensures that expectations about characteristics of the ideal employee for that position are based on accurate knowledge of the job and not gender stereotypes about the job ( Welle and Heilman, 2005 ). To reduce discrimination in performance evaluations, HR policies should necessitate the use of reliable measures based on explicit objective performance expectations and apply these practices consistently across all worker evaluations ( Bernardin et al., 1998 ; Ittner et al., 2003 ). Employees’ performance should be evaluated using behaviorally anchored rating scales ( Smith and Kendall, 1963 ) that allow supervisors to rate subordinates on examples of actual work behaviors. These evaluations should be done regularly, given that delays require retrieving memories of work performance and this process can be biased by gender stereotypes ( Sanchez and De La Torre, 1996 ). Finally, if greater gender differences are found on selection tests than on performance evaluations, then the use of such biased selection tests needs to be revisited ( Chung-Yan and Cronshaw, 2002 ). In summary, developing HR policies that standardize and objectify the process of employee/candidate evaluations can reduce personal bias in HR practices.

Importantly, the level of personal discrimination enacted by organizational decision makers can be reduced by formalizing HR policies, and by controlling the situations under which HR-related decisions are made. We have articulated how HR-related decisions involve social cognition and are therefore susceptible to biases introduced by the use of gender stereotypes. This can occur unwittingly by those who perceive themselves to be unprejudiced but who are affected by stereotypes or negative automatic associations nonetheless ( Chugh, 2004 ; Son Hing et al., 2008 ). For instance, when HR policies do not rely on objective criteria, and the context for evaluation is ambiguous, organizational decision makers will draw on gender (and other) stereotypes to fill in the blanks when evaluating candidates ( Heilman, 1995 , 2001 ). Importantly, the context can be constructed in such a way as to reduce these biases. For instance, organizational decision makers will make less biased judgments of others if they have more time available to evaluate others, are less cognitively busy ( Martell, 1991 ), have higher quality of information available about candidates, and are accountable for justifying their ratings and decisions ( Kulik and Bainbridge, 2005 ; Roberson et al., 2007 ). Thus, if they have the time, motivation, and opportunity to make well-informed, more accurate judgments, then discrimination in performance ratings can be reduced.

Reducing Organizational Decision Makers’ Sexism

Another means to reduce gender discrimination in HR-related decision-making and enactment is to focus directly on reducing the hostile and benevolent sexist beliefs of organizational decision makers. Interventions aimed at reducing these beliefs typically involve diversity training, such as a seminar, course, or workshop. Such training involves one or more sessions that involve interactive discussions, lectures, and practical assignments. During the training men and women are taught about sexism and how gender roles in society are socially constructed. Investigations have shown these workshop-based interventions are effective at reducing levels of hostile sexism but have inconsistent effects on benevolent sexism ( Case, 2007 ; de Lemus et al., 2014 ). The subtle, and in some ways positive nature of benevolent sexism makes it difficult to confront and reduce using such interventions. However, levels of benevolent sexism are reduced when individuals are explicitly informed about the harmful implications of benevolent sexism ( Becker and Swim, 2012 ). Unfortunately, these interventions have not been tested in organizational settings. So their efficacy in the field is unknown.

Gender inequality in organizations is a complex phenomenon that can be seen in HR practices (i.e., policies, decision-making, and their enactment) that affects the hiring, training, pay, and promotion of women. We propose that gender discrimination in HR-related decision-making and the enactment of HR practices stems from gender inequalities in broader organizational structures, processes, and practices, including HR policy but also leadership, structure, strategy, culture, and organizational climate. Moreover, reciprocal effects should occur, such that discriminatory HR practices can perpetuate gender inequalities in organizational leadership, structure, strategy, culture, and climate. Organizational decision makers also play an important role in gender discrimination. We propose that personal discrimination in HR-related decisions and enactment arises from organizational decision makers’ levels of hostile and benevolent sexism. While hostile sexism can lead to discrimination against women because of a desire to keep them from positions of power, benevolent sexism can lead to discrimination against women because of a desire to protect them. Finally, we propose that gender inequalities in organizational structures, processes, and practices affect organizational decision makers’ sexism through attraction, selection, socialization, and attrition processes. Thus, a focus on organizational structure, processes, and practices is critical.

The model we have developed extends previous work by Gelfand et al. (2007) in a number of substantive ways. Gelfand et al. (2007) proposed that aspects of the organization, that is, structure, organizational culture, leadership, strategy, HR systems, and organizational climates, are all interrelated and may contribute to or attenuate discrimination (e.g., racism, sexism, ableism, homophobia). First, we differ from their work by emphasizing that workplace discrimination is most directly attributable to HR practices. Consequently, we emphasize how inequalities in other organizational structures, processes, and practices affect institutional discrimination in HR policy. Second, our model differs from that of Gelfand et al. (2007) in that we focus on the role of organizational decision makers in the enactment of HR policy. The attitudes of these decision makers toward specific groups of employees are critical. However, the nature of prejudice differs depending on the target group ( Son Hing and Zanna, 2010 ). Therefore, we focus on one form of bias—sexism—in the workplace. Doing so, allows us to draw on more nuanced theories of prejudice, namely ambivalent sexism theory ( Glick and Fiske, 1996 ). Thus, third, our model differs from the work of Gelfand et al. (2007) by considering how dual beliefs about women (i.e., hostile and benevolent beliefs) can contribute to different forms of gender discrimination in HR practices. Fourth, we differ from Gelfand et al. (2007) by reviewing how organizational decision makers’ level of sexism within an organization is affected by organizational structures, processes, and practices via selection-attraction-attrition processes and through socialization processes.

However, the model we have developed is not meant to be exhaustive. There are multiple issues that we have not addressed but should be considered: what external factors feed into our model? What other links within the model might arise? What are the limits to its generalizability? What consequences derive from our model? How can change occur given a model that is largely recursive in nature? We focus on these issues throughout our conclusion.

In this paper, we have illustrated what we consider to be the dominant links in our model; however, additional links are possible. First, we do not lay out the factors that feed into our model, such as government regulations, the economy, their competitors, and societal culture. In future work, one could analyze the broader context that organizations operate in, which influences its structures, processes, and practices, as well as its members. For instance, in societies marked by greater gender inequalities, the levels of hostile and benevolent sexism of organizational decision makers will be higher ( Glick et al., 2000 ). Second, there is no link demonstrating how organizational decision makers who are more sexist have the capacity, even if they sit lower in the organizational hierarchy, to influence the amount of gender inequality in organizational structures, processes, and practices. It is possible for low-level managers or HR personnel who express more sexist sentiments to—through their own behavior—affect others’ perceptions of the tolerance for discrimination in the workplace ( Ford et al., 2001 ) and others’ perceptions of the competence and hireability of female job candidates ( Good and Rudman, 2010 ). Thus, organizational decision makers’ levels of hostile and benevolent sexism can affect organizational climates, and potentially other organizational structures, processes, and practices. Third, it is possible that organizational structures, processes, and practices could moderate the link between organizational decision makers’ sexist attitudes and their discriminatory behavior in HR practices. The ability of people to act in line with their attitudes depends on the strength of the constraints in the social situation and the broader context ( Lewin, 1935 , 1951 ). Thus, if organizational structures, processes, and practices clearly communicate the importance of gender equality then the discriminatory behavior of sexist organizational decision makers should be constrained. Accordingly, organizations should take steps to mitigate institutional discrimination by focusing on organizational structures, processes, and practices rather than focusing solely on reducing sexism in individual employees.

