research paper about gender discrimination

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

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 ​ Figure1 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.

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 ​ Figure1 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 ​ Figure1 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.

Acknowledgments

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

1 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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• Published: 28 April 2020

The impact a-gender: gendered orientations towards research Impact and its evaluation

• J. Chubb   ORCID: orcid.org/0000-0002-9716-820X 1 &
• G. E. Derrick   ORCID: orcid.org/0000-0001-5386-8653 2  

Palgrave Communications volume  6 , Article number:  72 ( 2020 ) Cite this article

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A Correction to this article was published on 19 May 2020

This article has been updated

Using an analysis of two independent, qualitative interview data sets: the first containing semi-structured interviews with mid-senior academics from across a range of disciplines at two research-intensive universities in Australia and the UK, collected between 2011 and 2013 ( n  = 51); and the second including pre- ( n  = 62), and post-evaluation ( n  = 57) interviews with UK REF2014 Main Panel A evaluators, this paper provides some of the first empirical work and the grounded uncovering of implicit (and in some cases explicit) gendered associations around impact generation and, by extension, its evaluation. In this paper, we explore the nature of gendered associations towards non-academic impact (Impact) generation and evaluation. The results suggest an underlying yet emergent gendered perception of Impact and its activities that is worthy of further research and exploration as the importance of valuing the ways in which research has an influence ‘beyond academia’ increases globally. In particular, it identifies how researchers perceive that there are some personality traits that are better orientated towards achieving Impact; how these may in fact be gendered. It also identifies how gender may play a role in the prioritisation of ‘hard’ Impacts (and research) that can be counted, in contrast to ‘soft’ Impacts (and research) that are far less quantifiable, reminiscent of deeper entrenched views about the value of different ‘modes’ of research. These orientations also translate to the evaluation of Impact, where panellists exhibit these tendencies prior to its evaluation and describe the organisation of panel work with respect to gender diversity.

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Introduction.

The management and measurement of the non-academic impact Footnote 1 (Impact) of research is a consistent theme within the higher education (HE) research environment in the UK, reflective of a drive from government for greater visibility of the benefits of research for the public, policy and commercial sectors (Chubb, 2017 ). This is this mirrored on a global scale, particularly in Australia, where, at the ‘vanguard’ (Upton et al., 2014 , p. 352) of these developments, methods were first devised (but were subsequently abandoned) to measure research impact (Chubb, 2017 ; Hazelkorn and Gibson, 2019 ). What is broadly known in both contexts as an ‘Impact Agenda’—the move to forecast and assess the ways in which investment in academic research delivers measurable socio-economic benefit—initially sparked broad debate and in some instances controversy, among the academic community (and beyond) upon its inception (Chubb, 2017 ). Since then, the debate has continued to evolve and the ways in which impact can be better conceptualised and implemented in the UK, including its role in evaluation (Stern, 2016 ), and more recently in grant applications (UKRI, 2020 ) is robustly debated. Notwithstanding attempts to better the culture of equality and diversity in research, (Stern, 2016 ; Nature, 2019 ) in the broader sense, and despite the implementation of the Impact agenda being studied extensively, there has been very little critical engagement with theories of gender and how this translates specifically to more downstream gendered inequities in HE such as through an impact agenda.

The emergence of Impact brought with it many connotations, many of which were largely negative; freedom was questioned, and autonomy was seen to be at threat because of an audit surveillance culture in HE (Lorenz, 2012 ). Resistance was largely characterised by problematising the agenda as symptomatic of the marketisation of knowledge threatening traditional academic norms and ideals (Merton, 1942 ; Williams, 2002 ) and has led to concern about how the Impact agenda is conceived, implemented and evaluated. This concern extends to perceptions of gendered assumptions about certain kinds of knowledge and related activities of which there is already a corpus of work, i.e., in the case of gender and forms of public engagement (Johnson et al., 2014 ; Crettaz Von Roten, 2011 ). This paper explores what it terms as ‘the Impact a-gender’ (Chubb, 2017 ) where gendered notions of non-academic, societal impact and how it is generated feed into its evaluation. It does not wed itself to any feminist tradition specifically, however, draws on Carey et al. ( 2018 ) to examine, acknowledge and therefore amend how the range of policies within HE and how implicit power dynamics in policymaking produce gender inequalities. Instead, an impact fluidity is encouraged and supported. For this paper, this means examining how the impact a-gender feeds into expectations and the reward of non-academic impact. If left unchecked, the propagation of the impact a-gender, it is argued, has the potential to guard against a greater proportion of women generating and influencing the use of research evidence in public policy decision-making.

Scholars continue to reflect on ‘science as a gendered endeavour’ (Amâncio, 2005 ). The extensive corpus of historical literature on gender in science and its originators (Merton, 1942 ; Keller et al., 1978 ; Kuhn, 1962 ), note the ‘pervasiveness’ of the ‘masculine’ and the ‘objective and the scientific’. Indeed, Amancio affirmed in more recent times that ‘modern science was born as an exclusively masculine activity’ ( 2005 ). The Impact agenda raises yet more obstacles indicative of this pervasiveness, which is documented by the ‘Matthew’/‘Matilda’ effect in Science (Merton, 1942 ; Rossiter, 1993 ). Perceptions of gender bias (which Kretschmer and Kretschmer, 2013 hypothesise as myths in evaluative cultures) persist with respect to how gender effects publishing, pay and reward and other evaluative issues in HE (Ward and Grant, 1996 ). Some have argued that scientists and institutions perpetuate such issues (Amâncio, 2005 ). Irrespective of their origin, perceptions of gendered Impact impede evaluative cultures within HE and, more broadly, the quest for equality in excellence in research impact beyond academia.

To borrow from Van Den Brink and Benschop ( 2012 ), gender is conceptualised as an integral part of organisational practices, situated within a social construction of feminism (Lorber, 2005 ; Poggio, 2006 ). This article uses the notion of gender differences and inequality to refer to the ‘ hierarchical distinction in which either women and femininity and men and masculinity are valued over the other ’ (p. 73), though this is not precluding of individual preferences. Indeed, there is an emerging body of work focused on gendered associations not only about ‘types’ of research and/or ‘areas and topics’ (Thelwall et al., 2019 ), but also about what is referred to as non-academic impact. This is with particular reference to audit cultures in HE such as the Research Excellence Framework (REF), which is the UK’s system of assessing the quality of research (Morley, 2003 ; Yarrow and Davies, 2018 ; Weinstein et al., 2019 ). While scholars have long attended to researching gender differences in relation to the marketisation of HE (Ahmed, 2006 ; Bank, 2011 ; Clegg, 2008 ; Gromkowska-Melosik, 2014 ; Leathwood et al., 2008 ), and the gendering of Impact activities such as outreach and public engagement (Ward and Grant, 1996 ), there is less understanding of how far academic perceptions of Impact are gendered. Further, how these gendered tensions influence panel culture in the evaluation of impact beyond academia is also not well understood. As a recent discussion in the Lancet read ‘ the causes of gender disparities are complex and include both distal and proximal factors ’. (Lundine et al., 2019 , p. 742).

This paper examines the ways in which researchers and research evaluators implicitly perceive gender as related to excellence in Impact both in its generation and in its evaluation. Using an analysis of two existing data sets; the pre-evaluation interviews of evaluators in the UK’s 2014 Research Excellence Framework and interviews with mid-senior career academics from across the range of disciplines with experience of building impact into funding applications and/ or its evaluation in two research-intensive universities in the UK and Australia between 2011 and 2013, this paper explores the implicitly gendered references expressed by our participants relating to the generation of non-academic, impact which emerged inductively through analysis. Both data sets comprise researcher perceptions of impact prior to being subjected to any formalised assessment of research Impact, thus allowing for the identification of unconscious gendered orientations that emerged from participant’s emotional and more abstract views about Impact. It notes how researchers use loaded terminology around ‘hard’, and ‘soft’ when conceptualising Impact that is reminiscent of long-standing associations between epistemological domains of research and notions of masculinity/femininity. It refers to ‘hard’ impact as those that are associated with meaning economic/ tangible and efficiently/ quantifiably evaluated, and ‘soft’ as denoting social, abstract, potentially qualitative or less easily and inefficiently evaluated. By extending this analysis to the gendered notions expressed by REF2014 panellists (expert reviewers whose responsibility it is to review the quality of the retrospective impact articulated in case studies for the purposes of research evaluation) towards the evaluation of Impact, this paper highlights how instead of challenging these tendencies, shared constructions of Impact and gendered productivity in academia act to amplify and embed these gendered notions within the evaluation outcomes and practice. It explores how vulnerable seemingly independent assessments of Impact are to these widespread gendered- associations between Impact, engagement and success. Specifically, perceptions of the excellence and judgements of feasibility relating to attribution, and causality within the narrative of the Impact case study become gendered.

