Sex, Gender and Leadership

Sex Versus Gender: Essential Distinctions

Before examining evidence, we must distinguish sex from gender, two concepts often conflated in popular discussion but meaningfully different in scientific analysis. Sex refers to biological categories based on reproductive anatomy and physiology. In most species including humans, sex is binary at the genetic level (XX or XY chromosomes, with rare exceptions) and bimodal in phenotypic expression. Gender refers to social and cultural categories, roles, expectations, and identities related to but not determined by biological sex -- encompassing societal expectations about how men and women should behave, cultural norms around masculinity and femininity, occupational roles traditionally associated with each sex, and individual gender identity.

This distinction matters because sex and gender interact in complex ways. Some behavioural differences between men and women trace to biological sex differences operating through hormones, brain structure, or physical characteristics. Other differences trace to gender -- cultural expectations, differential socialisation, structural barriers, and stereotype effects. Most real-world differences reflect both operating simultaneously through gene-culture coevolution.

Consider risk-taking. There's evidence that testosterone influences risk tolerance through neural mechanisms. There's also evidence that cultural gender roles affect risk-taking by making it more acceptable for men than women to take certain risks. These aren't competing explanations but complementary ones. Both operate simultaneously. Testosterone differences partly reflect genetic sex differences, but testosterone levels themselves are influenced by social experiences. The gene-culture coevolution perspective suggests that debates pitting 'biology' against 'culture' as explanations for sex differences miss the point. The real questions are: what biological differences exist on average? What cultural processes amplify, reduce, or transform those differences? How do biology and culture interact across development? And most importantly for leadership: how should organisations respond to whatever patterns exist?

The Evidence on Sex Differences in Leadership: What Meta-Analysis Actually Shows

Popular discussion of sex differences in leadership often involves either denial that any differences exist or exaggerated claims about fundamental male-female distinctions. The actual scientific evidence, synthesised through meta-analysis combining results across hundreds of studies, tells a more nuanced story.

Meta-analysis provides statistical synthesis of research literatures, calculating average effect sizes across studies and accounting for sampling error and methodological variation. Effect sizes indicate the magnitude of differences using Cohen's d, where d = 0.2 represents a small effect, d = 0.5 a medium effect, and d = 0.8 a large effect. Meta-analysis also reveals the extent of overlap between distributions, showing that even when group differences are statistically reliable, within-group variation typically dwarfs between-group differences.

Eagly and Johnson (1990) conducted the first major meta-analysis of sex differences in leadership styles, examining both laboratory studies and organisational research. They found minimal differences overall. When differences emerged, they were small and context-dependent. Female leaders averaged slightly more democratic and participative styles compared to male leaders' slightly more autocratic and directive styles, but the effect size was small (d approximately 0.2). Notably, these differences were smaller in organisational settings than in laboratory studies -- in actual organisations where leaders operated in real roles with genuine authority, sex differences diminished, suggesting that organisational roles constrain behaviour more than sex shapes it.

Eagly, Johannesen-Schmidt, and van Engen (2003) updated this analysis examining transformational versus transactional leadership. The meta-analysis found a small female advantage in transformational leadership (d approximately 0.1) and a small male advantage in transactional leadership (d approximately 0.15). These effects are statistically reliable across studies but substantively small -- the distributions overlap massively.

Most importantly, Eagly, Karau, and Makhijani (1995) examined leadership effectiveness, asking whether male or female leaders produce better outcomes. The meta-analysis found no overall difference: male and female leaders showed equivalent effectiveness. However, context mattered enormously. Female leaders were rated as less effective in roles that were male-dominated or required stereotypically masculine styles. Male leaders were rated as less effective in roles requiring stereotypically feminine styles. This pattern suggests that effectiveness depends on match between leadership style and context rather than sex per se.