Our model does not consider how women’s occupational status is affected by their preferences for gender-role-consistent careers and their childcare and family responsibilities, which perhaps should not be underestimated (e.g., Manne, 2001 ; Hakim, 2006 ; Ceci et al., 2009 ). In other words, lifestyle preferences could contribute to gender differences in the workplace. However, it is important to consider how women’s agency in choosing occupations and managing work-life demands is constrained. Gender imbalances (e.g., in pay) in the workplace (e.g., Moss-Racusin et al., 2012 ; Sheltzer and Smith, 2014 ) and gender imbalances in the home (e.g., in domestic labor, childcare; Bianchi, 2000 ; Bianchi et al., 2000 ) shape the decisions that couples (when they consist of a woman and a man) make about how to manage dual careers. For instance, research has uncovered that women with professional degrees leave the labor force at roughly three times the rate of men ( Baker, 2002 ). Women’s decisions to interrupt their careers were difficult and were based on factors, such as workplace inflexibility, and their husbands’ lack of domestic responsibilities, rather than a preference to stay at home with their children ( Stone and Lovejoy, 2004 ). Thus, both factors inside and outside the workplace constrain and shape women’s career decisions.

Our model is derived largely from research that has been conducted in male-dominated organizations; however, we speculate that it should hold for female-dominated organizations. There is evidence that tokenism does not work against men in terms of their promotion potential in female-dominated environments. Rather, there is some evidence for a glass-escalator effect for men in female-dominated fields, such as nursing, and social work ( Williams, 1992 ). In addition, regardless of the gender composition of the workplace, men are advantaged, compared with women in terms of earnings and wage growth ( Budig, 2002 ). Finally, even in female-dominated professions, segregation along gender lines occurs in organizational structure ( Snyder and Green, 2008 ). Thus, the literature suggests that our model should hold for female-dominated environments.

Some might question if our model assumes that organizational decision makers enacting HR practices are men. It does not. There is evidence that decision makers who are women also discriminate against women (e.g., the Queen Bee phenomenon; Ellemers et al., 2004 ). Further, although men are higher in hostile sexism, compared with women ( Glick et al., 1997 , 2000 ), they are not necessarily higher in benevolent sexism ( Glick et al., 2000 ). More importantly, the effects of hostile and benevolent sexism are not moderated by participant gender ( Masser and Abrams, 2004 ; Salvaggio et al., 2009 ; Good and Rudman, 2010 ). Thus, those who are higher in hostile or benevolent sexism respond in a more discriminatory manner, regardless of whether they are men or women. Thus, organizational decision makers, regardless of their sex, should discriminate more against women in HR practices when they are higher in hostile or benevolent sexism.

In future work, the consequences of our model for women discriminated against in HR practices should be considered. The negative ramifications of sexism and discrimination on women are well known: physical and psychological stress, worse physical health (e.g., high blood pressure, ulcers, anxiety, depression; Goldenhar et al., 1998 ); lower job satisfaction, organizational commitment, and attachment to work ( Murrell et al., 1995 ; Hicks-Clarke and Iles, 2000 ); lower feelings of power and prestige ( Gutek et al., 1996 ); and performance decrements through stereotype threat ( Spencer et al., 1999 ). However, how might these processes differ depending on the proximal cause of the discrimination?

Our model lays out two potential paths by which women might be discriminated against in HR practices: institutional discrimination stemming from organizational structures, processes, and practices and personal discrimination stemming from organizational decision makers’ levels of sexism. In order for the potential stressor of stigmatization to lead to psychological and physical stress it must be seen as harmful and self-relevant ( Son Hing, 2012 ). Thus, if institutional discrimination in organizational structures, processes, and practices are completely hidden then discrimination might not cause stress reactions associated with stigmatization because it may be too difficult for women to detect ( Crosby et al., 1986 ; Major, 1994 ), and label as discrimination ( Crosby, 1984 ; Stangor et al., 2003 ). In contrast, women should be adversely affected by stigmatization in instances where gender discrimination in organizational structures, processes, and practices is more evident. For instance, greater perceptions of discrimination are associated with lower self-esteem in longitudinal studies ( Schmitt et al., 2014 ).

It might appear that we have created a model, which is a closed system, with no opportunities to change an organization’s trajectory: more unequal organizations will become more hierarchical, and more equal organizations will become more egalitarian. We do not believe this to be true. One potential impetus for organizations to become more egalitarian may be some great shock such as sex-based discrimination lawsuits that the organization either faces directly or sees its competitors suffer. Large corporations have been forced to settle claims of gender harassment and gender discrimination with payouts upward of $21 million ( Gilbert v. DaimlerChrysler Corp., 2004 ; LexisNexis, 2010 ; Velez, et al. v. Novartis Pharmaceuticals Crop, et al., 2010 ). Discrimination lawsuits are time consuming and costly ( James and Wooten, 2006 ), resulting in lower shares, lower public perceptions, higher absenteeism, and higher turnover ( Wright et al., 1995 ). Expensive lawsuits experienced either directly or indirectly should act as a big driver in the need for change.

Furthermore, individual women can work to avoid stigmatization. Women in the workplace are not simply passive targets of stereotyping processes. People belonging to stigmatized groups can engage in a variety of anti-stigmatization techniques, but their response options are constrained by the cultural repertoires available to them ( Lamont and Mizrachi, 2012 ). In other words, an organization’s culture will provide its members with a collective imaginary for how to behave. For instance, it might be unimaginable for a woman to file a complaint of sexual harassment if she knows that complaints are never taken seriously. Individuals do negotiate stigmatization processes; however, this is more likely when stigmatization is perceived as illegitimate and when they have the resources to do so ( Major and Schmader, 2001 ). Thus, at an individual level, people engage in strategies to fight being discriminated against but these strategies are likely more constrained for those who are most stigmatized.

Finally, possibly the most efficacious way for organizational members (men and women) to challenge group-based inequality and to improve the status of women as a whole is to engage in collective action (e.g., participate in unions, sign petitions, organize social movements, recruit others to join a movement; Klandermans, 1997 ; Wright and Lubensky, 2009 ). People are most likely to engage in collective action when they perceive group differences as underserved or illegitimate ( Wright, 2001 ). Such a sense of relative deprivation involves feelings of injustice and anger that prompt a desire for wide scale change ( van Zomeren et al., 2008 ). Interestingly, people are more likely to experience relative deprivation when inequalities have begun to be lessened, and thus their legitimacy questioned ( Crosby, 1984 ; Kawakami and Dion, 1993 ; Stangor et al., 2003 ). If organizational leaders respond to such demands for change by altering previously gender oppressive organizational structures, processes, and practices, this can, in people’s minds, open the door for additional changes. Therefore, changes to mitigate gender inequalities within any organizational structure, policy, or practice could start a cascade of transformations leading to a more equal organization for men and women.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgment

This research was supported by funding from the Canadian Institute for Advanced Research (CIFAR) awarded to Leanne S. Son Hing.