The article is structured as follows. First, it reviews the gender-orientations towards notions of ‘hard’ and ‘soft’ excellence in forms of scholarly distinction and explores how this relates to the REF Impact evaluation criteria, and the under-representation of women in the academic workforce. Specifically, it hypothesises the role of how gendered notions of excellence that construct academic identities contribute to a system that side-lines women in academia. This is despite associating the generation of Impact as a feminised skill. We label this as the ‘Impact a-gender’. The article then outlines the methodology and how the two, independent databases were combined and convergent themes developed. The results are then presented from academics in the UK and Australia and then from REF2014 panellists. This describes how the Impact a-gender currently operates through academic cultural orientations around Impact generation, and in its evaluation through peer-review panels by members of this same academic culture. The article concludes with a recommendation that the Impact a-gender be explored more thoroughly as a necessary step towards guiding against gender- bias in the academic evaluation, and reward system.

Literature review

Notions of impact excellence as ‘hard’ or ‘soft’.

Scholars have long attempted to consider the commonalities and differences across certain kinds of knowledge (Becher, 1989 , 1994 ; Biglan, 1973a ) and attempts to categorise, divide and harmonise the disciplines have been made (Biglan, 1973a , 1973b ; Becher, 1994 ; Caplan, 1979 ; Schommer–Aikins et al., 2003 ). Much of this was advanced with a typology of the disciplines from (Trowler, 2001 ), which categorised the disciplines as ‘hard’ or ‘soft’. Both anecdotally and in the literature, ‘soft’ science is associated with working more with people and less with ‘things’ (Cassell, 2002 ; Thelwall et al., 2019 ). These dichotomies often lead to a hierarchy of types of Impact and oppose valuation of activities based on their gendered connotations.

Biglan’s system of classifying disciplines into groups based on similarities and differences denotes particular behaviours or characteristics, which then form part of clusters or groups—‘pure’, ‘applied’, ‘soft’, ‘hard’ etc. Simpson ( 2017 ) argues that Biglan’s classification persists as one of the most commonly referred to models of the disciplines despite the prominence of some others (Pantin, 1968 ; Kuhn, 1962 ; Smart et al., 2000 ). Biglan ( 1973b ) classified the disciplines across three dimensions; hard and soft, pure and applied, life and non-life (whether the research is concerned with living things/organisms) . This ‘taxonomy of the disciplines’ states that ‘pure-hard’ domains tend toward the life and earth sciences,’pure-soft’ the social sciences and humanities, and ‘applied hard’ focus on engineering and physical science with ‘soft-applied’ tending toward professional practice such as nursing, medicine and education. Biglan’s classification looked at levels of social connectedness and specifically found that applied scholars Footnote 2 were more socially connected, more interested and involved in service activities, and more likely to publish in the form of technical reports than their counterparts in the pure (hard) areas of study. This resonates with how Impact brings renewed currency and academic prominence to applied researchers (Chubb, 2017 ). Historically, scholars inhabiting the ‘hard’ disciplines had a greater preference for research; whereas, scholars representing soft disciplines had a greater preference for teaching (Biglan, 1973b ). Further, Biglan ( 1973b ) also found that hard science scholars sought out greater collaborative efforts among colleagues when teaching as opposed to their soft science counterparts.

There are also long-standing gendered associations and connotations with notions of ‘hard’ and ‘soft’ (Storer, 1967 ). Typically used to refer to skills, but also used heavily with respect to the disciplines and knowledge domains, gendered assumptions and the mere use of ‘hard’ or ‘soft’ to describe knowledge production carries with it assumptions, which are often noted in the literature; ‘ we think of physics as hard and of political science as soft ’, Storer explains, adding how ‘hard seems to imply tough, brittle, impenetrable and strong, while soft on the other hand calls to mind the qualities of weakness, gentleness and malleability’ (p. 76). As described, hard science is typically associated with the natural sciences and quantitative paradigms whereas normative perceptions of feminine ‘soft’ skills or ‘soft’ science are often equated with qualitative social science. Scholars continue to debate dichotomised paradigms or ‘types’ of research or knowledge (Gibbons, 1999 ), which is emblematic of an undercurrent of epistemological hierarchy of the value of different kinds of knowledge. Such debates date back to the heated back and forth between scholars Snow (Snow, 2012 ) and literary critic Leavis who argued for their own ‘cultures’ of knowledge. Notwithstanding, these binary distinctions do few favours when gender is then ascribed to either knowledge domain or related activity (Yarrow and Davies, 2018 ). This is particularly pertinent in light of the current drive for more interdisciplinary research in the science system where there is also a focus on fairness, equality and diversity in the science system.

Academic performance and the Impact a-gender

Audit culture in academia impacts unfairly on women (Morley, 2003 ), and is seen as contributory to the wide gender disparities in academia, including the under-representation of women as professors (Ellemers et al., 2004 ), in leadership positions (Carnes et al., 2015 ), in receiving research acknowledgements (Larivière et al., 2013 ; Sugimoto et al., 2015 ), or being disproportionately concentrated in non-research-intensive universities (Santos and Dang Van Phu, 2019 ). Whereas gender discrimination also manifests in other ways such as during peer review (Lee and Noh, 2013 ), promotion (Paulus et al., 2016 ), and teaching evaluations (Kogan et al., 2010 ), the proliferation of an audit culture links gender disparities in HE to processes that emphasise ‘quantitative’ analysis methods, statistics, measurement, the creation of ‘experts’, and the production of ‘hard evidence’. The assumption here is that academic performance and the metrics used to value, and evaluate it, are heavily gendered in a way that benefits men over women, reflecting current disparities within the HE workforce. Indeed, Morely (2003) suggests that the way in which teaching quality is female dominated and research quality is male dominated, leads to a morality of quality resulting in the larger proportion of women being responsible for student-focused services within HE. In addition, the notion of ‘excellence’ within these audit cultures implicitly reflect images of masculinity such as rationality, measurement, objectivity, control and competitiveness (Burkinshaw, 2015 ).

The association of feminine and masculine traits in academia (Holt and Ellis, 1998 ), and ‘gendering its forms of knowledge production’ (Clegg, 2008 ), is not new. In these typologies, women are largely expected to be soft-spoken, nurturing and understanding (Bellas, 1999 ) yet often invisible and supportive in their ‘institutional housekeeping’ roles (Bird et al., 2004 ). Men, on the other hand are often associated with being competitive, ambitious and independent (Baker, 2008 ). When an individual’s behaviour is perceived to transcend these gendered norms, then this has detrimental effects on how others evaluate their competence, although some traits displayed outside of these typologies go somewhat ‘under the radar’. Nonetheless, studies show that women who display leadership qualities (competitiveness, ambition and decisiveness) are characterised more negatively than men (Rausch, 1989 ; Heilman et al., 1995 ; Rossiter, 1993 ). Incongruity between perceptions of ‘likeability’ and ‘competence’ and its relationship to gender bias is present in evaluations in academia, where success is dependent on the perceptions of others and compounded within an audit culture (Yarrow and Davis, 2018). This has been seen in peer review, reports for men and women applicants, where women were disadvantaged by the same characteristics that were seen as a strength on proposals by men (Severin et al., 2019 ); as well as in teaching evaluations where women receive higher evaluations if they are perceived as ‘nurturing’ and ‘supportive’ (Kogan et al., 2010 ). This results in various potential forms of prejudice in academia: Where traits normally associated with masculinity are more highly valued than those associated with femininity (direct) or when behaviour that is generally perceived to be ‘masculine’ is enacted by a woman and then perceived less favourably (indirect/ unconscious). That is not to mention direct sexism, rather than ‘through’ traits; a direct prejudice.