The critical insight from meta-analysis is that effect sizes are small. Even the largest meta-analytic sex differences in leadership-relevant traits rarely exceed d = 0.3, considered small to medium. This means that distributions overlap enormously. Knowing someone's sex tells you very little about their actual leadership style or effectiveness. Within-sex variation massively exceeds between-sex differences. Using sex as a proxy for leadership style or capability is unjustified by evidence -- even if average differences exist, they're too small to predict individual characteristics reliably.

Why Differences Exist: Evolutionary and Social Role Perspectives

When sex differences in leadership or personality do appear, explaining them requires theory. Two major frameworks compete: evolutionary psychology emphasising sexual selection and biological influences, and social role theory emphasising culturally constructed gender roles and differential socialisation. The empirical debate between these perspectives is ongoing and probably misframed as either-or rather than both-and.

The evolutionary perspective argues that sexual selection created psychological sex differences in domains where males and females faced consistently different adaptive problems across evolutionary time. Sexual selection operates through intrasexual competition within sexes for mates, and intersexual choice between sexes of mates. For mammals including humans, sexual selection typically operates more intensely on males than females because female reproductive capacity is more limited. This asymmetry created stronger selection on males for traits enhancing competitive success: physical size and strength, risk-taking enabling status competition, aggression toward male rivals, and coalition formation for group conflicts. Females faced selection for different traits: mate choice evaluating male quality, provisioning and protecting offspring, forming social alliances, and managing social relationships enabling cooperative childcare.

Critically, evolutionary psychology predicts average differences, not universal ones, and expects substantial overlap. Evolution doesn't predict that all men are more competitive than all women, only that on average, across populations, male competitive orientation will exceed female competitive orientation somewhat. The theory predicts exactly what we observe: small average differences with massive overlap.

Social role theory, developed by Eagly and Wood (1999), offers a different explanation. It argues that sex differences in behaviour and personality arise from occupying different social roles rather than from biological differences. Throughout human history and across most contemporary societies, men and women have occupied systematically different roles: men more often in public, economic, and political domains requiring status competition and resource provision; women more often in domestic, caregiving, and relationship maintenance roles. Social role theory proposes that occupying these roles for generations shaped psychology through socialisation and learning. Boys learn to be competitive, assertive, and status-seeking because those traits are rewarded and expected in male roles. Girls learn to be communal, nurturing, and relationship-focused because those traits are rewarded and expected in female roles.

Evidence exists for both perspectives. Schmitt et al. (2008) examined personality sex differences across fifty-five nations and found that sex differences in personality were actually larger in more gender-egalitarian societies than in less egalitarian societies -- a pattern that contradicts simple social role theory predictions. One interpretation is that when environmental and social constraints are removed, biological predispositions can express more freely. Social role theory, set out by Wood and Eagly (2002), reads cross-cultural differences instead as products of each society's division of labour, so the meaning of the pattern is still disputed. The debate continues.

Henrich (2016) and others propose that gene-culture coevolution resolves the false dichotomy. Both biological and cultural factors matter. Sexual selection shaped psychological predispositions creating modest average sex differences in specific domains. Cultural evolution then operated on these biological substrates, sometimes amplifying differences through strongly differentiated gender roles, sometimes reducing them through egalitarian cultural evolution. This framework predicts cross-cultural universality in some sex differences combined with substantial cross-cultural variation in magnitude and expression -- exactly what we observe.

Context Matters: War, Peace, and Situation-Dependent Leadership Preferences

One of the most striking findings in recent evolutionary psychology research is that leadership preferences shift dramatically across contexts in ways that map onto plausible ancestral selection pressures. The same individuals who prefer one type of leader in peacetime prefer a very different type during conflict or crisis.

Little, Burriss, Jones, and Roberts (2007) examined facial preferences in wartime versus peacetime contexts. They showed participants faces varying in masculinity -- features correlating with testosterone exposure during development -- and asked them to rate how much they'd prefer this person as a leader. Half the participants first read about intergroup conflict scenarios; the other half read about cooperative scenarios. Participants who'd thought about conflict showed much stronger preferences for masculine-faced leaders compared to those who'd thought about cooperation. Simply priming thoughts about threat versus cooperation shifted leadership preferences substantially toward or away from masculine phenotypes.