• ^ In this study, candidates were identified with initials and participants were asked to indicate the presumed gender of the candidate after evaluating them.

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Keywords : hostile sexism, benevolent sexism, institutional discrimination, human resources practices, gender harassment, personal discrimination

Citation: Stamarski CS and Son Hing LS (2015) Gender inequalities in the workplace: the effects of organizational structures, processes, practices, and decision makers’ sexism. Front. Psychol. 6:1400. doi: 10.3389/fpsyg.2015.01400

Received: 27 January 2015; Accepted: 02 September 2015; Published: 16 September 2015.

Reviewed by:

Copyright © 2015 Stamarski and Son Hing. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Leanne S. Son Hing, Department of Psychology, University of Guelph, Guelph, ON N1G 2W1, Canada, [email protected]

† These authors have contributed equally to this work.

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Prevalence of workplace discrimination and mistreatment in a national sample of older U.S. workers: The REGARDS cohort study

Desta fekedulegn.

a Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA

Toni Alterman

b Surveillance Branch, Division of Surveillance, Hazard Evaluations, and Field Studies, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA

Luenda E. Charles

Kiarri n. kershaw.

c Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Monika M. Safford

d Weill Cornell Medicine, Weill Cornell Medical College, New York, NY, USA

Virginia J. Howard

e Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

Leslie A. MacDonald

f Industrywide Studies Branch, Division of Surveillance, Hazard Evaluations, and Field Studies, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA

Associated Data

Although workplace discrimination and mistreatment (WDM) has recently drawn widespread media attention, our understanding of the prevalence of these phenomena remains limited. In the current study, we generated national prevalence estimates of WDM from a community-based cohort of employed black and white men and women aged ≥48 years. Measures of WDM in the current job were obtained by computer-assisted telephone interview (2011–2013) involving dichotomous responses (yes or no) to five questions and deriving a composite measure of discrimination (yes to at least one). Prevalence estimates and age- and region-adjusted prevalence ratios were derived with use of SUDAAN software to account for the complex sample design. Analyses were stratified by race and sex subgroups. This sample represents over 40 million U.S. workers aged ≥48 years. The prevalence of workplace discrimination ranged from a high of 25% for black women to a low of 11% for white men. Blacks reported a 60% higher rate of discrimination compared to whites; women reported a 53% higher prevalence of discrimination, compared with men. The prevalence of workplace mistreatment ranged from 13% for black women to 8% for white men. Women reported a 52% higher prevalence of mistreatment compared to men, while differences by race were not significant. Mistreatment was 4–8 times more prevalent among those reporting discrimination than among those reporting none. Subgroup differences in mistreatment were confined to the wage-employed. Findings suggest that middle age and older wage-employed blacks and women experience the highest prevalence of WDM; moreover, discrimination is strongly associated with mistreatment. This study contributes to our understanding of at-risk segments of the U.S. labor market and the need for targeted interventions to reduce WDM.

• • US workplace discrimination and mistreatment for those aged ≥48 years is reported.
• • Workplace discrimination and mistreatment varied significantly by race and sex.
• • Workplace discrimination and mistreatment is most prevalent among black women.
• • Mistreatment is 4–8 times more prevalent among workers reporting discrimination.
• • Among self-employed and those aged ≥65, mistreatment did not vary by race or sex.

1. Introduction

Despite more than five decades of federal legislation in the United States designed to protect workers against discrimination based on sex, race, color, national origin, religion (Title VII of the Civil Rights Act of 1964), age (Age Discrimination in Employment Act of 1967), and disability (Title I and Title V of the Americans with Disabilities Act of 1990), workplace discrimination remains a pervasive problem. A recent report by the U.S. Equal Employment Opportunity Commission (EEOC) indicates that over 80,000 workplace discrimination charges were filed in 2017 (30% sex-based, 34% race-based, and 22% age-related), resulting in nearly $400 million in compensation for victims across the private sector and state and local governments ( EEOC, 2018 ). Moreover, age discrimination is a costly problem representing $810 million in monetary benefits between 2010 and 2018 ( EEOC, 2019 ), and the proportion of the older U.S. workforce (≥55 years) has been on the rise for more than a decade and represents the fastest growing segment of the U.S. workforce ( Fisher, Matthews, & Gibbons, 2016 ; Toossi, 2013 ).

Definitions of workplace discrimination vary by discipline ( Okechukwu, Souza, Davis, & de Castro, 2014 ), generally characterized as unfair terms or conditions (e.g., reduced opportunity) or negative treatment based on personal characteristics or membership in a particular social group such as race, sex or age ( Chou & Choi, 2011 ; Dhanani, Beus, & Joseph, 2017 ; Rospenda, Richman, & Shannon, 2009 ). Age-based discrimination, for example, may stem from stereotypes about the willingness of older workers to accept change and their level of competence, which may manifest as a reluctance to hire, promote, train or otherwise extend opportunities due to age. ( Rippon, 2018 ). Workplace discrimination can occur at the organizational or the interpersonal level, and may vary in severity, source, and motive ( McCord, Joseph, Dhanani, & Beus, 2018 ).

A separate but related subject, not currently prohibited by law, is workplace mistreatment ( WBI, 2017a , WBI, 2017b ). Workplace mistreatment is defined as interpersonal behaviors that inflict physical or psychological harm to a worker, and can originate from sources within the workplace (e.g., supervisors or coworkers) or from outside the organization (e.g., clients, customers, or patients) ( Schat & Kelloway, 2005 ). Workplace mistreatment is often broadly characterized as threats, harassment, or bullying – interpersonal behaviors that can manifest more specifically as incivility, ostracism, conflict, aggression, unwanted sexual attention, and abusive supervision.