Gendered associations of Impact are not only oversimplified but also incredibly problematic for an inclusive, meaningful Impact agenda and research culture. Currently, in the UK, the main funding body for research in the UK, UK Research and Innovation (UKRI) uses a broad Impact definition: ‘ the demonstrable contribution that excellent research makes to society and the economy ’ (UKRI website, 2019 ). The most recent REF, REF2014, Impact was defined as ‘ …an effect on, change or benefit to the economy, society, culture, public policy or services, health, the environment or quality of life, beyond academia ’. In Australia, the Australian Research Council (ARC) proposed that researchers should ‘embed’ Impact into the research process from the outset. Both Australia and the UK have been engaged in policy borrowing around the evaluation of societal impact and share many similarities in approaches to generating and evaluating it. Indeed, Impact has been deliberately conceptualised by decision-makers, funders and governments as broad in order to increase the appearance of being inclusivity, to represent a broad range of disciplines, as well as to reflect the ‘diverse ways’ that potential beneficiaries of academic research can be reached ‘beyond academia’. The adoption of societal impact as a formalised criterion in the evaluation of research excellence was initially perceived to be potentially beneficial for women, due to its emphasis on concepts such as ‘public engagement’; ‘duty’ and non-academic ‘cooperation/collaboration’ (Yarrow and Davies, 2018 ). In addition, the adoption of narrative case studies to demonstrate Impact, rather than adopting a complete metrics-focused exercise, can also be seen as an opportunity for women to demonstrate excellence in the areas where they are over-represented, such as teaching, cultural enrichment, public engagement (Andrews et al., 2005 ), informing public policy and improving public services (Schatteman, 2014 ; Wheatle and BrckaLorenz, 2015). However, despite this, studies highlight how for the REF2014, only 25% of Impact Case Studies for business and management studies were from women (Davies et al., 2020 ).

With respect to Impact evaluation, previous research shows that there is a direct link between notions of academic culture, and how research (as a product of that culture) is valued and evaluated (Leathwood and Reid, 2008 ; p. 120). Geertz ( 1983 ) argues that academic membership is a ‘cultural frame that defines a great part of one’s life’ influences belief systems around how academic work is orientated. This also includes gendered associations implicit in the academic reward system, which in turn influences how academics believe success is to be evaluated, and in what form that success emerges. This has implications in how academic associations of the organisation of research work and the ongoing constructions of professional identity relative to gender, feeds into how these same academics operate as evaluators within a peer review system evaluation. In this case, instead of operating to challenge these tendencies, shared constructions of gendered academic work are amplified to the extent that they unconsciously influence perceptions of excellence and the judgements of feasibility as pertaining to the attribution and causality of the narrative argument. As such, in an evaluation of Impact with its ambiguous definition (Derrick, 2018 ), and the lack of external indicators to signal success independent of cultural constructions inherent in the panel membership, effects are assumed to be more acute. In this way, this paper argues that the Impact a-gender can act to further disadvantage women.

The research combines two existing research data sets in order to explore implicit notions of gender associated with the generation and evaluation of research Impact beyond academia. Below the two data sets and the steps involved in analysing and integrating findings are described along with our theoretical positioning within the feminist literature Where verbatim quotation is used, we have labelled the participants according to each study highlighting their role and gender. Further, the evaluator interviews specify the disciplinary panel and subpanel to which they belonged, as well as their evaluation responsibilities such as: ‘Outputs only’; ‘Outputs and Impact’; and ‘Impacts only’.

Analysis of qualitative data sets

This research involved the analysis and combination of two independently collected, qualitative interview databases. The characteristics and specifics of both databases are outlined below.

Interviews with mid-senior academics in the UK and Australia

Fifty-one semi-structured interviews were conducted between 2011 and 2013 with mid-senior academics at two research-intensive universities in Australia and the UK. The interviews were 30–60 min long and participants were sourced via the research offices at both sites. Participants were contacted via email and invited to participate in a study concerning resistance towards the Impact agenda in the UK and Australia and were specifically asked for their perceptions of its relationship with freedom, value and epistemic responsibility and variations across discipline, career stage and national context. Mostly focused on ex ante impact, some interviewees also described their experiences of Impact in the UK and Australia, in relation to its formal assessment as part of the Excellence Innovation Australia (EIA) for Australia and the Research Excellence Framework (REF) in the UK.

Participants comprised mid to senior career academics with experience of winning funding from across the range of disciplines broadly representative of the arts and humanities, social sciences, physical science, maths and engineering and the life and earth sciences. For the purposes of this paper, although participant demographic information was collected, the relationship between the gender of the participants, their roles, disciplines/career stage was not explicitly explored instead, such conditions were emergent in the subsequent inductive coding during thematic analysis. A reflexive log was collected in order to challenge and draw attention to assumptions and underlying biases, which may affect the author, inclusive of their own gender identity. Further information on this is provided in Chubb ( 2017 ).

Pre- and post-evaluation interviews with REF2014 evaluators

REF2014 in the UK represented the world’s first formalised evaluation of ex-post impact, comprising of 20% of the overall evaluation. This framework served as a unique experimental environment with which to explore baseline tendencies towards impact as a concept and evaluative object (Derrick, 2018 ).

Two sets of semi-structured interviews were conducted with willing participants: sixty-two panellists were interviewed from the UK’s REF2014 Main Panel A prior to the evaluation taking place; and a fifty-seven of these were re-interviewed post-evaluation. Main Panel A covers six Sub-panels: (1) Clinical Medicine; (2) Public Health, Health Services and Primary Care; (3) Allied Health Professions, Dentistry, Nursing and Pharmacy; (4) Psychology, Psychiatry and Neuroscience; (5) Biological Sciences; and (6) Agriculture, Veterinary and Food Sciences. Again, the relationship between the gender of the participants and their discipline is not the focus for the purposes of this paper.

Database combination and identification of common emergent themes

The inclusion of data sets using both Australian and UK researchers was pertinent to this study as both sites were at the cusp of implementing the evaluation of Impact formally. These researcher interviews, as well as the evaluator interviews were conducted prior to any formalised Impact evaluation took place, but when both contexts required ex ante impact in terms of certain funding allocation, meaning an analysis of these baseline perceptions between databases was possible. Further, the inclusion of the post-evaluation interviews with panellists in the UK allowed an exploration of how these gendered perceptions identified in the interviews with researchers and panellists prior to the evaluation, influenced panel behaviour during the evaluation of Impact.

Initially, both data sets were analysed using similar, inductive, grounded-theory-informed approaches inclusive of a discourse and thematic analysis of the language used by participants when describing impact, which allowed for the drawing out of metaphor (Zinken et al., 2008 ). This allowed data combination and analysis of the two databases to be conducted in line with the recommendations for data-synthesis as outlined in Weed ( 2005 ) as a form of interpretation. This approach guarded against the quantification of qualitative findings for the purposes of synthesis, and instead focused on an initial dialogic approach between the two authors (Chubb and Derrick), followed by a re-analysis of qualitative data sets (Heaton, 1998 ) in line with the outcomes of the initial author-dialogue as a method of circumventing many of the drawbacks associated with qualitative data-synthesis. Convergent themes from each, independently analysed data set were discussed between authors, before the construction of new themes that were an iterative analysis of the combined data set. Drawing on the feminist tradition the authors did not apply feminist standpoint theory, instead a fully inductive approach was used to unearth rich empirical data. An interpretative and inductive approach to coding the data using NVIVO software in both instances was used and a reflexive log maintained. The availability of both full, coded, qualitative data sets, as well as the large sample size of each, allowed this data-synthesis to happen.