Spisak, Dekker, Kruger, and Van Vugt (2012) replicated and extended these findings. They found that masculine facial features signal dominance and physical formidability -- traits presumably useful in intergroup conflicts -- while feminine facial features signal trustworthiness and cooperativeness, traits useful in managing internal coordination. People's leadership preferences track these functional associations, shifting toward masculine traits when external threats are salient and toward feminine traits when cooperation challenges dominate.

Van Vugt and Spisak (2008) demonstrated that the pattern extends beyond faces to leadership styles. They presented participants with scenarios involving either external threats requiring group defence or internal coordination requiring cooperation. Participants facing external threats strongly preferred masculine-described leaders; those facing internal coordination challenges preferred feminine-described leaders. From an evolutionary perspective, this flexibility makes sense: different challenges required different leadership, and groups that matched leadership style to context would have outcompeted those with rigid preferences.

The implications for understanding sex differences in leadership are profound. If leadership preferences shift based on context, and if men on average display more stereotypically masculine traits while women on average display more stereotypically feminine traits, then we'd predict that men will be preferred for leadership in contexts emphasising competition, conflict, risk, and dominance, while women will be preferred in contexts emphasising cooperation, coordination, relationship management, and consensus. These preferences operate even when the sex difference in actual leadership capability is minimal or non-existent, because people are responding to perceived rather than actual differences.

This creates a perverse dynamic in highly competitive organisational contexts like Patricia's venture capital firm: decision-makers disproportionately prefer masculine leadership styles and, by association, male leaders -- not because men actually lead better in these contexts but because masculine styles feel appropriate and men are assumed to embody those styles. The preference becomes self-fulfilling: when organisations consistently select masculine-presenting leaders for competitive contexts, women learn that succeeding requires adopting masculine styles, but women who adopt masculine leadership styles face backlash because the behaviour violates gender role expectations.

This double bind is well-documented. Heilman (2001) and others have shown that women in leadership face contradictory pressures: lead in stereotypically feminine ways and be seen as too soft for tough contexts; lead in stereotypically masculine ways and be penalised for violating gender expectations. Men face no comparable contradiction because masculine leadership styles align with both leadership role expectations and male gender role expectations. Making contextual demands explicit rather than implicit might shift biased preferences -- asking 'what does this role actually require day-to-day?' rather than 'what does leading this firm feel like it requires?' could reveal that many roles reward precision and collaboration as much as boldness.

Coalitional Psychology and Sex: How Men and Women Form Groups Differently

Beyond individual leadership traits, sex differences appear in how people form and maintain coalitions. Benenson (2013) reviewed evidence on how girls and women form alliances and compete with one another. A study of how people present their social networks online found that men tended to display larger, all-male groups, while women tended to display one-to-one relationships (David-Barrett et al., 2015). Men also appear to respond more strongly to intergroup competition (Van Vugt, De Cremer, & Janssen, 2007).

These patterns make evolutionary sense given different adaptive challenges. Male reproductive success ancestrally depended heavily on status within hierarchies and success in intergroup competition -- forming large coalitions capable of warfare or territory defence enhanced fitness, and tolerating internal status competition within coalitions was acceptable as long as the coalition succeeded externally. Female reproductive success depended more on securing resources for offspring and building support networks for cooperative childcare -- smaller, close-knit coalitions of reliable allies served these functions better than large, competitive hierarchies.

Campbell (2004) examined female intrasexual competition, documenting that women compete intensely for mates and status but employ different strategies than men. Rather than overt physical aggression or public status contests, female competition operates through reputational damage, social exclusion, coalition manipulation, and indirect aggression. This makes female competition less visible but not less intense than male competition.