While the national prevalence of workplace discrimination and mistreatment (WDM) in the U.S. workforce has been previously reported ( Alterman, Luckhaupt, Dahlhamer, Ward, & Calvert, 2013 ; Avery, McKay, & Wilson, 2008 ; Chavez, Ornelas, Lyles, & Williams, 2015 ; Chou & Choi, 2011 ; Lutgen-Sandvik & Namie, 2009 ; Rospenda et al., 2009 ; Schat, Frone, & Kelloway, 2006 ), existing research suffers from a number of limitations. First, most studies have relied on small or moderately sized samples ( Chou & Choi, 2011 (n = 420); Avery et al., 2008 (n = 763); Rospenda et al., 2009 (n = 2151); Schat et al., 2006 (n = 2500)). A number of studies have used the Health and Retirement Survey ( Giasson, Queen, Larkina, & Smith, 2017 ; Han and Richardson, 2015 ; Rippon, Zaninotto, & Steptoe, 2015 ) and another used data from the Midlife in United States II (MIDUS II) study ( Chou & Choi, 2011 ) to look at the prevalence of age discrimination in the workplace within the older segment of the workforce (e.g., those aged ≥ 50 years who represent over two-fifths of the U.S. workforce and growing) ( BLS, 2017 ; Toossi, 2013 ). Although the Health and Retirement Survey ( Giasson et al., 2017 ; Han and Richardson 2015; ; Rippon et al., 2015 ), MIDUS II ( Chou & Choi, 2011 ), the National Health Interview Survey ( Alterman et al., 2013 ), and the Equal Employment Opportunity Commission 40th Anniversary Civil Rights in the Workplace Survey, (conducted by Gallup) ( Avery et al., 2008 ) oversampled minorities for more reliable prevalence estimates, other studies have not. Findings from the most recent national studies on discrimination were based on data collected nearly a decade ago. Only one prior study examined both workplace discrimination and mistreatment ( Rospenda et al., 2009 ). Despite growing research on the effects of WDM, little is known about the magnitude of differences in the prevalence of WDM by race-sex subgroups ( McCord et al., 2018 ). Prior studies able to explore race- or sex-specific differences were confined to convenience samples or population-based surveys with limited geographical representation, narrow labor market representation and/or demographic composition, and were often limited by small sample sizes ( Hammond, Gillen, & Yen, 2010 ; Lutgen-Sandvik, Tracy, & Alberts, 2007 ; Nunez-Smith et al., 2009 ; Simons, 2008 ; Triana, Jayasinghe, & Pieper, 2015 ).

The purpose of this study was to generate national prevalence estimates of WDM in middle-age and older U.S. workers by race-sex subgroups, to examine the magnitude of subgroup differences, and to investigate whether individuals who experienced discrimination reported more frequent mistreatment than those who did not. Using data from a national population-based sample of middle aged and older black and white men and women employed across a range of sectors within the U.S. labor market, we generate national prevalence estimates of perceived WDM by race-sex subgroups and examine the magnitude of subgroup differences. This study also examined the cross-sectional association between workplace discrimination and mistreatment.

This study contributes to our understanding of WDM in four specific ways: (1) provides national prevalence estimates of WDM; discrimination and mistreatment originating from a work context is considered more damaging than in other life domains, both for those who experience and for those who witness it ( Dhanani et al., 2017 ); (2) strengthens the literature on age discrimination at the workplace; (3) includes a large sample of black and white men and women aged ≥48 years, representing 44% of the employed U.S. workforce ( BLS, 2017 ); and (4) identifies subgroups within the U.S. workforce disproportionately affected by WDM. Relative to existing national studies, the current study improves estimates of the prevalence of WDM through (a) use of a larger sample size; (b) the assessment of age discrimination, which is a neglected area of research; (c) the assessment of both discrimination and mistreatment; (d) sampling among older workers who comprise the fastest growing segment of the U.S. labor force; (e) oversampling of blacks to obtain more reliable prevalence estimates; and (g) more recent data that would serve as important benchmark for prevalence of WDM prior to the widespread and continuing national news reports of workplace sexual harassment and mistreatment in the media.

2.1. Study sample

The REasons for Geographic and Racial Differences in Stroke (REGARDS) study involves a national, population-based, longitudinal cohort of 30,239 non-Hispanic black and non-Hispanic white participants aged ≥45 years enrolled between 2003 and 2007. Enrollment consisted of a Computer Assisted Telephone Interview (CATI), followed by completion of an in-home clinical exam and self-administered questionnaires ( Howard et al., 2005 ). The study sought to elucidate reasons for regional and racial differences in stroke incidence in the United States, specifically, the excess stroke-related mortality among blacks and residents of the southeast.

The study design provided for approximately equal representation by race and sex, through recruitment of participants via stratified random sampling with strata defined by region, race, and sex. The design involved intentional oversampling of blacks and residents of the geographic regions referred to as the “stroke buckle” (coastal North Carolina, South Carolina, and Georgia) and “stroke belt” (remainder of North Carolina, South Carolina, and Georgia, as well as Alabama, Mississippi, Tennessee, Arkansas, and Louisiana). Nearly one-half of the study participants were from the “stroke belt/buckle” region, while the remaining half were from the remaining 40 contiguous U.S. states and the District of Columbia. Participants gave consent verbally by phone and later in writing during a clinical exam. The Institutional Review Board at the University of Alabama at Birmingham (UAB) approved the study methods.

The sample for the current analyses was drawn from the REGARDS occupational ancillary study ( MacDonald, Pulley, Hein, & Howard, 2014 ). All active REGARDS study participants were asked to complete an occupational survey during routine bi-annual follow-up by CATI, a median 6.5 years after enrollment. Over a 2-year period (2011–2013), 17,648 participants consented to the occupational survey (87% response). Further details on data collection methods and measures are available elsewhere ( MacDonald et al., 2014 ). Institutional review boards at the UAB and the National Institute for Occupational Safety and Health (NIOSH) approved the ancillary study. Participants were eligible for inclusion in the current analyses if they were employed at the time of the occupational survey (n = 4949). Individuals who did not answer all the questions related to workplace discrimination and mistreatment (n = 130), whose occupational status (n = 3) or educational status (n = 2) was missing, or who were employed in farming, fishing, and forestry (n = 16, due to small sample size) were excluded. After these exclusions, data from 4798 participants were analyzed, from which the weighted proportions were 11% black (n = 1616) and 47.4% women (2,581).

2.2. Measures

Measures of workplace discrimination and mistreatment were selected from the NIOSH Quality of Work Life Questionnaire (NIOSH QWL) ( NIOSH, 2010 ). We assessed workplace discrimination at the current job by asking the following four single-item binary (yes, no) questions:

• (1) “On your job, do you feel in any way discriminated against because of your race or ethnic origin?”
• (2) “On your job, do you feel in any way discriminated against because of your sex?”
• (3) “On your job, do you feel in any way discriminated against because of your age?”
• (4) “On your job, do you feel in any way discriminated against for any other reason?”

In addition, a composite measure of discrimination was derived to represent the occurrence of any type of discrimination (i.e., yes to at least one of the 4 discrimination measures). We assessed workplace mistreatment by the following single-item binary (yes, no) question: “In the last 12 months, were you threatened, bullied, or harassed by anyone while you were on the job?”