Researcher’s perceptions of Impact as either ‘hard’ or ‘soft’

Both UK and Australian academic researchers (researchers) perceive a guideline of gendered productivity (Davies et al., 2017 ; Sax et al., 2002 ; Astin, 1978 ; Ward and Grant, 1996 ). This is where men or women are being dissuaded (by their inner narratives, their institutions or by colleagues) from engaging in Impact either in preference to other (more masculine) notions of academic productivity, or towards softer (for women) because they consider themselves and are considered by others to be ‘good at it’. Participants often gendered the language of Impact and introduced notions of ‘hard’ and ‘soft’. On the one hand, this rehearses and resurfaces long-standing views about the ‘Matthew Effect’ because often softer Impacts were seen as being of less value by participants, but also indicates that the word impact itself carries its own connotations, which are then weighed down further by more entrenched gender associations.

Our research shows that when describing Impact, it was not necessarily the masculinity or femininity of the researcher that was emphasised by participants, rather researchers made gendered presumptions around the type of Impact, or the activity used to generate it as either masculine or feminine. Some participants referred to their own research or others’ research as either ‘hard’ or as ‘soft and woolly’. Those who self-professed that their research was ‘soft’ or woolly’ felt that their research was less likely to qualify as having ‘hard’ impact in REF terms Footnote 3 ; instead, they claimed their research would impact socially, as opposed to economically; ‘ stuff that’s on a flaky edge — it’s very much about social engagement ’ (Languages, Australia, Professor, Male) . One researcher described Impact as ‘a nasty Treasury idea,’ comparing it to: a tsunami, crashing over everything which will knock out stuff that is precious ’ . (Theatre, Film and TV, UK, Professor, Male) . This imagery associates the concept of impact with force and weight (or hardness as mentioned earlier) particularly in disciplines where the effect of their research may be far more nuanced and subtle. One Australian research used force to depict the impact of teaching and claimed Impact was like a footprint, and teaching was ‘ a pretty heavy imprint ’ (Environment, UK, Professor, Male) . Participants characterised ‘force and weight’ as masculine, suggesting that some connotations of Impact and the associated activities may be gendered. The word ‘Impact’ was inherently perceived by many researchers as problematic, bound with linguistic connotations and those imposed by the official definitions, which in many cases are perceived as negative or maybe even gendered (Chubb, 2017 ): ‘ The etymology of a word like impact is interesting. I’ve always seen what I do as being a more subtle incremental engagement, relevance, a contribution ’. (Theatre, Film and TV, UK, Professor, Male) .

Researchers associated the word ‘impact’ with hard-ness, weight and force; ‘ anything that sorts of hits you ’ (Languages, UK, Senior Lecturer, Female) . One researcher suggested that Impact ‘ sounds kind of aggressive — the poor consumer! ’ (History, Australia, Professor, Female) . Talking about her own research in the performing arts, one Australian researcher commented: ‘ It’s such a pain in the arse because the Arts don’t fit the model. But in a way they do if you look at the impact as being something quite soft ’ (Music, Australia, Professor, Female) . Likewise, a similar comparison was seen by a female researcher from the mechanical engineering discipline: ‘ My impact case study wasn’t submitted mainly because I’m dealing with that slightly on the woolly side of things ’ (Mechanical Engineering, Australia, Professor, Female) . Largely, gender related comments hailed from the ‘hard’ science and from arts and humanities researchers. Social scientists commented less, and indeed, one levelled that Impact was perhaps less a matter of gender, and more a matter of ability (Chubb, 2017 ): ‘ It’s about being articulate! Both guys and women who are very articulate and communicate well are outward looking on all of these things ’ ( Engineering Education, Australia, Professor, Female).

Gendered notions of performativity were also very pronounced by evaluators who were assessing the outputs only, suggesting how these panel cultures are orientated around notions of gender and scientific outputs as ‘hard’ if represented by numbers. The focus on numbers was perceived by the following panellist as ‘ a real strong tendency particularly amongst the Alpha male types ’ within the panel that relate to findings about the association of certain traits—risk aversion, competitiveness, for example, with a masculinised market logic in HE;

And I like that a lot because I think that there is a real strong tendency particularly amongst the Alpha male types of always looking at the numbers, like the numbers and everything. And I just did feel that steer that we got from the panel chairs, both of them were men by the way, but they were very clear, the impact factors and citations and the rank order of a journal is this is information that can be useful, but it’s not your immediate first stop. (Panel 1, Outputs and Impact, Female)

However, a metric-dominant approach was not the result of a male-dominated panel environment and instead, to the panels credit, evaluators were encouraged not to use one-metric as the only deciding factor between star-rating of quality. However, this is not to suggest that metrics did not play a dominant role. In fact, in order to resolve arguments, evaluators were encouraged to ‘ reflect on these other metrics ’ (Panel 3, Outputs only, Male) in order to rectify arguments where the assessment of quality was in conflict. This use of ‘other metrics’ was preferential to a resolution of differences that are based on more ‘soft’ arguments that are based on understanding where differences in opinion might lie in the interpretation of the manuscript’s quality. Instead, the deciding factor in resolving arguments would be the responsibility, primarily, of a ‘hard’ concept of quality as dictated by a numerical value;

Read the paper, judge the quality, judge the originality, the rigour, the impact — if you have to because you’re in dispute with another assessor, then reflect on these other metrics. So I don’t think metrics are that helpful actually if and until you’ve got a real issue to be able to make a decision. But I worry very much that metrics are just such a simple way of making the process much easier, and I’m worried about that because I think there’s a bit of game playing going on with impact factors and that kind of thing. (Panel 3, Outputs Only, Male)

Table 1 outlines the emergent themes, which, through inductive coding participants broadly categorised domains of research, their qualities and associations, types of activities and the gendered assumption generally made by participants when describing that activity. The table is intended only to provide an indicative overview of the overall tendencies of participants toward certain narratives as is not exhaustive, as well as a guide to interpret the perceptions of Impact illustrated in the below results.

Table one describes the dichotomous views that seemed to emerge from the research but it’s important to note that researchers associated Impact as related to gender in subtle, and in some cases overt ways. The data suggests that some male participants felt that female academics might be better at Impact, suggesting that female academics might find it liberating, linked it to a sense of duty or public service, implying that it was second nature. In addition, some male participants associated types of Impact domains as female-orientated activity and the reverse was the case with female and male-orientated ‘types’ of Impact. For example, at one extreme, a few male researchers seemed to perceive public engagement as something, which females would be particularly good at, generalising that they are not competitive ‘ women are better at this! They are less competitive! ’ (Environment, UK, Professor, Male) . Indeed, one male researcher suggested that competitiveness actually helps academics have an impact and does not impede it:

I get a huge buzz from trying to communicate those to a wider audience and winning arguments and seeing them used. It’s not the use that motivates me it’s the process of winning, I’m competitive! (Economics, UK, Professor, Male)

Analysis also revealed evidence that some researchers has gendered perceptions of Impact activities just as evaluators did. Here, women were more likely to promote the importance of engaging in Impact activities, whereas men were focused on producing indicators with hard, quantitative indicators of success. Some researchers implied that public engagement was not something entirely associated with the kinds of Impact needed to advance one’s career and for a few male researchers, this was accordingly associated with female academics. Certain female researchers in the sciences and the arts suggested similarly that there was a strong commitment among women to carry out public engagement, but that this was not necessarily shared by their male counterparts who, they perceived, undervalued this kind of work:

I think the few of us women in the faculty will grapple with that a lot about the relevance of what we’re doing and the usefulness, but for the vast majority of people it’s not there… [She implies that]…I think there is a huge gender thing there that every woman that you talk to on campus would consider that the role of the university is along the latter statement (*to communicate to the public). The vast majority of men would not consider that’s a role of the university. There’s a strong gender thing. (Chemical Engineering, Australia, Professor, Female)