The coalition differences create systematic patterns in organisations. All-male groups tend to establish hierarchies quickly, tolerate substantial internal competition, and focus intensely on competing with external groups. All-female groups tend to resist hierarchy more strongly, punish internal competition more harshly, and prioritise relationship maintenance over external competition. Mixed-sex groups show intermediate patterns and additional complexity from gender dynamics. Van Vugt, De Cremer, and Janssen (2007) found that male groups show much higher willingness to engage in collective aggression against out-groups, while female coalitions facing similar threats show more caution and greater reluctance to engage in direct confrontation.

These differences don't mean women can't compete effectively or men can't cooperate internally -- the differences are average tendencies with massive individual variation. But they help explain certain puzzling organisational patterns: why predominantly male organisations sometimes develop extreme internal competition despite needing collaboration (male coalitional psychology tolerates substantial internal status competition as long as the coalition succeeds externally); and why predominantly female organisations sometimes struggle with gossip and exclusion (female coalitional psychology punishes internal competition through reputational damage rather than overt confrontation).

Risk-Taking Revisited: When Sex Differences Are Large and When They Disappear

Byrnes, Miller, and Schafer (1999) conducted meta-analysis of sex differences in risk-taking across diverse domains. The overall effect size was moderate (d approximately 0.3-0.4), indicating that men average higher risk-taking than women. However, the effect varied enormously across risk types. For physical risks (extreme sports, dangerous driving, physical challenges), sex differences were substantial (d approximately 0.5-0.8). For intellectual risks (challenging conventional wisdom, making controversial arguments), differences were minimal. For social risks (risking embarrassment or rejection), differences were negligible or sometimes reversed.

Eckel and Grossman (2008) examined sex differences in economic risk-taking through laboratory experiments. They found moderate sex differences in gambling and investment tasks, with men accepting higher-variance gambles and women preferring safer returns. But critically, when risks involved possible losses, differences disappeared or reversed --women became more willing to gamble to avoid certain losses. These patterns suggest that the sex difference in risk-taking reflects multiple psychological mechanisms, not a single 'risk tolerance' trait.

The contextual variation suggests that organisational risk cultures shape how sex differences manifest. In organisations that define risk narrowly as physical or competitive challenges, sex differences in 'risk-taking' appear large because that particular type of risk shows large sex differences. In organisations that recognise diverse risk types including social and reputational risks, sex differences appear smaller because those domains show smaller differences. Patricia's venture capital committee likely conflated several risk types: they perceived Amanda as 'risk-averse' partly because she acknowledged uncertainty and carefully evaluated evidence before deciding, when this actually reflected appropriate epistemic risk management. Michael's apparent 'risk tolerance' reflected overconfidence rather than high tolerance for thoughtfully chosen risks.

Understanding that 'risk-taking' encompasses multiple psychologically distinct phenomena, some showing large sex differences and others showing minimal differences, helps avoid mistaking one type of risk-handling for overall risk orientation. Leaders need appropriate risk-taking -- accepting worthwhile risks while avoiding foolish ones -- and evidence suggests that men and women can both achieve this, though they may approach it somewhat differently on average across specific domains.

Critical Examination: The Essentialist Traps and How to Avoid Them

Research on sex differences in leadership is perhaps the most fraught terrain in organisational psychology because the potential for misapplication and harm is enormous. Even carefully qualified scientific findings about small average differences get distorted into justifications for discrimination, stereotyping, and limitation of opportunity.

The first and most fundamental trap is confusing distributions with dichotomies. When we say 'men average higher in risk-taking,' we're describing a difference between overlapping distributions, not separate categories. Yet people intuitively treat categories as if they were dichotomies: 'men are more risk-tolerant' gets mentally translated into 'men are risk-tolerant, women are risk-averse,' which is simply false. Fighting this cognitive bias requires constant vigilance -- every statement about group differences must be qualified with 'on average' and 'with massive overlap,' and every application to individuals must be resisted.