2.3. Statistical analysis

Survey procedures in the SAS-callable SUDAAN software (version 11.0.1, Research Triangle Institute, Research Triangle Park, North Carolina) were used to estimate population-level summary measures, accounting for sample weights, stratification, and other complex design features similar to those described for other national surveys ( Korn & Graubard, 2011 ; Mirel et al., 2013 ). The REGARDS sampling weights derived for the full cohort were revised to reflect the race/sex/age/region composition of the occupational ancillary study sample. Descriptive analyses to characterize the sociodemographic characteristics of the sample were performed with a PROC CROSSTAB procedure. Adjusted prevalence and prevalence ratios (PRs) of discrimination and mistreatment and their associated 95% confidence intervals (CIs) were estimated with weighted logistic regression (PROC RLOGIST) ( Bieler, Brown, Williams, & Brogan, 2010 ). All estimates (prevalence and PRs) were adjusted for race, sex, age, and region (stroke belt, stroke buckle, and other). A PR was considered statistically significant if the 95% CI did not contain the null value (PR = 1.00). All proportions and prevalence results reported have been weighted.

Adjusted prevalence and PRs by race-sex subgroups, race, and sex were estimated from logistic regression models for each discrimination and mistreatment measure as a function of race (2 levels), sex (2 levels), interaction between race and sex (4 levels), age (continuous), and region (3 levels). Sensitivity analyses were performed to examine the influence of age strata when the discrimination data were collected (aged 48–64 versus ≥65 years). Additional sensitivity analyses were performed to evaluate the influence of employment type (wage vs. self-employed).

Logistic regression analyses were used to examine the association between discrimination and mistreatment. Estimates of adjusted prevalence and PRs of mistreatment were derived from models with the following predictors: discrimination type (2 level), race (2 levels), sex (2 levels), three-way interaction between discrimination type, race, and sex (8 levels), age (continuous), and region (3 levels). Separate models were fitted for four forms of discrimination and the composite discrimination measure (five models total).

3.1. Sociodemographic characteristics

The study sample comprised employed 4798 participants, representing a population of >40 million U.S. workers aged 48 years or older. Sociodemographic characteristics of the sample are shown overall and by race-sex subgroups in Table 1 . The study population was half male (53%), and the majority were white (89%); the race-sex composition was 6% black women (BW), 5% black men (BM), 42% white women (WW), and 47% white men (WM). At the time of the occupational survey, 27% were aged 48–54 years, 50% were aged 55–64 years, and 23% were aged ≥65 years. Nearly 60% were college graduates. The majority were wage-employed (76%), with nearly 60% employed in management and professional occupations, 20% employed in sales and office, 10% in service, and <10% in skilled and general manual labor occupations. Seventeen percent lived in the stroke belt/buckle region and 44% had a household income of ≥$75,000. Median tenure in the current job was nearly 13 years. There were significant differences in education, occupation, household income, and type of employment across the four race-sex subgroups (p < 0.01).

Sociodemographic characteristics of U.S. workers aged ≥48 years, by race-sex subgroups.

Percentages (that is, prevalences) might not sum to 100 because of rounding.

Type of employment, supervisory status, self-employed type of work, representation by union, and work hours preference were all defined for the current job the participants held at the time of the occupational survey. “Ever on shift work” reflects lifetime shift work status, whereas “currently on shift work” reflects shift work status at the time of the occupational survey.

Note: after application of sampling weights, the 4798 participants in the sample represent 40,352,947 workers in the U.S. population (5.9% black women, 5.1% black men, 41.5% white women, and 47.4% white men).

3.2. Prevalence of workplace discrimination and mistreatment

There were no statistically significant differences in the prevalence of age discrimination by race-sex subgroups, race, or sex ( Table 2 ), which ranged from a high of 10% for BW to a low of 6% for WM ( Fig. 1 ). The prevalence of racial discrimination was seven times higher for blacks than whites (PR = 7.01, 95% CI: 4.27–11.5) ( Table 2 ) and ranged from a high of 17% for BW and 12% for BM to a low of 2% for WW and WM ( Fig. 1 ). Moreover, racial discrimination was 10 times higher among BW than WW (PR = 10.1, 95% CI: 5.01–20.4), whereas racial discrimination was 5 times higher among BM than WM (PR = 5.03, 95% CI: 2.48–10.2) ( Table 2 ). The prevalence of sex discrimination was 5 times higher among women than among men (PR = 5.36, 95% CI: 2.89–9.92) ( Table 2 ), ranging from a high of 11% for BW and 8% for WW to a low of 2% for BM and WM ( Fig. 1 ). The comparison of sex discrimination between men and women was similar between blacks and whites (BW vs BM: PR = 5.45, 95% CI: 2.41–12.3; and WW vs. WM: PR = 5.34, 95% CI: 2.63–10.8). The prevalence of sex discrimination did not differ significantly by race ( Table 2 ).

Prevalence ratio (PR) of workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups, race, and sex.

Prevalence of workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups.

The prevalence of “any other” form of workplace discrimination was 82% higher among blacks than among whites (PR = 1.82, 95% CI: 1.19–2.77) ( Table 2 ), ranging from a high of 9% for BM and 8% for BW to lows of 5% for WW and 4% for WM ( Fig. 1 ). Reports from BM of other forms of workplace discrimination were more than twofold higher than those from WM (PR = 2.37, 95% CI: 1.21–4.65).

The prevalence of experiencing at least one form of workplace discrimination ranged from a high of 25% for BW (18% for BM and 16% for WW) to a low of 11% for WM ( Fig. 1 ), with significant differences by race-sex subgroups, race, and sex. Overall, blacks experienced a 60% higher prevalence of discrimination compared to whites (PR = 1.60, 95% CI: 1.27–2.00) ( Table 2 ). Specifically, BW experienced a 51% higher prevalence of discrimination than WW (PR = 1.51, 95% CI: 1.17–1.95), and BM experienced a 71% higher prevalence of discrimination than WM (PR = 1.71, 95% CI: 1.15–2.56). Overall, the reported prevalence of discrimination was 53% higher for women than for men (PR = 1.53, 95% CI: 1.16–2.02), whereas WW experienced 56% higher prevalence of discrimination than WM (PR = 1.56, 95% CI: 1.13–2.16).

The prevalence of workplace mistreatment was 52% higher among women than men (PR = 1.52, 95% CI: 1.07–2.17), ranging from a high of 13% for BW to a low of 8% for WM ( Fig. 1 ). Race-sex subgroups were not significantly different except for WW, who had a 57% higher prevalence of mistreatment than WM (PR = 1.57, 95% CI: 1.05–2.35) ( Table 2 ).

3.3. Sensitivity analysis

The pattern of results reported previously for the full sample were replicated by age strata (48–64 and ≥ 65 years) ( Table S1 and Fig. S1 ). Prevalence ratios for exposure to at least one form of discrimination did not change among younger workers (aged 48–64 years). However, among workers aged ≥65 years, there were no significant subgroup differences in the prevalence of mistreatment. Differences in the prevalence of “any discrimination” (i.e., at least one) were confined to black and white men and race overall. The prior pattern of subgroup results for the prevalence ratios for racial discrimination and any discrimination were mostly consistent when analyses were run by employment type (wage- and self-employed) ( Table S2 and Fig. S2 ). Mistreatment did not vary by race or sex among the self-employed. However, wage-employed blacks experienced a higher prevalence of age and sex discrimination than did wage-employed whites ( Table S2 ), while self-employed blacks experienced a lower prevalence of age discrimination than did self-employed whites.