Notwithstanding, it is important to distinguish between engagement and Impact. This research shows that participants perceive Impact activities to be gendered. There was a sense from one arts female researcher that women might be more interested in getting out there and communicating their work but that crucially, it is not the be-all and end- all of doing research: ‘ Women feel that there’s something more liberating, I can empathise with that, but that couldn’t be the whole job ’. Music, Australia, Professor, Female Footnote 4 . When this researcher, who was very much orientated towards Impact, asked if there were enough interviewees, she added ‘ mind you, you’ve probably spoken to enough men in lab coats ’. This could imply that inward-facing roles are associated with male-orientated activity and outward facing roles as perceived as more female orientated. Such sentiments perhaps relate to a binary delineation of women as more caring, subjective, applied and of men as harder, scientific and theoretical/ rational. This links to a broader characterisation of HE as marketised and potentially, more ‘male’ or at least masculinised—where increasing competitiveness, marketisation and performativity can be seen as linked to an increasingly macho way of doing business (Blackmore, 2002 ; Deem, 1998 ; Grummell et al., 2009 ; Reay, n.d. ). The data is also suggestive of the attitude that communication is a ‘soft’ skill and the interpersonal is seen as a less masculine trait. ‘ This is a huge generalisation but I still say that the profession is so dominated by men, undergraduates are so dominated by men and most of those boys will come into engineering because they’re much more comfortable dealing with a computer than with people ’ (Chemical Engineering, Australia, Professor, Female) . Again, this suggests women are more likely to pursue those scientific subjects, which will make a difference or contribute to society (such as nursing or environmental research, certainly those subjects that would be perceived as less ‘hard’ science domains).

There was also a sense that Impact activity, namely in this case public engagement and community work, was associated with women more than men by some participants (Amâncio, 2005 ). However, public engagement and certain social impact domains appeared to have a lower status and intellectual worth in the eyes of some participants. Some inferred that social and ‘soft’ impacts are seen as associated. With discipline. For instance, research concerning STEM (Science, Technology, Engineering and Medicine) subjects with females. They in turn may be held in low esteem. Some of the accounts suggest that soft impacts are perceived by women as not ‘counting’ as Impact:

‘ At least two out of the four of us who are female are doing community service and that doesn’t count, we get zero credit, actually I would say it gets negative credit because it takes time away from everything else ’. (Education Engineering, Australia, Professor, Female)

This was intimated again by another female UK computer scientist who claimed that since her work was on the ‘woolly side’ of things, and her impacts were predominantly in the social and public domain, she would not be taken seriously enough to qualify as a REF Impact case study, despite having won an award for her work:

‘ I don’t think it helps that if I were a male professor doing the same work I might be taken more seriously. It’s interesting, why recently? Because I’ve never felt that I’ve not been taken seriously because I’m a woman, but something happened recently and I thought, oh, you’re not taking me seriously because I’m a woman. So I think it’s a part ’. (Computer Science, UK, Professor, Female)

Researchers also connect the ‘hard’ and ‘soft’ associations with Impact described earlier to male and female traits. The relationship between Impact and gender is not well understood and it is not clear how much these issues are directly relatable to Impact or more symptomatic of the broader picture in HE. In order to get a broader picture, it is important to examine how these gendered notions of Impact translate into its evaluation. Some participants suggested that gender is a factor in the securing of grant money—certainly this comment reveals a local speculation that ‘the big boys’ get the grants, in Australia, at least: ‘ ARC grants? I’ve had a few but nothing like the big boys that get one after the other ,’ (Chemical Engineering, Australia, Professor, Female) . This is not dissimilar to the ‘alpha male’ comments from the evaluators described below who note a tendency for male evaluators to rely on ‘hard’ numbers whose views are further examined in the following section.

Gendered excellence in Impact evaluation

In the pre-evaluation interviews, panellists were asked about what they perceived to be ‘excellent’ research and ‘excellent’ Impact. Within this context, are mirrored conceptualisations of impacts as either ‘soft’ or ‘hard’ as was seen with the interviews with researchers described above. These conceptualisations were captured prior to the evaluation began. They can therefore be interpreted as the raw, baseline assumptions of Impact that are free from the effects of the panel group, showed that there were differences in how evaluators perceived Impact, and that these perceptions were gendered.

Although all researchers conceptualised Impact as a linear process for the purposes of the REF2014 exercise (Derrick, 2018 ), there was a tendency for female evaluators to be open to considering the complexity of Impact, even in a best-case scenario. This included a consideration that Impact as dictated within the narrative might have different indicators of value to different evaluators; ‘ I just think that that whole framing means that there is a form of normative standard of perfect impact ’ (Main Panel, Outputs and Impacts, Female) . This evaluator, in particular, went further to state how that their impression of Impact would be constructed from the comparators available during the evaluation;

‘ Given that I’m presenting impact as a good story, it would be like you saying to me; ‘Can you describe to me a perfect Shakespearean play?’…. well now of course, I can’t. You can give me lots of plays but they all have different kinds of interesting features. Different people would say that their favourite play was different. To me, if you’re taking interpretivist view, constructivist view, there is no perfect normative standard. It’s just not possible ’. (Panel 1, Outputs and Impacts, Female)

Female evaluators were also more sensitive to other complex factors influencing the evaluation of Impact, including time lag; ‘ …So it takes a long time for things like that to be accepted…it took hundreds of studies before it was generally accepted as real ’ (Panel 1, Outputs and Impacts, Female ); as well as the indirect way that research influences policy as a form of Impact;

‘ I don’t think that anything would get four stars without even blinking. I think that is impossible to answer because you have to look at the whole evidence in this has gone on, and how that does link to the impact that is being claimed, and then you would then have to look at how that impact, exactly how that research has impacted on the ways of the world, in terms of change or in terms of society or whatever. I don’t think you can see this would easily get four stars because of the overall process is being looked at, as well as the actual outcome ’ . (Panel 3, Outputs and Impact, Female)

Although these typologies were not absolute, there was a lack of complexity in the nuances around Impact. There was also heavily gendered language around Impacts as measurable, or not, that mirrored the association of Impact as being either ‘hard’, and therefore measurable, or ‘soft, and therefore more nuanced in value. In this way, male evaluators expressed Impact as a causal, linear event that occurred ‘ in a very short time ’ (P2, Outputs and Impact, Male) and involved a single ‘ star ’ (P3, Impacts only, Male) or ‘ impact champion ’ (Main Panel, Outputs and Impacts, Male) that drove it from start (research), to finish (Impact). These associations about Impact being ‘soft’ and ‘hard’ made by evaluators, mirror the responses from researchers in the above sections. In the example below, the evaluator used words such as ‘ strong ’ and ‘ big way ’ to describe Impact success, as well as emphasises causality in the argument;

‘ …if it has affected a lot of people or affected policy in a strong way or created change in a big way, and it can be clearly linked back to the research, and it’s made a difference ’. (Panel 2, Outputs and Impact, Male)

These perhaps show disciplinary differences as much as gendered differences. Further, there was a stronger tendency for male evaluators to strive towards conceptualisations of excellence in Impact as measurable or ‘ it’s something that is decisive and actionable ’ (Panel 6, Impacts, Male) . One male evaluator explained his conceptualised version of Impact excellence as ‘ straightforward ’ and therefore ‘ obviously four-star ’ due to the presence of metrics with which to measure Impact. This was a perception more commonly associated with male evaluators;

‘ …if somebody has been able to devise a — let’s say pancreatic cancer — which is a molecular cancer, which hasn’t made any progress in the last 40 years, and where the mortality is close to 100% after diagnosis, if someone devised a treatment where now suddenly, after diagnosis of pancreatic cancer, 90 percent of the people are now still alive 5 years later, where the mortality rate is almost 0%, who are alive after 5 years. That, of course, would be a dramatic, transformative impact ’. (Panel 1, Outputs and Impact, Male)

In addition, his tendency to seek various numeric indicators for measuring, and therefore assessing Impact (predominantly economic impact), as well as compressing its realisation to a small period of time ( ‘ suddenly ’ ) in a causal fashion, was more commonly expressed in male evaluators. This tendency automatically indicates the association of impacts as either ‘soft’ or ‘hard’ and divided along gendered norms, but also expresses Impact in monetary terms;

‘ Something that went into a patient or the company has pronounced with…has spun out and been taken up by a commercial entity or a clinical entity ’ (Panel 3, Outputs and Impacts, Male) , as well as impacts that are marketised; ‘ A new antimicrobial drug to market ’. (Panel 6, Outputs and Impact, Male) .