The second trap is ignoring context in ways that attribute to biology what actually reflects culture. Stereotype threat provides a powerful example. Steele and Aronson (1995) demonstrated that merely making group identity salient before a test can impair performance of stereotyped groups. Spencer, Steele, and Quinn (1999) showed this for women's mathematics performance specifically: in the stereotype threat condition, a significant sex difference emerged favouring men; in the reduced threat condition, the sex difference disappeared entirely. The 'sex difference' was actually a stereotype threat effect, not a biological difference in ability. Many observed sex differences in organisational contexts may reflect stereotype threat, gender role expectations, or structural barriers rather than biological differences in capability.

The third trap is conflating descriptive and prescriptive claims. Describing average sex differences tells us what is, not what ought to be. Even if men and women differ on average in some leadership-relevant trait, this doesn't imply that organisations should prefer one sex for leadership roles (the overlap between distributions means both sexes contain plenty of individuals with any desired trait profile), that individuals should conform to sex-typical patterns (within-sex variation means deviation from average isn't abnormal), or that current sex distributions in leadership reflect optimal or natural patterns (structural barriers, bias, and discrimination explain far more of the sex gap in leadership than any biological differences).

The fourth trap is biological determinism -- treating average sex differences as immutable facts of nature rather than malleable outcomes of gene-culture-environment interaction. Even highly heritable traits show substantial environmental sensitivity. A woman in a highly gender-egalitarian culture might show leadership traits very different from a woman in a highly traditional culture, despite identical biology. The fifth trap involves ignoring intersectionality: sex interacts with culture, race, class, nationality, and other social categories in complex ways. A Black woman's experience of leadership differs from a white woman's in ways that cannot be reduced to either race or sex separately. The sixth trap is using evolutionary or biological explanations to justify existing inequalities -- the naturalistic fallacy has been thoroughly debunked but remains intuitively compelling. The fact that some sex difference might have evolutionary origins doesn't make it morally justified, immutable, or relevant to individual assessment.

The appropriate stance combines intellectual honesty about what evidence shows with ethical commitment to using knowledge to reduce rather than reinforce discrimination. This means acknowledging that small average sex differences in some leadership-relevant traits probably exist with both biological and cultural contributions, while recognising that within-sex variation massively exceeds between-sex differences; understanding that even genuine average differences don't justify discrimination because distributions overlap enormously; recognising that much of what appears to be sex differences in leadership actually reflects bias in evaluation, stereotype threat effects, structural barriers, and differential treatment; and remaining vigilant against both denial of any sex differences and exaggeration of sex differences.

Moving Toward Responsible Application

How should leaders and organisations use knowledge about sex differences in leadership responsibly? Several principles emerge from the evidence and ethical analysis.

Evaluate individuals, not categories. Never assume that someone will show particular traits because of their sex -- within-sex variation is so large that sex provides minimal information about individual characteristics. Design selection and evaluation systems that assess individuals directly rather than relying on demographic proxies. Recognise that seemingly neutral evaluation can embody bias: audit evaluation criteria to ensure they're genuinely relevant to role demands rather than reflecting gendered stereotypes about what leadership should look like.

Make role demands explicit and specific. Vague criteria like 'executive presence' or 'strategic vision' invite bias because they're interpreted through cultural stereotypes. Specific behavioural criteria like 'makes decisions with incomplete information while acknowledging uncertainty' or 'builds coalitions across organisational boundaries' are harder to bias because they describe observable behaviour rather than subjective impressions. Use structured processes that reduce bias -- structured interviews with standardised questions, multiple independent evaluators, and explicit criteria all reduce bias substantially compared to unstructured intuitive judgments.

Diversify decision-making groups. Homogeneous groups are more vulnerable to shared biases that go unchallenged -- Patricia was the only woman in the committee and had difficulty getting her observations taken seriously. Create accountability for equity outcomes: when decision-makers know their outcomes will be scrutinised for bias, they're more careful about their processes and judgments. Recognise that different leadership styles can be equally effective -- organisations that treat one style, often stereotypically masculine, as the gold standard while treating other approaches as deficient miss both talent and organisational diversity of thought.