3.4. Association of discrimination with mistreatment

The prevalence of mistreatment, stratified by discrimination type, is presented in Fig. 2 . Among workers who experienced any discrimination, the prevalence of mistreatment ranged from a high of 34% for WM, 34% for WW, and 31% for BW, to a low of 26% for BM ( Fig. 2 ). Among those who did not report any discrimination, the prevalence of mistreatment was low, ranging from 5% for WM to 7% for BW. The data in Fig. 2 show that those reporting discrimination experienced a substantially higher prevalence of mistreatment compared with those who did not report discrimination. Mistreatment was 4–8 times more prevalent among those reporting at least one form of discrimination compared with those reporting none ( Table 3 ). For example, the prevalence of mistreatment among black women who reported at least one form of discrimination was nearly 5 times higher than those reporting no discrimination (PR = 4.71, 95% CI: 2.71–8.19; BM: PR = 3.65, 1.65–8.10; WW: PR = 4.40, 2.84–6.84; and WM: PR = 7.54, 4.13–13.8) ( Table 3 ).

Prevalence of workplace mistreatment among U.S. workers aged ≥48 years, by discrimination in race-sex subgroups.

Association between workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups.

Values (%) in the table represent the prevalence ratios (PRs) comparing prevalence of mistreatment in those who experienced discrimination relative to those who did not experience discrimination in each race-sex subgroup.

4. Discussion

We generated national estimates of the prevalence of workplace discrimination and mistreatment by race, sex, and race-sex subgroups for a sample of black and white men and women aged ≥48 years. By including measures of both discrimination (race, sex, age, any other reason) and mistreatment, we provide a more complete understanding of WDM in the U.S. workforce than many prior studies. The prevalence of workplace discrimination varied significantly by race, sex, and race-sex subgroups, with a higher prevalence among blacks compared with whites and a higher prevalence among women compared with men. The prevalence of workplace mistreatment varied by sex, with a higher prevalence among women compared with men (overall) and a higher prevalence among white women compared with white men.

Our findings corroborate prior research indicating that racial minorities experience race-based workplace discrimination at higher rates compared to whites ( Avery et al., 2008 ; ( Rospenda et al., 2009 ). In our study, the prevalence of race-based workplace discrimination was 7 times higher among blacks compared to whites but there was no significant difference in race-based discrimination by sex. Similarly, findings from the Behavioral Risk Factor Surveillance System (BRFSS, 2004–2010, n = 70,080) showed that the prevalence of racial discrimination was significantly higher among blacks compared to whites (21.2% vs 4.2%), whereas differences in the prevalence of racial discrimination by sex were not significant (Chavez at al., 2015).

In addition, our finding that blacks and women have a higher prevalence of exposure to at least one form of workplace discrimination compared with whites and men is also consistent with prior findings in occupation-specific studies ( Hammond et al., 2010 ; Nunez-Smith et al., 2009 ; Sellers, Cherepanov, Hanmer, Fryback, & Palta, 2013 ). Following a survey of U.S. physicians conducted in 2006–2007 (n = 529), Nunez-Smith et al. (2009) reported substantial differences in prevalence of perceived racial/ethnic workplace discrimination at the current job, by race: 59% of black, 39% of Asian, 35% of “other” race, 24% of Hispanic/Latino, and 21% of white physicians reported experiencing discrimination “sometimes, often, or very often.” In a study of hospital workers in northern California, Hammond et al. (2010) reported that the prevalence of race-based workplace discrimination (in the past year) was significantly higher among blacks than among whites (19.7% vs. 3.1%), whereas racial differences in the prevalence of sex and age discrimination were not significant. In the current study, the prevalence of age discrimination was similar across subgroups, ranging from a high of 9.5% among BM to a low of 6.3% among WM; the overall prevalence of age discrimination among older workers was 6.9% but did not manifest differentially across subgroups.

A study of employees from five organizations reported that minority women were subject to double jeopardy at work, experiencing the most sexual harassment because they were both women and members of a minority group ( Berdahl & Moore, 2006 ). Although black women in the current study experienced a 32% higher prevalence of sex discrimination compared to white women, the difference was not statistically significant. The difference between the two studies may be due to differences in the sex discrimination measure used (Berdahl and Moore used a 19-item questionnaire to assess sexual harassment, while the current study used a single question) or sample size.

Our findings are consistent with prior research suggesting that women experience elevated levels of workplace discrimination ( Avery et al., 2008 ; Rospenda et al., 2009 ) and mistreatment compared to men ( Berdahl & Moore, 2006 ; Magley, Gallus, & Bunk, 2010 ; McCord et al., 2018 ; Okechukwu et al., 2014 ; Saad, 2015 ). Results of a recent Gallup poll indicate that 12% of working women, versus 5% of working men, reported feeling they had been passed over for a promotion or other opportunity because of their sex ( Saad, 2015 ). A recent meta-analysis indicated that women report significantly more sex-based workplace mistreatment than men ( McCord et al., 2018 ). While our global measure of mistreatment (threatened, bullied or harassed) did not illicit whether the mistreatment was sex-based, women in our study were 50 percent more likely to experience mistreatment than men. Because our findings were gathered in 2011–2013, they serve as important benchmarks for WDM prevalence prior to the widespread and continuing national news reports of sexual workplace harassment and mistreatment reported among high-profile individuals in the entertainment and media industries ( Cobb & Horeck, 2018 ).

The prevalence of workplace mistreatment was significantly higher for women than for men (12.1% vs. 8.0%), but racial differences (11.8% for blacks vs. 9.7% for whites) were not statistically significant. Comparing our results to the 2010 National Health Interview Survey, which has a nearly identical measure of mistreatment, we report a marginally higher prevalence of mistreatment overall (9.9% vs. 7.8%) and for women (12.1% vs. 9.3%), blacks (11.8% vs. 8.2%), and whites (9.7% vs. 7.9%) ( Alterman et al., 2013 ). Our findings are also consistent with results from the 2017 national survey by the Workplace Bullying Institute (WBI), which reported that 9% of workers were bullied in the past year, and that women were most often the targets of workplace bullying ( WBI, 2017c ).

In sensitivity analyses, results for exposure to at least one form of discrimination and for mistreatment in the overall sample were consistent for all sub-group comparisons in the lower age strata (48–64 years). In the higher age strata (≥65 years), results were consistent only for discrimination involving comparisons between black men vs. white men and blacks vs. whites; the non-significant findings for the other subgroup comparisons may be due to true smaller subgroup differences among older workers combined with reduced statistical power. Discordant findings for exposure to mistreatment among older workers (aged ≥ 65 years) involving comparisons between white women and white men and women vs men are similarly impacted by reduced statistical power; however, a change in the direction of the effect estimates from positive to negative for subgroup comparisons by sex suggests possible effect modification that will need to be confirmed in future research with a larger sample.