There was also the perception that female academics would be better at engagement (Johnson et al., 2014 ; Crettaz Von Roten, 2011 ) due to its link with notions of ‘ duty ’ (as a mother), ‘ engagement ’ and ‘ public service ’ are reflected in how female evaluators were also more open to the idea that excellent Impact is achieved through productive, ongoing partnerships with non-academic stakeholders. Here, the reflections of ‘duty’ from the evaluators was also mirrored by in interviews with researchers. Indeed, the researchers merged perceptions of parenthood, an academic career and societal impact generation. One female researcher drew on her role as a mother as supportive of her ability to participate in Impact generation, ‘ I have kids that age so… ’ (Biology, UK, Senior Lecturer, Female) . Indeed, parenthood emerged from researchers of both genders in relation to the Impact agenda. Two male participants spoke positively about the need to transfer knowledge of all kinds to society referencing their role as parents: ‘ I’m all for that. I want my kids to have a rich culture when they go to school ’ (Engineering, Australia, Professor, Male, E2) , and ‘ My children are the extension of my biological life and my students are an extension of my thoughts ’ (Engineering, Australia, Professor, Male, E1) . One UK female biologist commented that she indeed enjoys delivering public engagement and outreach and implies a reference to having a family as enabling her ability to do so: ‘ It’s partly being involved with the really well-established outreach work ,’ (Biology, UK, Senior Lecturer, Female) .

For the evaluators, the idea that ‘public service’ as second nature for female academics, was reflected in how female evaluators perceived the long, arduous and serendipitous nature of Impact generation, as well as their commitment to assessing the value of Impact as a ‘pathway’ rather than in line with impact as a ‘product’. Indeed, this was highlighted by one male evaluator who suggested that the measurement and assessment of Impact ‘ …needs to be done by economists ’ and that

‘ you [need] to put in some quantification one everything…[that] puts a negative value on being sick and a positive large value on living longer. So, yeah, the greatest impact would be something that saves us money and generates income for the country but something broad and improves quality of life ’. (Panel 2, Impacts, Male)

Since evaluators tend to exercise cognitive bias in evaluative situations (Langfeldt, 2006 ), these preconceived ideas about Impact, its generation and the types of people responsible for its success are also likely to permeate the evaluative deliberations around Impact during the peer review process. What is uncertain is the extent that these messages are dominant within the panel discourse, and therefore the extent that they influence the formation of a consensus within the group, and the ‘dominant definition’ of Impact (Derrick, 2018 ) that emerges as a result.

Notions of gender from the evaluators post-evaluation

Similar notions of gender-roles in academia pertaining to notions of scientific productivity were echoed by academics who were charged with its evaluation as part of the UK’s 2014 Research Excellence Framework. Interviews with evaluators revealed not only that the panel working-methods and characteristics about what constituted a ‘good’ evaluator were implicitly along gendered norms, but also that the assumed credit assumptions of performativity were also based on gender.

In assessments of the Impact criterion, an assessment that is not as amenable to quantitative representation requiring panels to conceptualise a very complex process, with unstandardised measures of significance and reach, there was still a gendered perception of Impact being ‘women’s work’ in academia. This perception was based on the tendency towards conceptualising Impact as ‘slightly grubby’ and ‘not very pure’, which echoes previously reported pre-REF2014 tensions that Impact is a task that an academic does when they cannot do real research (de Jong et al., 2015 );

But I would say that something like research impact is — it seems something slightly grubby. It’s not seen as not — by the academics, as not very pure. To some of them, it seems women’s work. Talking to the public, do you see what I mean? (Main Panel, Outputs and Impact, Female)

In addition, gendered roles also relate to how the panel worked with the assessment of Impact. Previous research has outlined how the equality and diversity assessment of panels for REF2014 were not conducted until after panellists were appointed (Derrick, 2018 ), leading to a lack of equal-representation of women on most panels. Some of the female panellists reflected that this resulted not only in a hyper-awareness of one’s own identity and value as a woman on the panel, but also implicitly associating the role that a female panellist would play in generating the evaluation. One panellist below, reflected that she was the only female in a male-dominated panel, and that the only other females in the room were the panel secretariat. The panellist goes further to explain how this resulted in a gendered-division of labour surrounding the assessment of Impact;

I mean, there’s a gender thing as well which isn’t directing what you’re talking about what you’re researching, but I was the only woman on the original appointed panel. The only other women were the secretariat. In some ways I do — there was initially a very gendered division of perspective where the women were all the ones aggregate the quantitative research, or typing it all up or talking about impact whereas the men were the ones who represented the big agenda, big trials. (Main Panel, Outputs and Impact, Female)

In addition, evaluators expressed opinions about what constituted a good and a bad panel member. From this, the evaluation showed that traits such as the ability to work as a ‘team’ and to build on definitions and methods of assessment for Impact through deliberation and ‘feedback’ were perceived along gendered lines. In this regard, women perceived themselves as valuable if they were ‘happy to listen to discussions’, and not ‘too dogmatic about their opinion’. Here, women were valued if they played a supportive, supplementary role in line with Bellas ( 1999 ), which was in clear distinction to men who contributed as creative thinkers and forgers of new ideas. As one panellist described;

A good panel member is an Irish female. A good panel member was someone who was happy to — someone who is happy to listen to discussions; to not be too dogmatic about their opinion, but can listen and learn, because impact is something we are all learning from scratch. Somebody who wasn’t too outspoken, was a team player. (Panel 3, Outputs and Impact, Female)

Likewise, another female evaluator reflected on the reasons for her inclusion as a panel member was due to her ‘generalist perspective’ as opposed to a perspective that is over prescribed. This was suggestive of how an overly specialist perspective would run counter to the reasons that she was included as a panellist which was, in her opinion, due to her value as an ethnic and gender ‘token’ to the panel;

‘ I think it’s also being able to provide some perspective, some general perspective. I’m quite a generalist actually, I’m not a specialist……So I’m very generalist. And I think they’re also well aware of the ethnic and gender composition of that and lots of reasons why I’m asked on panels. (Panel 1, Outputs and Impact, Female)

Women perceived their value on the panel as supportive, as someone who is prepared to work on the team, and listen to other views towards as a generalist, and constructionist, rather than as an enforced of dogmatic views and raw, hard notions of Impact that were represented through quantitative indicators only. As such, how the panel operated reflects general studies of how work can be organised along gender lines, as well as specific to workload and power in the academy. The similarity between the gendered associations towards conceptualising Impact from the researchers and evaluators, combined with how the panel organises its work along gendered lines, suggests how panel culture echoes the implicit tendencies within the wider research community. The implications of this tendency in relation to the evaluation of non-academic Impact is discussed below.

Discussion: an Impact a-gender?

This study shows how researchers and evaluators in two, independent data sets echoed a gendered orientation towards Impact, and how this implies an Impact a-gender. That gendered notions of Impact emerged as a significant theme from two independent data sets speaks to the importance of the issue. It also illustrates the need for policymakers and funding organisations to acknowledge its potential effects as part of their efforts towards embedding a more inclusive research culture around the generation and evaluation of research impact beyond academia.

Specifically, this paper has identified gendered language around the generation of, and evaluation of Impact by researchers in Australia and the UK, as well as by evaluators by the UK’s most recent Research Excellence Framework in 2014. For the UK and Australia, the prominence of Impact, as well as the policy borrowing between each country (Chubb, 2017 ) means that a reliable comparison of pre-evaluation perceptions of researchers and evaluators can be made. In both data sets presumptions of Impact as either ‘soft’ or ‘hard’ by both researchers and evaluators were found to be gendered. Whereas it is not surprising that panel culture reflects the dominant trends within the wider academic culture, this paper raises the question of how the implicit operation of gender bias surrounding notions of scientific productivity and its measurement, invade and therefore unduly influence the evaluation of those notions during peer-review processes. This negates the motivation behind a broad Impact definition and evaluation as inclusive since unconscious bias towards women can still operate if left unchecked and unmanaged.