Attend to structural barriers beyond individual assessment. Even perfectly unbiased evaluation won't create equity if structural factors systematically disadvantage one sex. Family leave policies, work schedule flexibility, sponsorship networks, informal mentorship, and organisational culture all affect who can succeed in leadership roles. Be alert to double binds and impossible standards: when women are penalised for being either 'too soft' or 'too aggressive' while men face no comparable contradiction, the system is structurally biased regardless of evaluators' intentions.

Two years after the Managing Partner selection, Patricia left TechVenture Capital to start her own fund. She designed her selection and evaluation processes explicitly to counteract the biases she'd witnessed: structured interviews with standardised questions, work samples demonstrating analytical capability, diverse evaluation committees, explicit and specific role demands, and tracking of outcomes by gender with scrutiny of disparities. Her fund's leadership team ended up being majority female -- not through preferences favouring women but through processes that evaluated capability without gender bias. Her fund ranked in the top quartile, demonstrating that different leadership styles could succeed in venture capital when given fair opportunity. The broader lesson is that knowledge about sex differences in leadership should inform efforts to reduce bias and create equitable opportunity, not justify existing disparities or limit individual potential.

Key takeaways

• Meta-analytic evidence shows small average sex differences in leadership styles (effect sizes typically d = 0.1-0.3) with massive distribution overlap, meaning within-sex variation enormously exceeds between-sex differences and sex provides minimal information about individual leadership characteristics.
• No consistent sex differences appear in leadership effectiveness overall --effectiveness depends on match between leadership style and organisational context rather than sex, with both stereotypically masculine and feminine styles proving effective in appropriate contexts.
• Both biological factors (sexual selection creating modest psychological predispositions) and cultural factors (gender role socialisation) contribute to observed sex differences through gene-culture coevolution, making nature versus nurture debates false dichotomies that miss how biology and culture interact.
• Leadership preferences shift contextually: people prefer masculine traits when primed with competition or conflict but feminine traits when primed with cooperation, creating bias when competitive contexts are assumed to require masculine styles despite actual role demands often favouring diverse approaches.
• Stereotype threat, gendered evaluation of identical behaviours, structural barriers, and double binds where women are penalised for being either too soft or too aggressive explain substantial portions of sex gaps in leadership beyond any biological capability differences.
• Responsible application requires evaluating individuals not categories, recognising bias in seemingly neutral processes, making role demands explicit and specific, using structured evaluation reducing bias, diversifying decision-makers, and attending to structural barriers beyond individual assessment.
• Knowledge about sex differences should inform efforts to reduce bias and create equitable opportunity rather than justify existing disparities -- small average differences with massive overlap operating in biased contexts demand sophisticated responses evaluating individuals fairly while addressing structural inequities.

Reflection questions

• Reflect on selection or promotion decisions you've participated in or witnessed. Can you identify instances where stereotypically masculine or feminine leadership styles were evaluated differently? Were certain traits valued more than equally relevant traits? How might making role demands more explicit have changed evaluations?
• Consider your own leadership style and how it aligns with or deviates from gender stereotypes. Have you experienced pressure to conform to gendered expectations? Have you been evaluated differently for behaviour that would be assessed differently in someone of another gender? How have you navigated these dynamics?
• Think about how your organisation defines and evaluates 'risk-taking' in leadership contexts. Does the definition emphasise physical or competitive risks where sex differences are larger, while neglecting social or reputational risks where differences are minimal? How might a broader conception of appropriate risk-taking affect who is recognised as having necessary leadership qualities?
• Examine your organisation's leadership pipeline and outcomes by sex. Are there disproportionate sex ratios at various leadership levels? If so, what explains the patterns -- biased evaluation, structural barriers, different attrition rates, differential access to development opportunities? What specific interventions might address identified causes?
• Consider situations where you've observed or made assumptions about someone's leadership capability based on their sex. What evidence were those assumptions based on? How often do you consciously check whether you're evaluating an individual's actual behaviour versus applying group stereotypes?
• Reflect on the distinction between descriptive and prescriptive claims about sex differences. Have you heard or made arguments that moved from 'men and women differ on average in X' to 'therefore, women shouldn't be in Y leadership roles'? How might you challenge that logical leap while still acknowledging whatever evidence exists for average differences?

