Progress in women’s representation in top leadership weakens people’s disturbance with gender inequality in other domains
Perceiving greater women’s representation in organizations’ top leadership leads people to overgeneralize women's access to equal opportunities, which in turn predicts lower concern with ongoing gender inequality in other domains.
It is commonly believed that achieving progress in women’s representation in top leadership levels is crucial for advancing gender equality generally, because it will produce better outcomes for women in other domains as well (e.g., the pay gap). To wit, Facebook COO Sheryl Sandberg writes in her 2013 book, Lean In, that “conditions for all women will improve when there are more women in leadership roles giving strong and powerful voice to their needs and concerns” (Sandberg, 2013, p. 8). Increasing the proportion of women at the top of organizations has thus become a priority for many companies and countries, with some instituting minimum quotas and mentorship programs to increase the representation of female leaders. Concomitantly, substantial progress has been seen on this front, with the number of female CEOs in Fortune 500 companies increasing from near-zero in 1995 to 24 in 2015. Similarly, in Europe, women’s representation on boards has risen from 11% in 2007 to 23% in 2016.
However, gender disparities remain. For example, in Iceland, where women occupy an exceptional 44% of board seats, there is still a 14% gender pay gap – a gap on par with that of most other Western countries. Rather than being a linear process across domains of inequality, this example suggests that progress is in fact a fragmented process, whereby substantive advances in some domains (e.g., top leadership representation) coexist with persisting inequality in others (e.g., pay). The authors thus investigated how perceiving progress for women in the domain of top leadership representation shapes people’s concern with persisting gender inequality in other domains, such as the gender wage gap.
To do so, the authors built on theories of exemplar-based information processing, which propose that a salient exemplar of success in a given group can shape people’s perceptions of the entire group to which this person belongs. Extending these theories to perceptions of social progress for stigmatized groups, the authors theorized that perceiving substantive representation for a stigmatized group (i.e., a mass of individuals beyond token representation) in a domain traditionally dominated by a majority group would lead people to overgeneralize the extent to which the entire stigmatized group has access to equal opportunities.
The authors predicted that in turn, this overgeneralization would predict decreased concern about the persisting inequalities faced by the stigmatized group in other domains (e.g., pay gaps).
Using samples from Amazon’s Mechanical Turk, as well as a sample approximately representative of the US population, the authors tested these predictions in the context of the substantive progress that has recently occurred for women’s representation at the top of organizations.
Perceiving greater female representation in organizations’ top leadership levels (i.e., progress for women in the domain of top leadership representation) leads people to overgeneralize women's access to equal opportunities, which in turn predicts decreased concern about gender inequality in other domains (such as the gender pay gap).
- Perceiving high levels of female representation in organizations’ top levels increases people’s perceptions that women now have access to equal opportunities.
- For example, in Study 3, the authors found a mean of 2.54 compared to a mean of 2.24 on a Likert scale from 1 to 5 that measured perceptions of women’s access to equal opportunities among participants randomly assigned to read an article describing women’s representation level in top leadership as high versus low (“high” versus “low representation” condition).
- In turn, people’s overgeneralization of women’s access to equal opportunities predicted lower concern about persisting gender inequality in other domains, whether at work – e.g., the gender wage gap, or access to venture capital in entrepreneurship, – or beyond – e.g., housework distribution, purchasing power, entertainment, and sports.
- A mini metanalysis of the experiments found that the mean effect across Studies 1, 3 and 4, was significant (Md = 0.22, 95% CI [0.09, 0.34], p< .001), in that compared to participants randomly assigned to the low representation condition, participants in the high representation condition reported significantly lower concern about persisting gender inequality in other domains, both at work and beyond.
Celebrating progress in women’s representation in organizations’ top leadership is of course paramount, given it has been shown to narrow the gender gap in girls’ aspirations and advancement in education. However, this article’s findings provide the caveat that highlighting progress in this domain may paradoxically decrease people’s concern about ongoing gender inequality in other domains. These findings are worrisome, given that concern with social inequality predicts collective will to address it. Future research should therefore explore whether there are effective ways to broadcast messages about gender progress in the domain of top leadership representation without jeopardizing progress for women in other domains of inequality.
Through a series of 2 correlational studies and 3 experiments pre-registered on the Open Science Framework, the authors investigated how perceiving progress for women in the domain of top leadership representation may impact people’s concern about persisting gender inequality in other domains (e.g., pay gap, housework distribution). The researchers chose to measure participants’ level of disturbance with persisting gender inequalities, because disturbance with social inequality predicts people’s willingness to address it.
In Studies 1, 2a, 3, and 4, participants were recruited from Amazon’s Mechanical Turk platform (Ns = 331, 350, 454, and 326 participants, respectively). They were all American, working either full or part time, and had earned at least an average 95% approval rating on the platform – thus ensuring high levels of data quality. In contrast, Study 2b reanalyzed data collected through Survey Sampling International for another article, and provided a sample of 1,098 participants who were roughly representative of the United States population, based on Census data.
In Study 1, participants were randomly assigned to read that women’s representation at the top of US organizations was either high or low (“high” versus “low representation” condition). Then, they were asked to indicate their level of disturbance with 6 factual statistics about the gender wage gap in the U.S., as well as 6 factual statistics about wealth inequality in general in the U.S. Participants indicated their responses using a Likert scale ranging from 1 (not at all disturbed) to 7 (extremely disturbed).
Study 2a and 2b had a correlational design. Participants were asked to provide their best estimate of the percentage of women in top leadership in the U.S., and were then asked to indicate their level of disturbance with the 6 factual statistics about the gender pay gap used in Study 1.
Study 3 introduced a control condition to test the directionality of the effect, and thus randomly assigned participants to one of three experimental conditions: participants read an article describing women’s representation at top levels in US organizations as either high, low, or unknown (a “control” condition). Participants then reported their disturbance with the gender pay gap using the measure used in Study 1.
Study 4 tested whether the findings of the previous studies would generalize to domains of gender inequality beyond the gender pay gap: entrepreneurship, purchasing power, housework distribution, entertainment, and sports. Participants were randomly assigned to the high or low condition, and were asked to indicate their degree of disturbance with 6 factual statistics, each describing the current state of gender inequality in each of the 6 domains listed above. Participants completed this measure using a Likert scale ranging from 1 (not at all disturbed) to 7 (extremely disturbed).