Gendered notions of excellence were also related to the ability to be ‘competitive’, and that once Impact became a formalised, countable and therefore competitive criterion, it also become masculine where previously it existed as a feminised concept related to female academic-ness. As a feminised concept, Impact once referred to notions of excellence requiring communication such as public engagement, or stakeholder coordination—the ‘softer’ impacts. However, this association only remains ‘soft’ insofar as Impact remains unmeasurable, or more nuanced in definition. This is especially pertinent for the evaluation of societal impact where already conceived ideas of engagement and ‘ women’s work ’ influence how evaluators assess the feasibility of impact narratives for the purposes of its assessment. This paper also raises the question that notions of gender in relation to Impact persist irrespective of the identities assumed for the purposes of its evaluation (i.e., as a peer reviewer). This is not to say that academic culture in the UK and Australia, where Impact is increasingly being formalised into rewards systems, is not changing. More that there is a tendency in some evaluations for the burden of evidence to be applied differently to genders due to tensions surrounding what women are ‘good’ at doing: engagement, versus what ‘men’ are good at doing regarding Impact. In this scenario, quantitative indicators of big, high-level impacts are to be attributable to male traits, rather than female. This has already been noted in student evaluations of teaching (Kogan et al., 2010 ) and of academic leadership performance where the focus on the evaluation is on how others interpret performance based on already held gendered views about competence based on behaviours (Williams et al., 2014 ; Holt and Ellis, 1998 ). As such, when researchers transcend these gendered identities that are specific to societal impact, there is a danger of an Impact-a-gender bias arising in the assessment and forecasting of Impact. This paper extends this understanding and outlines how this may also be the case for assessments of societal impact.

By examining perceptions, as well as using an inductive analysis, this study was able to unearth unconsciously employed gendered notions that would not have been prominent or possible to pick up if we asked the interviewees about gender directly. This was particularly the case for the re-analysis of the post-evaluation interviews. However, future studies might consider incorporating a disciplinary-specific perspective as although the evaluators were from the medical/biomedical disciplines, researchers were from a range of disciplines. This would identify any discipline-specific risk towards an Impact a-gender. Nonetheless, further work that characterises the impact a-gender, as well as explores its wider implications for gender inequities within HE is currently underway.

How research evidence is labelled as excellent and therefore trustworthy, is heavily dictated by an evaluation process that is perceived as impartial and fair. However, if evaluations are compounded by gender bias, this confounds assessments of excellence with gendered expectation of non-academic impact. Consequently, gendered expectations of excellence for non-academic impact has the potential to: unconsciously dissuade women from pursuing more masculinised types of impact; act as a barrier to how female researchers mobilise their research evidence; as well as limit the recognition female researchers gain as excellent and therefore trustworthy sources of evidence.

The aim of this paper was not to criticise the panellists and researchers for expressing gendered perspectives, nor to present evidence about how researchers are unduly influenced by gender bias. The results shown do not support either of these views. However, the aim of this paper was to acknowledge how gender bias in research Impact generation can lead to a panel culture dominated by academics that translate the implicit and explicit biases within academia that influence its evaluation. This paper raises an important question regarding what we term the ‘Impact a-gender’, which outlines a mechanism in which gender bias feeds into the generation and evaluation of a research criterion, which is not traditionally associated with a hard, metrics-masculinised output from research. Along with other techniques used to combat unconscious bias in research evaluation, simply by identifying, and naming the issue, this paper intends to combat its ill effects through a community-wide discussions as a mechanism for developing tools to mitigate its wider effect if left unchecked or merely accepted as ‘acceptable’. In addition, it is suggested that government and funding organisations explicitly refer to the impact a-gender as part of their wider EDI (Equity, Diversity and Inclusion) agendas towards minimising the influence of unconscious bias in research impact and evaluation.

Data availability

Data is available upon request subject to ethical considerations such as consent so as not to compromise the individual privacy of our participants.

Change history

19 may 2020.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

For the purposes of this paper, when the text refers to non-academic, societal impact, or the term ‘Impact’ we are referring to the change and effect as defined by REF2014/2021 and the larger conceptualisation of impact that is generated through knowledge exchange and engagement. In this way, the paper refers to a broad conceptualisation of research impact that occurs beyond academia. This allows a distinction between Impact as central to this article’s contribution, as opposed to academic impact, and general word ‘impact’.

Impact scholars or those who are ‘good at impact’ are often equated with applied researchers.

One might interpret this as meaning ‘economic impact’.

This is described in the next section as ‘women’s work’ by one evaluator.

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This research was funded by the UK Economic and Social Research Council (ESRC) Future Research Leaders Programme (ES/K008897/2). We would also like to acknowledge their peers for offering their views on the paper in advance of publication and in doing so thank Dr. Richard Watermeyer, University of Bath, Professor Paul Wakeling, University of York and Dr. Gabrielle Samuel, Kings College London.

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Chubb, J., Derrick, G.E. The impact a-gender: gendered orientations towards research Impact and its evaluation. Palgrave Commun 6 , 72 (2020). https://doi.org/10.1057/s41599-020-0438-z

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Research Article

Twenty years of gender equality research: A scoping review based on a new semantic indicator

Contributed equally to this work with: Paola Belingheri, Filippo Chiarello, Andrea Fronzetti Colladon, Paola Rovelli

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

Affiliation Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Engineering, University of Perugia, Perugia, Italy, Department of Management, Kozminski University, Warsaw, Poland

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

Affiliation Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

• Paola Belingheri, 
• Filippo Chiarello, 
• Andrea Fronzetti Colladon, 
• Paola Rovelli

• Published: September 21, 2021
• https://doi.org/10.1371/journal.pone.0256474
• Reader Comments

9 Nov 2021: The PLOS ONE Staff (2021) Correction: Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLOS ONE 16(11): e0259930. https://doi.org/10.1371/journal.pone.0259930 View correction

Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Citation: Belingheri P, Chiarello F, Fronzetti Colladon A, Rovelli P (2021) Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLoS ONE 16(9): e0256474. https://doi.org/10.1371/journal.pone.0256474

Editor: Elisa Ughetto, Politecnico di Torino, ITALY

Received: June 25, 2021; Accepted: August 6, 2021; Published: September 21, 2021

Copyright: © 2021 Belingheri et al. 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 within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Funding: P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

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

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

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https://doi.org/10.1371/journal.pone.0256474.t001

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

https://doi.org/10.1371/journal.pone.0256474.t002

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

https://doi.org/10.1371/journal.pone.0256474.g001

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

https://doi.org/10.1371/journal.pone.0256474.g002

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

https://doi.org/10.1371/journal.pone.0256474.g003

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0256474.g004

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

https://doi.org/10.1371/journal.pone.0256474.t003

Compensation.

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making.

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression.

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance.

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization.

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital.

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

S1 text. keywords used for paper selection..

https://doi.org/10.1371/journal.pone.0256474.s001

Acknowledgments

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

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Gender Discrimination

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• Kailing Shen 2  

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This chapter provides a bird’s eye view of the literature on gender discrimination. The presentation of studies is grouped into five parts. Part 1 presents evidence of gender discrimination measured via various dimensions in various countries and contexts. Part 2 discusses in detail the gender wage gap – one of the most important measures of gender discrimination – as well as gender segregation and its origins. Part 3 discusses the close relationship between female empowerment and violence, and the experience of women of color. Part 4 covers gender behavioral differences. Part 5 presents studies on the experience of women trying to break the glass ceiling, as well as the differential effects of education on boys and girls.

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Acknowledgments

Responsible section editor: Klaus F. Zimmermann.

The article has benefited from the valuable comments of the editor, and Peter Kuhn and Jacquelyn Zhang. No financial support is received for this work. There is no conflict of interest.