Results for exposure to at least one form of discrimination and for mistreatment in the overall sample were consistent with the results for all sub-group comparisons involving wage, but not self-employed, individuals. The non-significant sub-group differences in exposure to discrimination among the self-employed may be due to true smaller differences in combination with reduced statistical power. Discordant findings for exposure to mistreatment among the self-employed may also be influenced by reduced statistical power but, more importantly, changes in the direction of the effect estimates from positive to negative for most subgroup comparisons suggests possible effect modification by employment type that will need to be confirmed in future research with a larger sample.

Differential exposure to WDM by race, sex, and race-sex subgroups has important public health implications. Previous research has shown that exposure to WDM can be physically and psychologically harmful to the targeted individuals ( Dhanani et al., 2017 ; Høgh, Mikkelsen, & Hansen, 2011 ; Lewis, Cogburn, & Williams, 2015 ; Nielsen & Einarsen, 2012 ; Okechukwu et al., 2014 ; Pascoe & Smart Richman, 2009 ; Rospenda et al., 2009 ). It has been theorized by Dhanani et al. (2017) that workplace discrimination threatens a person's sense of self and increases feelings of marginalization, which induces a stress response manifesting in adverse mental and physical health as well as poor employee performance outcomes (negative job attitudes, decreased positive and increased negative workplace behaviors, sickness-related absenteeism, turnover, grievance, compensation and litigation, and reduced productivity) ( Dhanani et al., 2017 ; Hoel, Sheehan, Cooper, & Einarsen, 2011 ; Triana et al., 2015 ). The negative impacts of discrimination on physical health outcomes ( Lewis et al., 2015 ) includes objective clinical disease outcomes (all-cause mortality, hypertension, incident breast cancer, and incident asthma) and preclinical outcomes with established linkages to later disease (carotid intima media thickness, coronary artery calcification, nighttime blood pressure elevation, increase in visceral fat, and inflammation). WDM also can influence the adoption or exacerbation of unhealthy behaviors such as smoking and drinking ( Chavez et al., 2015 ; Pascoe & Smart Richman, 2009 ; Rospenda et al., 2009 ). Even subtle and interpersonal forms of discrimination, which are often overlooked, are as detrimental to those targeted as are the more typical, overt forms of discrimination ( Jones, Peddie, Gilrane, King, & Gray, 2016 ). These reports of adverse effects, combined with our findings of differential exposure, suggest that WDM may be an important under-recognized determinant of health disparities by race and sex.

This study has several limitations. Due to constraints on survey administration time, we used single-item measures to characterize WDM. Single-item measures of complex psychological constructs have shortcomings ( Fisher et al., 2016 ; Hoeppner, Kelly, Urbanoski, & Slaymaker, 2011 ; Krieger, Smith, Naishadham, Hartman, & Barbeau, 2005 ): they are more vulnerable than multiple-item measures to random measurement errors and internal-consistency reliability statistics cannot be computed. The global single-item measure of mistreatment used in our study (i.e., threatened, bullied, or harassed on the job in the past 12 months) makes it infeasible to learn the prevalence of different forms of mistreatment and how exposure to specific types of mistreatment (e.g., sexual harassment, bullying) vary by race-sex subgroups. Worker populations whose jobs involve greater social or interpersonal interactions (e.g., healthcare or service workers) may have more opportunities for being subject to mistreatment or discrimination. As is true for much of the WDM research conducted to date, the source of discrimination or mistreatment (such as a customer or client, a superior, peer, or subordinate) was not identified in our study.

Data collection for exposure to WDM was restricted to the current job; a participant who held multiple jobs concurrently reported their experiences at the job where they spent the majority of their working hours. Sensitivity analyses were likely underpowered; therefore, we cannot rule out that differences reported by age strata and employment type are due to chance. Because data on sex-race composition of the participant's workplace were not collected, we cannot examine whether race-sex differences in the prevalence of WDM varies by minority/majority status. This study collected self-reported sex as a binary variable when other identifications of sex and gender relevant to the study of WDM are possible (e.g., transsexual, transgender). It is not possible to know if those exposed to “any other form of discrimination” included individuals with non-binary identities.

While the racial diversity of the sample was limited to non-Hispanic whites and blacks, we expect our findings to be generalizable to the majority of the U.S. workforce aged ≥48 years because the racial composition of the older segment of the U.S. workforce is majority white and black (US Senate Special Committee on Aging Report ( ADD, 2017 ). However, our results are not generalizable to other racial and ethnic minority groups. Despite the aforementioned limitations, this study represents an important contribution to our understanding of the prevalence of discrimination and mistreatment among workers in the United States. Strengths of this study include the large national population-based sample of middle-aged and older (aged ≥ 48 years) black and white men and women employed across 77% of all detailed U.S. Census occupation codes. This is one of the first national studies to examine associations between discrimination and mistreatment in an employed sample.

In conclusion, our results suggest that women and blacks employed across a broad range of the US labor market perceived more workplace discrimination than men and whites, respectively. Race differences were more pronounced for race-based discrimination, whereas sex differences were more pronounced for sex-based discrimination, relative to other forms of discrimination. Although women experienced more workplace mistreatment than men, there were no significant differences in mistreatment by race. Overall, our findings regarding race and sex differences are consistent with other research with younger employed samples. Our results also suggest that discrimination may be a determinant of mistreatment, with those experiencing discrimination reporting a higher prevalence of mistreatment compared with their counterparts. However, due to the cross-sectional design, we cannot establish that discrimination precedes mistreatment; it is possible that mistreatment precedes discrimination. It is also worth noting that mistreatment may be a way to circumvent illegal forms of harassment and discrimination (e.g., to sexually harass without the risk of being accused of sexual harassment). Investigation using a longitudinal rather than cross-sectional design would be appropriate to establish casual direction. The imbalance in prevalence of WDM among women and racial minorities represents an important focus for both prevention and intervention.

Acknowledgments

This research project is supported by cooperative agreement U01 NS041588, co-funded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging, National Institutes of Health, Department of Health and Human Services. The occupational ancillary study is supported by intramural funding by the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions is available at www.regardsstudy.org/ . The authors additionally thank Cathy Tinney-Zara (Biostatistics and Epidemiology Branch, HELD/NIOSH) for proofreading and Seleen Collins (Information Resources and Dissemination Branch, EID/NIOSH) for editing the manuscript.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ssmph.2019.100444 .

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS, NIA, CDC, or NIOSH. Representatives of NINDS and NIOSH were involved in the review of the manuscript but not directly involved in the collection, management, analysis, or interpretation of the data.

Ethical approval

The Institutional Review Boards at the University of Alabama at Birmingham (UAB) and the National Institute for Occupational Safety and Health (NIOSH) approved the study.

The prevalences represent weighted population estimates and were adjusted for stratification variables (race, sex, age at time of enrollment, and region of residence at time of enrollment). “At least one” refers to experiencing at least one of the four discrimination types (age, racial, sex, or other).