References

1. Benenson, J. F. (2013). The development of human female competition: Allies and adversaries. Philosophical Transactions of the Royal Society B: Biological Sciences, 368(1631), 20130079.
2. Byrnes, J. P., Miller, D. C., & Schafer, W. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367–383.
3. Campbell, A. (2004). Female competition: Causes, constraints, content, and contexts. Journal of Sex Research, 41(1), 16–26.
4. David-Barrett, T., Rotkirch, A., Carney, J., Behncke Izquierdo, I., Krems, J. A., Townley, D., McDaniell, E., Byrne-Smith, A., & Dunbar, R. I. M. (2015). Women favour dyadic relationships, but men prefer clubs: Cross-cultural evidence from social networking. PLoS ONE, 10(3), e0118329.
5. Eagly, A. H., & Johnson, B. T. (1990). Gender and leadership style: A meta-analysis. Psychological Bulletin, 108(2), 233–256.
6. Eagly, A. H., & Wood, W. (1999). The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54(6), 408–423.
7. Eagly, A. H., Johannesen-Schmidt, M. C., & van Engen, M. L. (2003). Transformational, transactional, and laissez-faire leadership styles: A meta-analysis comparing women and men. Psychological Bulletin, 129(4), 569–591.
8. Eagly, A. H., Karau, S. J., & Makhijani, M. G. (1995). Gender and the effectiveness of leaders: A meta-analysis. Psychological Bulletin, 117(1), 125–145.
9. Eckel, C. C., & Grossman, P. J. (2008). Men, women and risk aversion: Experimental evidence. In C. R. Plott & V. L. Smith (Eds.), Handbook of experimental economics results (Vol. 1, pp. 1061–1073). Elsevier. https://doi.org/10.1016/S1574-0722(07)00113-8
10. Heilman, M. E. (2001). Description and prescription: How gender stereotypes prevent women's ascent up the organizational ladder. Journal of Social Issues, 57(4), 657–674.
11. Henrich, J. (2016). The secret of our success: How culture is driving human evolution, domesticating our species, and making us smarter. Princeton University Press.
12. Little, A. C., Burriss, R. P., Jones, B. C., & Roberts, S. C. (2007). Facial appearance affects voting decisions. Evolution and Human Behavior, 28(1), 18–27.
13. Schmitt, D. P., Realo, A., Voracek, M., & Allik, J. (2008). Why can't a man be more like a woman? Sex differences in Big Five personality traits across 55 cultures. Journal of Personality and Social Psychology, 94(1), 168–182.
14. Spencer, S. J., Steele, C. M., & Quinn, D. M. (1999). Stereotype threat and women's math performance. Journal of Experimental Social Psychology, 35(1), 4–28.
15. Spisak, B. R., Dekker, P. H., Krüger, M., & van Vugt, M. (2012). Warriors and peacekeepers: Testing a biosocial implicit leadership hypothesis of intergroup relations using masculine and feminine faces. PLoS ONE, 7(1), e30399.
16. Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797–811.
17. Van Vugt, M., & Spisak, B. R. (2008). Sex differences in the emergence of leadership during competitions within and between groups. Psychological Science, 19(9), 854–858.
18. Van Vugt, M., De Cremer, D., & Janssen, D. P. (2007). Gender differences in cooperation and competition: The male-warrior hypothesis. Psychological Science, 18(1), 19–23.
19. Wood, W., & Eagly, A. H. (2002). A cross-cultural analysis of the behavior of women and men: Implications for the origins of sex differences. Psychological Bulletin, 128(5), 699–727.