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Shen, K. (2022). Gender Discrimination. In: Zimmermann, K.F. (eds) Handbook of Labor, Human Resources and Population Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-57365-6_304-1

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Gender Discrimination

• Kailing Shen
• Published in Encyclopedia of the UN… 2021

32 Citations

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Perceived discrimination, satisfaction with life and radicalization: gender differences, “the parent trap”: gender stereotypes and parenting roles in an australian parenting website, foreign experience in ensuring gender equality: social and legal research, diving in the minds of recruiters: what triggers gender stereotypes in hiring, the labyrinth metaphor obstacles for women’s advancement to high-managerial and executive positions, 102 references, gender discrimination in the british labour market: a reassessment, gender similarities and differences., is there sex discrimination in the legal profession further evidence on tangible and intangible margins., the reproduction of gender inequality in muslim societies: a case study of iran in the 1980s, understanding gender differences in leadership, when the shadow is the substance: judge gender and the outcomes of workplace sex discrimination cases, racial ethnic women's labor: the intersection of race, gender and class oppression, sex discrimination and occupational segregation in the australian labour market, on the origins of gender roles: women and the plough.

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Gender Discrimination in Job Ads: Evidence from China*

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Half of Latinas say the situation of Hispanic women in the U.S. is better now than it was 10 years ago, and a similar share say the situation will improve in the next 10 years. Their mixed assessments reflect gains in education and at work over the last two decades, but also stalled progress in closing wage gaps with other groups.

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Voters who support Biden and Trump have starkly different opinions on many issues, and these two groups are divided internally as well.

Government data shows gains in education, employment and earnings for Hispanic women, but gaps with other groups remain.

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Women made up 47% of the U.S. civilian labor force in 2023, up from 30% in 1950 – but growth has stagnated.

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Supreme Court should rule bans on gender-affirming care for trans people unconstitutional

Over the last few years, the tennessee general assembly has made national headlines for targeting lgbtq+ rights on athletics participation, bathroom use and the community’s inclusion in curriculum..

• David Plazas is the director of opinion and engagement for the USA TODAY Network Tennessee.

A Tennessee state law could determine the future of gender affirming care nationally now that the U.S. Supreme Court has agreed to take up a case over a constitutional battle concerning transgender people's rights.

Since 2022, the number of states banning gender-affirming care for minors has skyrocketed from four to 25 , and the justices will be asked whether this is about a state's right to regulate health care access or whether these bans violate the civil rights of transgender people "on the basis of sex."

Witnessing the evolution of Tennessee's law, I believe these laws came about in response to anti-trans fervor fueled by far-right politicians who saw limiting trans people’s rights as a winning issue for their base.

If the Supreme Court is true to precedent, justices must side with the vast majority of district court judges who have decided that the bans are blatantly unconstitutional and at least in one ruling "based on bigotry."

Tennessee's attorney general wants to win the fight at the Supreme Court

However, Tennessee Attorney General Jonathan Skrmetti clearly disagrees.

The lawsuit bears his name − L.W. v. Skrmetti −and he said he plans on “finishing up the fight” over whether state bans on gender-affirming care for minors are constitutional.

• Are Tennessee’s ban and others like it across the country about a state’s interest in protecting transgender minors from “irreversible” medical treatments?
• Or do these prohibitions trample on transgender people’s civil rights and freedom to self-determination, and parental rights to access medical care for their children who live with gender dysphoria?

Skrmetti’s position clearly falls in the first camp. After all, it is his role is to defend the laws of the state of Tennessee, in this case, the Prohibition on Medical Procedures Performed on Minors Related to Sexual Identity Act of 2023.

However, multiple federal district judges have ruled against or agreed to halt enforcement of laws in different states because they raise questions over whether lawmakers infringed upon the constitutional rights of transgender minors and their parents.

Court of Appeals punted on the constitutional issue

On Monday, Skrmetti wrote in a public statement:

"We fought hard to defend Tennessee's law protecting kids from irreversible gender treatments and secured a thoughtful and well-reasoned opinion from the Sixth Circuit. I look forward to finishing the fight in the United States Supreme Court. This case will bring much-needed clarity to whether the Constitution contains special protections for gender identity.”

Except that the U.S. Sixth Circuit Court of Appeals’ 2-1 majority did not really answer the key question and they presumed the plaintiffs would lose.

Chief Judge Jeffrey S. Sutton and Judge Amul R. Thapar reversed a lower court injunction on enforcing Tennessee and Kentucky’s bans and allowed the case to proceed in the legal system.

They acknowledged the existence of gender dysphoria, but they said that the relative newness of certain treatments, including puberty blockers, made it difficult to determine the long-term consequences of the treatment.

“Prohibiting citizens and legislatures from offering their perspectives on high-stakes medical policies, in which compassion for the child points in both directions, is not something life-tenured federal judges should do without a clear warrant in the Constitution,” they wrote.

In other words, they punted on the constitutional question.

In her dissent, however, Judge Helene N. White did not mince words:

“Tennessee’s and Kentucky’s laws tell minors and their parents that the minors cannot undergo medical care because of the accidents of their births and their failure to conform to how society believes boys and girls should look and live. The laws further deprive the parents — those whom we otherwise recognize as best suited to further their minor children’s interests — of their right to make medical decisions affecting their children in conjunction with their children and medical practitioners. For these reasons, I dissent.”

Dahron Johnson, Nashville co-chair of the Tennessee Equality Project , said in a statement about the high court taking up the case that Tennessee "has abused its power in a brazen overreach seeking to gain access to the medical records of transgender and gender-diverse Tennesseans."

"As the Supreme Court takes up (the case), we trust that the Court will recognize the ways Tennessee, in banning such care, has sought to undermine that trust and communication, blocking access to life-saving health services for our state’s gender-diverse children," she added.

Federal judge calls out state bans as 'based on bigotry'

In June, a federal judge blocked Florida’s ban on gender affirming care for minors, ruling it unconstitutional

However, Judge Robert Hinkle went further in his ruling and called the law out as legislation “based on bigotry.”

“This is a politically fraught area. There has long been, and still is, substantial bigotry directed at transgender individuals,” Hinkle wrote. “Common experience confirms this, as do some of the comments of legislators recounted above. And even when not based on bigotry, there are those who incorrectly but sincerely believe that gender identity is not real but instead just a choice. This is, as noted above, the elephant in the room.”

Prior to Tennessee’s enactment of its ban, state and federal lawmakers embraced a 2022 claim from The Daily Wire right-wing outlet claiming Vanderbilt University Medical Center was “butchering, mutilating and sterilizing” children – something that still has yet to be proven.

But Republican politicians, including U.S. Sen. Marsha Blackburn, held a Rally to End Genital Mutilation in front of the state Capitol just weeks before the start of the legislative session.

In a 2023 guest opinion , trans activist Jace Wilder offered three reasons why the state should not ban care.

"How is it that a ban, that only last year was seen as  too extreme in this state by its leaders , is being pushed through now? The factor that may come to mind is what we keep hearing: 'It's to protect the kids from mutilation.' This isn’t the case," he said.

State lawmakers also wrote guest essays in The Tennessean explaining why they were introducing the ban on gender-affirming care for minors.

“Cultural forces from the left would like us to accept an alarming new myth; that gender is not a biological reality,” wrote House Majority Leader William Lamberth in one column 2022 shortly before the rally. Senate Majority Leader Jack Johnson wrote a defense of the bill in early 2023 during the session. They co-wrote an essay in August 2023 defending the law .

Civil Rights Act should extend to all minors' access to health care

Over the last several years, the Tennessee General Assembly has made national headlines for targeting LGBTQ+ rights in athletics participation, bathroom use and the community’s inclusion in curriculum students learn.

The Supreme Court ruled in the 2020 Bostock v. Clayton County decision that employment discrimination against people based on gender identity was unconstitutional under the Civil Rights Act. Hopefully, they will use similar logic to protect the rights of transgender children and their parents to access medical care.

There is political gain in enacting these bans, but it doesn’t mean lawmakers are right.

David Plazas is the director of opinion and engagement for the USA TODAY Network Tennessee. He is an editorial board member of The Tennessean. He hosts the  Tennessee Voices videocast  and curates the  Tennessee Voices  and  Latino Tennessee Voices  newsletters. Call him at (615) 259-8063, email him at  [email protected]  or tweet to him at  @davidplazas .