The error bars represent the estimate plus/minus the standard error (SE), not the confidence interval (CI) and hence conclusions about the statistical significance of differences between groups cannot be made by looking at whether the error bars overlap or not.

The prevalences represent weighted population estimates and were adjusted for stratification variables (race, sex, age at time of enrollment, and region of residence at time of enrollment). “At least one” refers to experiencing at least one of the four discrimination types (age, racial, sex, or other). The error bars represent the estimate plus/minus the standard error (SE), not the confidence interval (CI) and hence conclusions about the statistical significance of differences between groups cannot be made by looking at whether the error bars overlap or not.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

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Research: How Bias Against Women Persists in Female-Dominated Workplaces

• Amber L. Stephenson,
• Leanne M. Dzubinski

A look inside the ongoing barriers women face in law, health care, faith-based nonprofits, and higher education.

New research examines gender bias within four industries with more female than male workers — law, higher education, faith-based nonprofits, and health care. Having balanced or even greater numbers of women in an organization is not, by itself, changing women’s experiences of bias. Bias is built into the system and continues to operate even when more women than men are present. Leaders can use these findings to create gender-equitable practices and environments which reduce bias. First, replace competition with cooperation. Second, measure success by goals, not by time spent in the office or online. Third, implement equitable reward structures, and provide remote and flexible work with autonomy. Finally, increase transparency in decision making.

It’s been thought that once industries achieve gender balance, bias will decrease and gender gaps will close. Sometimes called the “ add women and stir ” approach, people tend to think that having more women present is all that’s needed to promote change. But simply adding women into a workplace does not change the organizational structures and systems that benefit men more than women . Our new research (to be published in a forthcoming issue of Personnel Review ) shows gender bias is still prevalent in gender-balanced and female-dominated industries.

• Amy Diehl , PhD is chief information officer at Wilson College and a gender equity researcher and speaker. She is coauthor of Glass Walls: Shattering the Six Gender Bias Barriers Still Holding Women Back at Work (Rowman & Littlefield). Find her on LinkedIn at Amy-Diehl , Twitter @amydiehl , and visit her website at amy-diehl.com
• AS Amber L. Stephenson , PhD is an associate professor of management and director of healthcare management programs in the David D. Reh School of Business at Clarkson University. Her research focuses on the healthcare workforce, how professional identity influences attitudes and behaviors, and how women leaders experience gender bias.
• LD Leanne M. Dzubinski , PhD is acting dean of the Cook School of Intercultural Studies and associate professor of intercultural education at Biola University, and a prominent researcher on women in leadership. She is coauthor of Glass Walls: Shattering the Six Gender Bias Barriers Still Holding Women Back at Work (Rowman & Littlefield).

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Gender discrimination comes in many forms for today’s working women.

The survey – conducted in the summer before a recent wave of sexual misconduct allegations against prominent men in politics, the media and other industries – found that, among employed adults, women are about twice as likely as men (42% versus 22%) to say they have experienced at least one of eight specific forms of gender discrimination at work.

One of the biggest gender gaps is in the area of income: One-in-four working women (25%) say they have earned less than a man who was doing the same job; one-in-twenty working men (5%) say they have earned less than a female peer.

Women are roughly four times as likely as men to say they have been treated as if they were not competent because of their gender (23% of employed women versus 6% of men), and they are about three times as likely as men to say they have experienced repeated small slights at work because of their gender (16% versus 5%).

There are significant gaps on other items as well. While 15% of working women say they have received less support from senior leaders than a man who was doing the same job, only 7% of working men report having a similar experience. One-in-ten working women say they have been passed over for the most important assignments because of their gender, compared with 5% of men.

The survey, which was conducted July 11-Aug. 10, 2017, with a nationally representative sample of 4,914 adults (including 4,702 who are employed at least part time), also asked about sexual harassment in a separate question. It found that while similar shares of women and men say sexual harassment is at least a small problem in their workplace (36% versus 35%), women are about three times as likely as men to have experienced it personally while at work (22% versus 7%).

In more recent surveys conducted by other organizations, the share of women reporting personal experiences with sexual harassment has fluctuated, depending in part on how the question was asked. In an ABC News/Washington Post survey conducted Oct. 12-15, for example, 54% of women said they have received unwanted sexual advances from a man that they felt were inappropriate whether or not those advances were work-related; 30% said this had happened to them at work. In an NPR/PBS NewsHour/Marist poll conducted Nov. 13-15, 35% of women said they have personally experienced sexual harassment or abuse from someone in the workplace.

The Center’s survey asked about sexual harassment specific to the workplace. The survey was conducted as part of a broader forthcoming study on women and minorities in science, technology, engineering and math (STEM) fields.

Differences by education

Among employed women, the share saying they have experienced sexual harassment in the workplace is roughly similar across racial and ethnic, educational, generational and partisan lines. But when it comes to specific forms of workplace discrimination tested in the survey, there are significant differences among women that are rooted mainly in their level of education.

Women with a bachelor’s degree or more education report experiencing discrimination across a range of items at significantly higher rates than women with less education. And in some regards, the most highly educated women stand out. While 57% of working women with a postgraduate degree say they have experienced some form of gender discrimination at work, for example, the same is true for 40% of women with a bachelor’s degree and 39% of those who did not complete college.

When it comes to wages, working women with a bachelor’s degree or more are much more likely than those with less education to say they have earned less than a man who performed the same job. Women with family incomes of $100,000 or higher stand out here as well – 30% of them say they’ve earned less than a man who was doing comparable work compared with roughly one-in-five women with lower incomes (21%). But overall, women with higher family incomes are about equally likely to have experienced at least one of these eight forms of gender-based discrimination at work.

Women’s experiences with discrimination in the workplace also differ along party lines. Roughly half (48%) of working Democratic women and Democratic-leaning independents say they have experienced at least one form of gender discrimination at work, compared with a third of Republican and Republican-leaning women. These party differences hold up even after controlling for race. The partisan gap is in keeping with wide party differences among both men and women in their views of gender equality in the U.S.; a separate 2017 Pew Research Center survey found Democrats largely dissatisfied with the country’s progress toward gender equality.

About the survey: These are some of the findings from a survey conducted among a nationally representative sample of 4,914 adults, ages 18 and older, from July 11-Aug. 10, 2017. The survey, which was conducted online in English and in Spanish through GfK’s Knowledge Panel, included an oversample of employed adults working in science, technology, engineering and math-related fields. The margin of sampling error based on the 4,702 employed adults in the sample is plus or minus 2.0 percentage points. The margin of sampling error based on the 2,344 employed women in the sample is plus or minus 3.0 percentage points. See the  topline  for exact question wording.

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For Women’s History Month, a look at gender gains – and gaps – in the U.S.

Key takeaways on americans’ views on gender equality a century after u.s. women gained the right to vote, most americans support gender equality, even if they don’t identify as feminists, activism on gender equality differs widely by education among democratic women, 61% of u.s. women say ‘feminist’ describes them well; many see feminism as empowering, polarizing, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .