Women in Leadership in STEMM

This is the essential enduring purpose of Homeward Bound, its raison d’être, to:

  • To enable you to lead more effectively in the world
  • To give you the skills to progressively work more effectively together
  • To have a greater impact on our world both individually and together, to a healthier, more inclusive, more sustainable future in which women have a shared seat at the decision-making table

So what is the current state of play, what are the facts?

The following three sections are designed to inform and allow you to speak with confidence and authority on the current issues facing women who seek to lead in STEMM.

MOTHER NATURE NEEDS HER DAUGHTERS:

A HOMEWARD BOUND GLOBAL REVIEW AND FACT SHEET INVESTIGATING GENDER INEQUALITY IN STEMM

Collated from scientific literature, international and national reports, this is a fact sheet aimed encouraging women’s empowerment at work and in leadership.

This fact sheet was compiled as a project of a number of women from the HB2 (2018) and HB3 (2019) cohorts, as a source document and overview of important research in this area. Click the button to download the document, or read on below.

 

What are the biases for women entering, already in, or staying in STEMM?
Key issues include: stereotypes around science and gender and biology, beliefs around intelligence, self- assessment, beliefs about spatial skills, school and University environments and processes and implicit and workplace biases.
What prevents women from entering STEM? Biology is not destiny
  • A review of 400+ articles exploring the causes of women’s under- representation in STEM concluded that research on sex differences in brain structure and hormones is inconclusive. Female and male brains are physically distinct, but how these differences translate into specific cognitive strengths and weaknesses remains unclear.1
  • Sociocultural factors and environmental factors are more likely explanation for gender gaps. For example, fewer girls think they are good at math, but in the past few decades the gender gap has narrowed, and today girls are doing as well as boys in math on average.2
  • Gender differences in self-confidence in STEM subjects begin in middle school and increase in high school and college, with girls reporting less confidence than boys in their math and science ability.3
  • Boys may develop greater confidence in STEM through experience developing relevant skills. A number of studies have shown that gender differences in self-confidence disappear when variables such as previous achievement or opportunity to learn are controlled4
  • Although boys still outperform girls at the highest achieving end of mathematics, the relative proportion of girls doing well on tests of advanced mathematical ability has increased exponentially over the last 30 years showing much of the difference was environmental and societal: 13:1 in 1983 to around 3:1 in 2007.5
  • Research shows that girls in a single-sex school are often more competitive with their peers in their desire to achieve. The environment of a single-sex school, especially for girls, may promote opportunities for students to overcome gender biases that occur through social learning. Girls approach their studies during the compulsory years more positively in a single-sex school and will enthusiastically attempt the areas of maths, science and technology at the senior levels, where female representation is generally lower in co-educational schools.6
  • In some fields such as biology, women and men are now equally represented in training at undergraduate, graduate and postgraduate levels. However, women disproportionately leave these disciplines at each career stage following training.7
It could be that women are just not interested... but societal constructs play a major role in what women are interested in
  • Interest in an occupation is influenced by many factors, including a belief that one can succeed in that occupation8 and culturally prescribed gender roles may influence occupational interest.9
  • Girls assess their mathematical ability as lower than boys with equivalent past mathematical achievement. Girls hold themselves to a higher standard in subjects like math, where boys are considered to excel. Because of this, girls are less likely to believe that they will succeed in a STEM field and, therefore, less likely to express interest in a STEM career.
  • There are well-documented gender differences in the value that women and men place on doing work that contributes to society. Women are more likely than men to prefer work with a clear social purpose.10 People do not always view STEM occupations as directly benefiting society or individuals (although this is inaccurate).11
  • STEM subdisciplines with a clearer social purpose, such as medicine, biomedical engineering and environmental engineering, have higher percentages of women than have other subdisciplines like mechanical or electrical engineering.12
There are fewer women in STEM, their jobs are less secure and they earn less
    • Women earn nearly one-third less than men within a year of completing a PhD in a science, technology, engineering or mathematics (STEM) field.13
    • Although women fill close to half of all jobs in the U.S. economy, they hold less than 25% of STEM jobs. This has been the case throughout the past decade, even as college – educated women have increased their share of the overall workforce.14
    • Women who do not have children tend to earn more than women who do, but both groups still earn less than men.15 E.g. female physician researchers earn less than male counterparts, even after adjustments are made for other factors such as part time work16
    • Controlling for differences in academic field, women still lagged men by 11% in first-year earnings. That difference was explained entirely by the finding that married women with children earned less than men. Married men with children, on the other hand, saw no disadvantage in earnings.17
    • In academia, women outnumber men in full-time fixed term contracts, and in part-time and casual employment categories. Improved job security has been identified as the single factor that most increases job satisfaction.18
    • Research suggests that women who have young children within 5–10 years after earning their PhDs are less likely to have tenure-track jobs or to hold tenured faculty positions than men or women without children.19
    • This may be because outside of academia, female scientists tend to work slightly fewer hours than do their male counterparts.20
Once in, retention and rewards are lesser
      • Women’s representation among tenured faculty is lower than one would expect based on the supply of female science and engineering doctoral degree recipients in recent decades.21
      • For example, women earned 12% of the doctorates in engineering in 1996 but were only 7% of the tenured faculty in engineering in 2006. Even in fields like biology, where women now receive about one-half of doctorates and received 42% in 1996, women made up less than one-quarter of tenured faculty and only 34% of tenure-track faculty in 2006.22
      • Several studies have found a gender difference in hiring in STEM academic disciplines. Recent research found that when women do apply for STEM faculty positions at major research universities they are more likely than men to be hired, but smaller percentages of qualified women apply for these positions in the first place.23
      • Female STEM faculty express lower job satisfaction than do their male peers. Lower satisfaction leads to higher turnover and a loss of talent in science and engineering. The climate of science and engineering departments is closely related to satisfaction of female faculty and providing effective mentoring and work-life policies can help improve job satisfaction and, hence, the retention of female STEM faculty.24
      • Female scientists, engineers, and technologists in business and high-tech industry have higher attrition rates than do both their male peers, and women in other occupations. Midcareer is a critical time for female scientists. Female engineers and technologists are fairly well represented at the lower rungs on corporate ladders.25
      • Documented attrition among STEM faculty shows that women leave at higher rates than men, and women are more likely than men to consider changing jobs within academia. Women’s higher turnover intention in academia (which is the best predictor of actual turnover) is mainly due to dissatisfaction with departmental culture, advancement opportunities, faculty leadership, and research support.26 27
      • Between 2001 and 2014, women across 18 STEM disciplines were significantly underrepresented among recipients of scholarly and research awards and over represented in service and teaching awards relative to the proportion of PhDs, Full and Associate Professors.28
      • Regardless of their representation in the nomination pool, men were twice as likely to win scholarly awards.29
      • Minorities also remain woefully under-represented in the sciences. For example, both the gender and racial composition of the Ecological Society of America remains skewed compared to the overall US population, and leadership and award winners have mostly been white males.30
      • In the United Kingdom, there is also evidence that women academics in science, engineering, and mathematics have more administrative duties on average than men, and hence, less time to do research.31
      • Because scientists are increasingly judged by the number of their publications, citations, research grants, awards and membership of elite academies, this effectively constrains women’s career choices and progression.32
      • Women cite feelings of isolation, an unsupportive work environment, extreme work schedules, and unclear rules about advancement33 and success as major factors in their decision to leave.34 Family responsibilities such as caring for children and/or moving to follow a partner’s job are common reasons for exiting the science and engineering sector.35 36 37
      • Women are more likely to work part-time, and remain at the bottom of the academic hierarchy, with lower salaries, fewer senior roles, fewer opportunities for career development and training, more substantial teaching and service duties, and less research productivity than men.38 39
Implicit Bias
        • People judge women to be less competent than men in “male” jobs unless they are clearly successful. When a woman is clearly competent in a “masculine” job, she is considered to be less likable. Because both likability and competence are needed for success in the workplace, women in STEM fields can find themselves in a double bind.
        • Being disliked can affect career outcomes, leading to lower evaluations and less access to organizational rewards. Gender stereotypes can introduce bias in evaluative judgments of women in male-dominated environments, even when these women have proved themselves to be successful and demonstrated their competence.40
        • Bias can be explicit or implicit (unconscious). There are many unconscious biases. Implicit biases may reflect, be stronger than or in some cases contradict, explicitly held beliefs or values. Therefore, even individuals who espouse a belief in gender equity and equality may have implicit biases about gender and, hence, negative gender stereotypes about women and girls in science and math.41
        • Definition: A cognitive bias is a systemic deviation from rational thinking and a mistake in reasoning, evaluating, remembering, or other cognitive process, often occurring as a result of holding onto one’s preferences and beliefs regardless of contrary information. Cognitive biases relate to memory, reasoning and decision-making. Unconscious or hidden or implicit bias is defined as automatic prejudice triggered by quick assessments outside conscious awareness that are based on our one’s background, culture and personal experiences. These include amongst others: ingroup biases, assumptions of group behaviour, noticing data that confirms pre-existing expectations and evaluating those from minority groups more negatively.
        • Importantly, biases can change over time with societal views.
        • Biases are greatest against women of colour. As an educator, Bonilla-Santiago said she faced obstacles rooted in covert prejudice and low expectations. “I think women of colour in society have to constantly, particularly in academia, prove themselves,” Bonilla-Santiago, director of the Community Leadership Centre at Rutgers-Camden.42
Bias in Hiring
        • Yale researchers used different genders on two identical job applications. Regardless of selectors’ gender, most evaluated John as significantly more competent, more hireable and offered Jennifer a 12% lower salary and less mentorship.43
        • Both male and female faculty were equally likely to exhibit bias against Jennifer.44
        • Academic scientists tend to favour men applications over women for student positions.45
        • When scientists judged the female applicants more harshly, they did not use sexist reasoning explicitly to do so. Instead, they drew upon ostensibly sound reasons to justify why they would not want to hire her: she is not competent enough. This shows that you do not need to use anti- women language or even harbour conscious anti-women beliefs to behave in ways that are effectively anti-women. This makes it all the more easy for women to internalize unfair criticisms as valid.46
        • “If faculty express gender biases, we are not suggesting that these biases are intentional or stem from a conscious desire to impede the progress of women in science. Past studies indicate that people’s behaviour is shaped by implicit or unintended biases, stemming from repeated exposure to pervasive cultural stereotypes that portray women as less competent…”47
        • The challenge for women in information technology is implicit in this statistic: In 2015, women held 57% of all professional occupations, yet they held only 25% of all computing occupations. Research shows company culture, bias and discouragement from science and math all work against women in this male-dominated career.48
Bias in peer review
          • Female postdoctoral applicants have to be significantly more productive than a male applicant to receive the same peer review score. This meant that she either had to publish at least three more papers in a prestigious science journal or an additional 20 papers in lesser-known specialty journals to be judged as productive as a male applicant. Systematic underrating of female applicants could help explain the lower success rate of female scientists in achieving high academic rank compared with their male counterparts.49
          • STEM-talented women are similar to STEM-talented men in age of first publication, age at which STEM talent was first recognized, and age of PhD; however, women publish less frequently than men and women’s publications are less likely to be cited by peers.50,51 Even in engineering where women publish in higher impact journals, they receive fewer citations and it is hypothesised that this is due to male collaboration networks.52
          • Double blind reviewing of publications, where authors are not identifiable to reviewers, and vice versa, has increased publication rates for women first author researchers, suggesting either women were given harsher treatment during review, or were less likely to submit when their gender could be identified at submission.53
          • Systematic differences in letters of recommendation for academic faculty positions for female and male applicants occur. Recommenders (the majority of whom were men) appear to rely on accepted gender schema in which, for example, women are not expected to have significant accomplishments in a field like academic medicine. Letters written for women are more likely to refer to their compassion, teaching, and effort as opposed to their achievements, research, and ability, which are the characteristics highlighted for male applicants. Recommenders unknowingly used selective categorization and perception, also known as stereotyping, in choosing what features to include in their profiles of the female applicants”54
Bias in investment
          • In three entrepreneurial pitch competitions and two controlled experiments, Harvard and MIT researchers found that investors preferred entrepreneurial pitches presented by men to women. The effect was moderate by physical attractiveness for men, while physical attractiveness made no significant difference for women (but attractive women still scored lower than unattractive ones). Even when the content of the pitch is identical, men are more than twice as likely to have their entrepreneurial pitches funded than women.55
          • Diversity training on university faculty found that implicit associations about women in STEM improved for men. Women’s associations around women in STEM remained unchanged, as they already tended towards positive implicit associations.56
          • Men are more likely than women to explicitly endorse stereotypes about women in STEM and these attitudes did not change as a result of diversity training.57
          • In one study of conference talks at the American Astronomical Society, women were under- represented as question-askers. While there was likely an age effect, with senior scientists (mostly men) more likely to ask questions, women also asked disproportionately fewer questions in sessions chaired by men. Speaker gender seemed to have the greatest impact on the gender ratio of questioners.
What are the biases for women in STEMM, or being promoted to leadership within STEMM?
          • Mentoring may overcome some of the gender disparity in STEM and serve to increase the number of women at higher ranks.58
          • Scientific journals tend to appoint more men than women on editorial boards, and editors tend to select reviewers of the same gender as themselves 59
          • Expert ecologists of both genders persistently ranked men-dominated articles as higher quality before actual assessment, demonstrating subconscious bias.60
          • Scientists tend to rate writings authored by men higher than those authored by women.61
          • The work of female scientists is often invisible. For example, women scientists are consistently under-represented in ecology textbooks compared to baseline assumptions of no bias.62
          • Although female role models may be effective in the retention of women in STEM, female and male role models can be equally effective in recruitment efforts. Given the limited number of women in STEM, it may be most useful to concentrate their efforts on the retention of other women while encouraging men to serve as role models for potential female recruits.63
          • A study examining gender bias at the Yale School of Medicine has found significant inequities between male and female faculty. In addition to advancement and salary equity, the task force reported on an unfavourable climate for women on the school’s faculty. It stated that a review of earlier reports on the issue “revealed that concerns for gender equity have been present for at least two decades.” Concerns about sexual bias within the medical school faculty were highlighted earlier this year by news reports of a sexual-harassment complaint by a female former Yale researcher against Dr. Michael Simons, who was suspended for 18 months and removed as director at the Yale Cardiovascular Research Center.64
          • At the Salk Institute, a third female professor has sued the La Jolla Science Center for allegedly giving preference to men in pay, promotions, grant funding and leadership positions. “Very few females have made it to the level of full Professor, and those who have, have endured numerous discriminatory reprisals minimizing their successes.” That includes slower promotion processes, lower pay regardless of their experience and scientific contributions; and less access to crucial services needed to win grants, publish in the most prestigious journals and build an overall reputation of excellence.65
          • She also alleges in the lawsuit that there’s been “an unequal distribution of resources” when it comes to donor funding and lab staff. She describes a workplace where women are denied “nearly all leadership and professional advancement opportunities,” and where women “are undermined, disrespected, disparaged and treated unequally.”66
          • “There’s some good evidence to suggest that women have a more difficult time getting their work published in these journals because it is kind of an old boys’ network to get in in the first place,” Eisen said. “So it is particularly problematic to say, ‘Well geez, these women aren’t performing at the level of their male colleagues using, you know, a metric that’s known to be biased against women.’ To me, the fact that the Salk said that is a tacit acknowledgment that they’re using a gender-biased system to evaluate these women.”67
          • Among other issues reported by the Ad Hoc Task Force were “inadequate mentoring” and large differences between the numbers of men and women in senior positions. “Although the ratio of men to women hires approaches 1 at the Assistant Professor level,” with 148 men and 134 women hired, “more men are hired at higher ranks, especially tenured faculty positions,” the report states.68
          • Between 2010 and 2014, 20 men were hired as full Professors compared with five women, while the number hired at the level of tenured Associate Professor was seven men compared with one woman, according to the task force.69
          • Mentors who are influential in women’s decisions to major in STEM are female, enthusiastic about STEM, encourage questions, and treat their mentees with respect.70
          • Women that stay in STEM seek mentors more actively and are identified more frequently by mentors as possible protégés.71
          • Encouragement from mentors in graduate school plays an important role in women’s STEM persistence–for instance, female mathematics students who had doubts about continuing stayed when their advisors encouraged them.72
          • A professor’s encouragement can be the deciding factor in a woman’s choice of major; for example, a professor’s explicit recognition of women’s STEM aptitude and encouragement to continue influenced women’s decisions to major in STEM.73
          • Encouraging feedback keeps eminent female scientists focused and interested despite obstacles.74
What is the relationship of 1 to the problems women face no matter what field?
Women need to compose 15%–30% of a department or organization before they start having institutional effects.75
Bias in Hiring
          • If there is only one woman in your candidate pool, there is statistically no chance she will be hired.76
          • Male decision makers exhibit a pro-male bias and female decision makers exhibit minimal bias.77
          • When traditional gender roles are made salient, political ideology moderates evaluations of the female employment candidates such that conservatives evaluate her negatively and liberals evaluate her positively.78
          • Political ideology-based bias does not occur when the non-traditional female gender roles are made salient. This study also demonstrated that the observed effects were not driven by liberals and conservatives’ differing perceptions regarding the female applicant’s qualifications for the job.79
          • Without any information other than a candidate’s appearance, both men and women are twice more likely to hire a man than a woman. This remains the same when performance is self- reported, as men tend to boast about their performance, whereas women underreport it.80
          • Institutional support for family commitments is linked with job satisfaction and sense of belonging for both men and women. Women with low institutional support for family commitments were significantly less satisfied with their jobs and felt less belonging to their workplace environment than comparable men.81
          • Women of colour are by far the most marginalised in the workplace and in leadership. “…Black women founders only receive $36,000 in funding on average,” said Kathryn Finney, a tech entrepreneur and a 2013 recipient of the Champion of Change Award from the White House for her efforts to make the tech sector inclusive of black women.82
          • While venture capitalists sunk a record $37.1 billion into American tech start-ups last year, according to a Money Tree study, less than one-tenth of 1% of all venture capital funding went to black female founders between 2010 to 2014, reports ProjectDiane, Finney’s data-collection initiative. Furthermore, only 18 black women-owned ventures raised as much as $100,000 in outside investments, and only five received $2 million in the past five years.
          • Finney said stereotypes are strong barriers to entering the tech business. “The biggest challenge is overcoming this prevailing notion in the industry that black women don’t do tech,” she said.83
          • Many of the challenges facing women in their technology careers are attributed to the candidate funnel, inadequate professional development opportunities, hiring for “cultural fit” and other circumstances leading organizations to simply reinforce existing imbalances84
Gender pay gap
          • Women make up 45% of the global workforce and account for 70% of the population living in poverty.85
          • The gender pay gap clearly extends beyond STEMM, and it is estimated that women earn 20% less than men in America in 2016. If this rate of change continues, pay equality will not be reached until 2119. That’s just over a century.86
          • Non-white or non-Asian women are even more significantly marginalised. The pay gap increases with age and even more dramatically with disability. When we consider equality, it needs to be cross-cultural and across all societal sectors.87
          • More education is not an effective tool against the gender pay gap. At every level of academic achievement, women’s median earnings are less than men’s median earnings, and in some cases the gender pay gap is larger at higher levels of education.88
          • All of the biases mentioned in Question 1 are contributing factors to the gender pay gap across all sectors.
Workplace participation
          • Many entrenched organizational structures and work practices were designed to fit men’s lives and situations at a time when women made up only a very small portion of the workforce.89
          • Women remain significantly underrepresented across the length of the corporate pipeline. Fewer women than men are hired at the entry level, despite women being 57% of recent college graduates. At every subsequent step, the representation of women further declines.90
          • Women are much more likely to consider ethics in decision making and behaviour. With corporate ethics becoming more and more important to a business’ ability to thrive, these inherent differences should be even more important.91
          • Over time, empirical research, experience and common sense quickly proved that women were just as competent as men, providing they had the appropriate training, experience and supervision. So, it’s hard to believe today that in the past, women were considered too emotionally unstable, lacked confidence in handling conflict or that men and women simply couldn’t work together because of the potential of sexual attraction.92
Workplace retention
          • It seems that compared to STEMM, women and men leave their companies at similar rates. Of people leaving the workplace, only 2% or less say they’re leaving to focus on family. This percentage is also the same for men and women. The majority intend to stay in the workforce.
          • Three major factors contribute to broad workplace advantage: (1) Women experience a workplace skewed in favour of men. (2) Women of colour face even greater challenges. (3) Women and men see the success of gender diversity differently; men have a more positive assessment that often clashes with reality.93
          • Household work still falls squarely on women, regardless of the level of earning in the family. Time pressures negatively affect career aspirations.94
          • The women received more positive comments in workplace evaluations (excellent! stellar! terrific!) than the men, but only 6% of the women (as opposed to 15% of the men) were mentioned as potential partner material, reflecting, the researchers concluded, the application of lower standards to the women and (self-fulfilling) lower expectations. This is consistent with the bias that women need protection and special consideration, which restricts women’s advancement.95
          • The gender similarities hypothesis: males and females are similar on most, but not all, psychological variables. Results from a review of 46 meta analyses support the gender similarities hypothesis. Gender differences can vary substantially in magnitude at different ages and depend on the context in which measurement occurs. Overinflated claims of gender differences carry substantial costs in areas such as the workplace and relationships.96
          • The comprehensive body of research around these inherent and second generation biases shows why advocating for a “pure meritocracy” — rather than explicitly pursuing diversity — doesn’t help companies overcome bias. In fact, “meritocracy” may actually cause greater bias against women.97
          • Calling for a meritocracy and denying that workplace inequality still exists captures what scientists refer to as modern sexism.98
          • Women are the key to solving the challenges facing humanity. Women tend to think more about the longer term than do men, and about the future needs of their children and grandchildren. They tend to seek peaceful and constructive solutions to problems rather than fighting over differences in values and beliefs, or resources.99
What is the relationship of 2 to women in leadership generally?
          • Meta-analyses consistently reveal higher ratings for men than for women in occupations that confer high status, power, and pay — e.g. Leadership positions.100
          • Compared to women, men are more likely to hold traditional stereotypes about women (e.g., passive, timid) have less favourable attitudes toward gender egalitarianism, endorse hostile sexism, and view leadership positions as more masculine and less feminine.101
          • A recent study that compared current beliefs about what characterizes a good manager with beliefs of the past three decades found that people continue to ascribe stereotypically masculine traits, such as dominance, intuitiveness, and emotional stability to good managers. “Think manager – think man”102
          • Imposter syndrome- early family dynamics and later gender stereotyping contribute significantly. Men tend to own their success as a quality inherit to themselves; women project the cause of success outward as “luck” or “effort” that they don’t equate with inherent ability.103
          • Job adverts for male dominated areas employ wording that is associated with male stereotypes- leader, competitive, dominant, compared to adverts in female dominated areas. Adverts with masculine wording as perceived occupations that are predominantly male, and are less appealing to women.104
          • Many employees think women are well represented in leadership when they see only a few. Nearly 50% of men think women are well represented in leadership in organizations where only one in ten senior leaders is a woman. 39% of women believe the best opportunities go to the most deserving employees; compared to 47% of men. These unconscious biases mean that men are less committed to gender equality. This needs to change, as we can’t get to equality without them.105
          • The breakdown of female and male students in the business school’s undergraduate programs is about 50-50. But the percentage of female students pursuing an MBA drops significantly, falling to about 25%. Women hold only 4.6% of CEO positions at Standard & Poor’s top 500 companies — with only 23 female chief executives out of 500 companies, according to research group Catalyst.106
          • One factor in women’s lower rate of promotion is that they are less likely to receive advice from managers and senior leaders on how to advance. This kind of support is important: employees who receive it are more likely to say they’ve been promoted in the last two years.107
          • In top-performing companies, women are much more likely to be promoted to manager than in lesser performing companies (4% less likely to be promoted in higher performing compared to 18% less likely in lower performing companies).108
          • Subtle gender bias that persists in organizations and in society disrupts the learning cycle at the heart of becoming a leader. These second-generation biases including feeling less connected to one’s male colleagues, being advised to take a staff role to accommodate family, finding oneself excluded from consideration for key positions—all put women at a disadvantage.109
          • Most women are unaware of having personally been victims of gender discrimination and deny it even when it is objectively true and they see that women in general experience it.110
          • Women consistently excel in leadership roles. On all levels, women are rated higher in 12 of the 16 competencies that go into outstanding leadership. This included taking initiative and driving for results, which are thought of as particularly male strengths.111
          • But fewer female leaders means fewer role models and can suggest to young would-be leaders that being a woman is a liability, discouraging them from viewing senior women as credible sources of advice and support.112
          • Research indicates that organizations tend to ignore or undervalue behind-the-scenes work (building a team, avoiding a crisis), which women are more likely to do, while rewarding heroic work, which is most often done by men.113
          • Women often have to provide more evidence of competence than men do to be seen as equally capable, a problem documented in scores of studies on double standards, attribution bias, leniency bias, recall bias, and polarized evaluations.114
          • Women received 51.1% of appointments to state boards with functions classified as ‘feminine’, but only 15.8% of appointments to boards with functions classified as ‘masculine’, including commerce, finance, natural resources and more.115
          • In an overview of women’s representation in senior leadership positions in a region of Canada, across nine sectors, including elected office, education boards, health boards, corporate boards and union leaders, women held an average of 36 % of leadership positions.116
What holds women back?
NOT

  • qualifications or ability: Higher percentage of women then men hold a university degree and women consistently outperform men in terms of academic achievement
  • personality differences: Extraversion, conscientiousness and openness to experience (which consistently predict leadership emergence) are the same between women and men. Women show higher levels of agreeableness and neuroticism, but weak connections of these two dimensions with leadership.118

MORE LIKELY

  • Family responsibilities: Women’s domestic responsibilities exceed men’s – 2:1 and they don’t seem to be able to reduce this. Employed mothers in 2000 spent as much time interacting with their children as mothers without a job in 1975! But they still perceive that they spend too little time.120
  • Taking breaks from employment including leaves of absence and sick days for family members or seeking flexible or part-time jobs. 37% of professional women voluntarily dropped out of employment at some point in their lives compared to 24% of men. Women take time out for “family time”, men take time out to change careers. The serious implications are: lost income, impeded career growth, depreciation of skills, difficulty in re-establishing one’s career.121
  • Employment bias of 2:1 in favour of men at all levels.122

Even in female-dominated fields women don’t have the advantage! Token women generally suffer slow promotion in male-dominated careers but token men advance quickly in female dominated careers, the glass escalator effect.123

Men and women may want different types of leaders. Women have a perception of their ideal leader as more sensitive, understanding, sincere and helpful and less domineering, pushy and selfish than men.124

Women who adopt masculine styles of leadership (directive and assertive behaviours) tend to be disliked and their ability to wield influence can be undermined. Women also risk not getting a job or a promotion when they are too direct.125

Negotiation strategies can be an additional hurdle. Women routinely negotiate less desirable employment terms than men and women who are assertive in negotiation still need to engage in behaviours signalling warmth and likeability (gender consistent behaviours in order to achieve positive outcomes. Before negotiating, women report believing that they might be punished if they were perceived as too ‘pushy’ or ‘demanding’.126 Further, this fear of backlash was unique to women negotiating their own salaries, as those negotiating for a friend did not anticipate social punishment for their behaviour. The fear is warranted. Women and men both penalized female job candidates who initiated salary negotiations.127

Gender differences in negotiation performance lead to asymmetric distribution of rewards. Male managers and professionals negotiate 60% higher starting pay than their female peers.128

A series of experimental studies suggest that a female candidate is more likely to be appointed to a leadership position when the position is risky and there is an increased risk of failure. Are women set up to fail or are they considered to function better under crisis?129

Why do women hurt women or why women have a tendency to tear other women down both within STEMM and generally?
Historically, many negative judgments on the capacity of female friendship, mostly by men.130

Sociological findings suggest relational aggression or verbal and emotional abuse are more common in women. It is unclear if this is biologically or socially founded. Possibilities include:131

  • Sexual jealousy or competition for resources. Samantha Brick and others believe that women not men, belittle, objectify and sabotage other women, especially attractive ones.
  • Queen Bee obstacles. Women held to different standards than men and competitiveness is seen as positive in men but negative in women. Queen Bees are those who deny they have a gender problem as a response to a difficult male dominated environment.
  • Queen Bees with a more masculine leadership style do not believe they experience bias as they think they were different form other women. Although most women will think to mentor others when primed, Queen Bees do not. If Queen Bees are in leadership roles, they are unlikely to change gender bias.
  • Intersexual competition. In one study women react to a sexually attractive rival with aggressive and belittling behaviour but are helpful to the same woman dressed in a non-sexualized way.132
  • More intense pressures can arise from internal competition in minority groups.133
  • Time spent adapting to work expectations can have resource implications To manage the competence-likeability trade-off, women may downplay femininity, or try to soften a hard-charging style, or attempt to strike a perfect balance between the two. But overinvestment in one’s image diminishes the emotional and motivational resources available for larger purposes. People who focus on how others perceive them are less clear about their goals, less open to learning from failure, and less capable of self-regulation.134
Family responsibilities and prejudices against mothers
  • “… Pregnancy is… a wonderful thing for the woman, it’s a wonderful thing for the husband… it’s certainly an inconvenience for a business.”– Donald Trump (2004)
  • Today, 42% of mothers with children under the age of 18 are their families’ primary or sole breadwinners.135 Inequality in pay contributes directly to poverty affecting women, and the family more broadly.136
  • Many people think that women leave STEM academic careers because they cannot balance work and family responsibilities.137 However there is evidence138 for a more nuanced relationship between family responsibilities and academic STEM careers.
  • Being single is a good predictor that a woman will be hired for a tenure-track job and promoted. Research also shows that marriage is a good predictor for both women and men of being hired as an Assistant Professor. However children change the equation. Married women with children in STEM have fewer tenure and promotion opportunities compared to married men with children.139
  • Other data from academic environments suggest that over time, children affect women’s careers and women may recognise this. Among tenured faculty in the sciences, 12 to 14 years after earning a doctorate 70% of men but only 50% of the women had children living in their home. In this cohort, 77% of male science professors who had babies within the first 5 years of receiving a doctorate, achieved tenure, while only 53% of women had achieved this140
  • More than twice as many female academics (38%) as male academics (18%) indicated that they had fewer children than they had wanted.141
  • Male and female postdocs without children are equally likely to decide against research careers. But female postdocs who become parents or plan to have children abandon research careers up to twice as often as men in similar circumstances.142
  • Having young children may affect women’s productivity since child-care responsibilities fall disproportionately on women.143 This is not unique to STEM. In business and industry both women and men identify family responsibilities as a possible barrier to advancement, but women are affected differently by this “family penalty”. Although both feel that having a family hinders their success at work, women are more likely than men to report foregoing marriage or children and delaying having children. Among women and men with families, women are more likely to report that they are the primary caregiver and have a partner who also works full time.144.
  • A recent retention study found that most women and men who left engineering said that interest in another career was a reason, but women were far more likely than men to also cite time and family-related issues.145
  • Additionally, women in STEM are more likely to have a partner who is also in STEM and faces a similarly demanding work schedule. In a situation where a “two body problem” exists, the man’s career is often given priority.146
  • Early career working women face an additional family-related barrier to career advancement as they may be viewed likely to have an (eventual) pregnancy (“maybe baby” effect). This possible life event is construed as an organizational inconvenience.147
  • Women who become faculty members in Astronomy, Physics and Biology tend to have fewer children than their male colleagues — 1.2 versus 1.5 on average. They also have fewer children than they desire.148
  • There are many biases held by women and men about the role of motherhood. Female professionals report the need to “go the extra mile” and “prove they are the same” to calm co- workers’ and supervisors’ fears about pregnancy-related losses in terms of their dependability.149 Experimental studies show biases against mothers in competence expectations and screening recommendations.150 Working mothers are seen as more self-oriented and as less dedicated to their children than stay-at home mums, especially when they are believed to work because of personal choice.151 Working mothers are also seen as less dedicated to work15214. (“Women in STEM: A Gender Gap to Innovation | Economics & Statistics Administration” n.d.)15. www.chiefscientist.gov.au [Australia’s STEM Workforce Full Report, March 2016]16. PMR: Journal of Injury, Function & Rehabilitation https://doi.org/10.1016/j.pmrj.2017.02.016

    17. American Economic Review doi:10.1257/aer.p20161124

    18. Bell and Yates 2015 http://www.lhmartininstitute.edu.au/documents/publications/wmn‐in‐sci‐rsrch‐rprt‐web‐070915.pdf

    19. Mason, M. A. & Goulden, M. Academe 88, 21–27 (2002)

    20. Ceci, S. J., Ginther, D. K., Kahn, S. & Williams, W. M. Psychol. Sci. Public Interest 15, 75–141(2014)

    21. Kulis, S., Sicotte, D., & Collins, S. (2002). More than a pipeline problem: Labor supply constraints and gender stratification across academic science disciplines. Research in Higher Education, 43(6), 657‐691. DOI: 10.1023/A:1020988531713

    22. http://www.nsf.gov/statistics/nsf08321

     

    23. Bentley & Adamson, 2003; Nelson & Rogers, n.d.; Ginther & Kahn, 2006, National Research Council, 2009

    24. Cathy Trower and her colleagues at the Collaborative on Academic Careers in Higher Educa‐ tion (COACHE) at Harvard University

    25. Hewlett, S.A et al 2008. The Athena factor: Reversing the brain drain in science, engineering, and technology. Harvard Business Review Research
    Report, 10094, pp.1‐100.

    Simard, C, Gilmartin S, Senior technical women: a profile of success, 2008, Anita Borg Institute for gender and technology, www.gender.stanford.edu

    26. Xu (2008) DOI: 10.1007/s11162‐008‐9097‐4

    27. O’Brien KR and Hapgood KP 2012 The academic jungle: ecosystem modelling reveals why women are driven out of research. Oikos 121: 999‐1004, doi: 10.1111/j.1600‐0706.2012.20601.x

    28. Scholars awards go mainly to men, Nature, 2011, January, 469: 472
    AU; AAUW report. Why so Few? Women in Science, Technology, Engineering and Mathematics, Catherine Hill, Ph.D. Christianne Corbett Andresse St. Rose,

    Ed.D. 2010, www.aauw.org; https://implicit.harvard.edu/implicit/

    29. http://www.awis.org/?

    30. Beck C, Boersma K, Tysor CS and Middendorf G. Diversity at 100: women and underrepresented minoriteies in the ESA. doi:10.1890/14.WB.011

    31. Aldercotte A, Guyan K, Lawson J, Neave S and Altorjai S. ASSET 2016: experiences of gender equality in STEMM academia and their intersections with ethnicity, sexual orientation, disability and age.

    Equality Challenge unit, London, UK, 2017

    32. Xie Y 2014 “Undemocracy”: inequalities in science. Science 344: 809‐810

    33. Hunt, J. 2010. Why do women leave science and engineering? NBER Working Paper 15853, National Bureau of Economic Research, MA, USA

    34. Hewlett, S.A et al 2008. The Athena factor: Reversing the brain drain in science, engineering, and technology. Harvard Business Review Research
    Report, 10094, pp.1‐100

    35. Herman, C. and Webster, J. 2010. Taking a lifecycle approach: redefining women returners to science, engineering and technology. – Int. J. Gender Sci. Technol. 2: 1–27

    36. Hunt, J. 2010. Why do women leave science and engineering? NBER Working Paper 15853, National Bureau of Economic Research, MA, USA.

    37. Robinson, C. V. 2011. Women in science: in pursuit of female chemists. Nature 476: 273–275.

    38. Aldercotte A, Guyan K, Lawson J, Neave S and Altorjai S. ASSET 2016: experiences of gender equality in STEMM academia and their intersections with ethnicity, sexual orientation, disability and age. Equality Challenge unit, London, UK, 2017

    39. Buckley LM, Sanders K, Shih M, Kallar S and Hampton C. 2000 Obstacles to promotion? Values of women faculty about career success and recognition. Academ. Med. 75: 283‐288.

    40. Heilman et al., 2004AAUW report. Why so Few? Women in Science, Technology, Engineering and Mathematics, Catherine Hill, Ph.D. Christianne Corbett Andresse St. Rose, Ed.D. 2010, www.aauw.org

    https://implicit.harvard.edu/implicit/

    41. Valian, 1998, ISBN: 9780262220545. Nosek BA, Mahzarin R.B., Math=Male, Me=Female, Therefore Math not equal Me, 2002 Journal of Personality and Social Psychology , Vol. 83, No. 1, 44–59 DOI: 10.1037//0022‐3514.83.1.44

     

    42. McGuire, JN 2016, ‘At Rutgers‐Camden, women leaders reflect on what it took’, Philadelphia Inquirer, The (PA).

    43. Moss‐Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham, M.J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences, 109(41), 16474‐79. doi:10.1073/pnas.121286109

    44. Moss‐Racusin CA, Dovidio JF, Brescoll VL, Graham MJ and Handelsman J. Science faculty’s subtle gender biases favour male students. PNAS 109: 16474‐16479.

    45. Moss‐Racusin CA, Dovidio JF, Brescoll VL, Graham MJ and Handelsman J. Science faculty’s subtle gender biases favour male students. PNAS 109: 16474‐16479.

    46. Blogs scientificamerican, “Study shows Gender bias in science is real: here’s why it matters” Yurkiewitz 2012:

    47. Blogs scientificamerican, “Study shows Gender bias in science is real: here’s why it matters” Yurkiewitz 2012:

    48. Scheid, L 2016, ‘The challenges and rewards for women in information technology’, Reading Eagle (PA).

    49. Wenneras & Wold, 1997 DOI: 10.1038/387341a0, Steinpreis et al., 1999 DOI: 10.1023/A:1018839203698

     

    50. Bird KS, 2011. Do women publish fewer journal articles than men? Sex differences in publication productivity in the social sciences, British Journal of Sociology of Education , 32 , (6), https://doi.org/10.1080/01425692.2011.59638

    51. Journal of Health Organization and Management https://doi.org/10.1108/JHOM‐12‐2016‐0243

    52. Ghiasi G, Larivière V, Sugimoto CR (2015) On the Compliance of Women Engineers with a Gendered Scientific System. PLoS ONE 10(12): e0145931. https://doi.org/10.1371/journal.pone.0145931

    53. Budden AE et al.2008 Double‐blind review ravours increased representation of female authors. Trends. Ecol. Evol. 23: 4‐6 doi: http://dx.doi.org/10.1016/j.tree.2007.07.008

    54. Trix and Psenka (2003) https://doi.org/10.1177/0957926503014002277

    55. Brooks, A., Huang, L., Kearney, S.W., & Murray, F.E. (2014). Investors prefer entrepreneurial ventures pitched by attractive men. Proceedings of the National Academy of Sciences, 111(12), 4427‐4431.

    56. Jackson, Hillard, and Schneider (2014) https://doi.org/10.1007/s11218‐014‐9259‐5 57 Jackson, Hillard, and Schneider (2014) https://doi.org/10.1007/s11218‐014‐9259‐5

     

    58. Adams, Steiner, and Wiedinmyer (2015) https://doi.org/10.1175/BAMS‐D‐15‐00040.1

    59. Helmer M, Schottdorf M, Neef A and Battaglia D. 2017 Gender bias in scholarly peer review. eLife 6, e21718. Doi: 10.7554/eLife.21718

    60. Bradshaw CJA and Courchamp F 2017 Gender‐biased perceptions of important ecology articles. Pre‐print. doi: http://dx.doi.org/10.1101/219824

    61. Knobloch‐Westerwick S, Glynn CJ and huge M 2013. The Matilda Effect in science communication. Sci. Comm. 35: 603‐625. Doi: 10.1177/1075547012472684

    62. Damschen EI et al. Visibility matters: increasing knowledge of women’s contributions to ecology. Frontiers. Ecol. Environ. 3: 212‐219. doi:10.1890/1540‐9295(2005)003[0212:VMIKOW]2.0.CO;2

    63. Drury, Siy, and Cheryan (2011) https://doi.org/10.1080/1047840X.2011.620935

    64. Stannard, E 2015, ‘Report details wide gender‐based inequities at Yale School of Medicine’, New Haven Register (CT).

    65. Fikes, GJ 2017, ‘Gender discrimination controversy grows at fabled Salk Institute’, San Diego Union‐Tribune, The (CA).

    66. Fikes, GJ 2017, ‘Gender discrimination controversy grows at fabled Salk Institute’, San Diego Union‐Tribune, The (CA)

    67. Fikes, GJ 2017, ‘Gender discrimination controversy grows at fabled Salk Institute’, San Diego Union‐Tribune, The (CA).

    68. Stannard, E 2015, ‘Report details wide gender‐based inequities at Yale School of Medicine’, New Haven Register (CT).

    69. Stannard, E 2015, ‘Report details wide gender‐based inequities at Yale School of Medicine’, New Haven Register (CT).

    70. Review of Educational Research doi:10.3102/00346543074002171

    71. Journal of Adult Development doi:10.1007/s10804‐006‐9002‐3

    72. Journal of Secondary Gifted Education doi:10.4219/jsge‐2001‐363

    73. Review of Educational Research doi:10.3102/00346543074002171

    74. REF: Journal of Secondary Gifted Education doi:10.1177/1932202×9600700406

     

    75. Holmes et al. (2008) https://doi.org/10.1038/ngeo113

    76. Johnson, Hekman, and Chan (2016) https://hbr.org/2016/04/if‐theres‐only‐one‐woman‐in‐your‐candidate‐pool‐theres‐statistically‐no‐chance‐shell‐be‐hired

    77. Sex Roles doi:10.1007/BF00289761

    78. Journal of Experimental Psychology https://doi.org/10.1016/j.jesp.2011.08.004

    79. Journal of Experimental Psychology https://doi.org/10.1016/j.jesp.2011.08.004

    80. Reuben, Sapienza, and Zingales (2014) https://doi.org/10.1073/pnas.1314788111

    81. Moors, Malley, and Stewart (2014) https://doi.org/10.1177/0361684314542343

    82. Sapong, E 2015, ’43North winners break down tech barriers for black female entrepreneurs’, Buffalo News, The (NY).

    83. Sapong, E 2015, ’43North winners break down tech barriers for black female entrepreneurs’, Buffalo News, The (NY).

     

    84. Marketwired 2016, ‘Breaking Barriers: 2016 HR Technology Conference to Host Inaugural Women in HR Technology Pre‐Conference Event’, Marketwire

    85. Todaro, Lenora. ‘Going after globalization’ The Village Voice ; New York [New York]20 June 2000: 59‐60.

    86. AAUW (2017) The SIMPLE TRUTH ABOUT THE GENDER PAY GAP https://www.aauw.org/resource/the‐simple‐truth‐about‐the‐gender‐pay‐gap/

    87. AAUW (2017) The SIMPLE TRUTH ABOUT THE GENDER PAY GAP https://www.aauw.org/resource/the‐simple‐truth‐about‐the‐gender‐pay‐gap/

    88. AAUW (2017) The SIMPLE TRUTH ABOUT THE GENDER PAY GAP https://www.aauw.org/resource/the‐simple‐truth‐about‐the‐gender‐pay‐gap/

    89. hbr.org (Harvard Business Review): Sept 2013. Ibarra et al “ Women rising: the unseen barriers”

    90. Mckinsey and LeanIn.Org; Women in the Workplace (2017) https://www.mckinsey.com/global‐themes/gender‐equality/women‐in‐the‐workplace‐2017

    91. Women in the Workplace: A Research Roundup (2013) Harvard Business Review. https://hbr.org/2013/09/women‐in‐the‐workplace‐a‐research‐ roundup?referral=03759&cm_vc=rr_item_page.bottom

    92. ‘Climbing ranks’, 2013, Winnipeg Free Press (MB), p. H1.

    93. http://swim.yale.edu/Women_in_the_Workplace_2017_318513_1095_5_v1.pdf

    94. Mckinsey and LeanIn.Org; Women in the Workplace (2017) https://www.mckinsey.com/global‐themes/gender‐equality/women‐in‐the‐workplace‐2017

    95. Women in the Workplace: A Research Roundup (2013) Harvard Business Review. https://hbr.org/2013/09/women‐in‐the‐workplace‐a‐research‐ roundup?referral=03759&cm_vc=rr_item_page.bottom

    96. Hyde, J.S., 2005. The gender similarities hypothesis. American psychologist, 60(6), p.581. http://gsappweb.rutgers.edu/cstudents/readings/Summer/Summer/Kelly_Diversity/Hyde%202005%20gender%20similarities%20hypothesis.pdf

    97. Johnson (2017) What the Science Actually Says About Gender Gaps in the Workplace. Harvard Business Review. https://hbr.org/2017/08/what‐the‐science‐ actually‐says‐about‐gender‐gaps‐in‐the‐workplace?referral=03759&cm_vc=rr_item_page.bottom

    98. Johnson (2017) What the Science Actually Says About Gender Gaps in the Workplace. Harvard Business Review. https://hbr.org/2017/08/what‐the‐science‐ actually‐says‐about‐gender‐gaps‐in‐the‐workplace?referral=03759&cm_vc=rr_item_page.bottom

    99. Julian Cribb, Surviving the 21st Century – Humanity’s ten greatest challenges and how to overcome them.

    100. Journal of Experimental Psychology https://doi.org/10.1016/j.jesp.2011.08.004

    101. Journal of Applied Psychology DOI: 10.1037/a0036734

    102. Journal of Personality and Social Psychology doi:10.1037/0022‐3514.46.4.735

    103. Clance and Imes (1978) https://doi.org/10.1037/h0086006

    104. Gaucher, Friesen, and Kay (2011) https://doi.org/10.1037/a0022530

    105. Mckinsey and LeanIn.Org; Women in the Workplace (2017)

    106. Hernandez, ML 2012, ‘UTPA wants more women STEM professors’, Monitor, The (McAllen, TX).

    107. Mckinsey and LeanIn.Org; Women in the Workplace (2017) https://www.mckinsey.com/global‐themes/gender‐equality/women‐in‐the‐workplace‐2017

    108. Mckinsey and LeanIn.Org; Women in the Workplace (2017) https://www.mckinsey.com/global‐themes/gender‐equality/women‐in‐the‐workplace‐2017

    109. Herminia Ibarra, Robin J. Ely, Deborah M. Kolb. (2013. Women Rising: The Unseen Barriers https://hbr.org/2013/09/women‐rising‐the‐unseen‐barriers

    110. Herminia Ibarra, Robin J. Ely, Deborah M. Kolb. (2013. Women Rising: The Unseen Barriers https://hbr.org/2013/09/women‐rising‐the‐unseen‐barriers

    111. Herminia Ibarra, Robin J. Ely, Deborah M. Kolb. (2013. Women Rising: The Unseen Barriers https://hbr.org/2013/09/women‐rising‐the‐unseen‐barriers

    112. hbr.org (Harvard Business Review): Sept 2013. Ibarra et al “ Women rising: the unseen barriers”

    113. hbr.org (Harvard Business Review): Sept 2013. Ibarra et al “ Women rising: the unseen barriers”

    114. Hbr: Hacking Tech’s diversity problem (Williams, 2014)

    115. Russell, BZ 2015, ‘Idaho boards, commissions lack women, study says’, Spokesman‐Review, The (Spokane, WA).

    116. ‘Mohawk College Stoney Creek hopes to expand leadership opportunities for women’, 2015, Stoney Creek News (ON).

    117. “What Holds Women Back?” Olga Epitropaki, American Business School of Greece

    118. Costa PT1, Terracciano A, McCrae RR, 2001, Gender differences in personality traits across cultures: robust and surprising findings, J Pers Soc Psychol. 2001 Aug;81(2):322‐331. doi: 10.1037/0022‐3514.81.2.322. DOI:10.1037/0022‐3514.81.2.322

     

    119. Bessette, C 2015, ‘Participants in Women in Leadership forum attempt to break barriers’, Day, The (New London, CT).

    120. Bianci et al., 2000 DOI 10.1353/dem.2000.0001

    121. Hewlett, S.A., Luce, C.B. and West, C., 2005. Leadership in your midst. Harvard Business Review, 83(11), pp.74‐82.

    122. Steinpreis, Anders, & Ritzke (1999) The impact of gender on the review of the curricula vitae of job applicants and tenure candidates: A National Empirical Study, Sex Roles, 41; 509

    Daryl G. Smith, Caroline Sotello Viernes Turner, Nana Osei‐Kofi, Sandra Richards, 2004. Interrupting the Usual: Successful Strategies for Hiring Diverse Faculty, The Journal of Higher Education, 75 (2), , pp. 133‐160 DOI: 10.1353/jhe.2004.0006

    123. Williams CL. The glass escalator: Hidden advantages for men in the “female” professions. Social problems. 1992 Aug 1;39(3):253‐67. https://doi.org/10.2307/3096961

    124. Epitropaki & Martin 2004; 2005 DOI: 10.1037/0021‐9010.89.2.293 and DOI: 10.1037/0021‐9010.90.4.659

    125. Tepper et al., 1993 DOI: 10.1111/j.1559‐1816.1993.tb01072.x ; Bowles et al., 2007 DOI: 10.1016/j.obhdp.2006.09.001.

    126. Amanatullah and Morris 2013. Ask and Ye Shall Receive? How Gender and Status Moderate Negotiation Success.. Negotiation and Coflict Management Research, 6(4),pp. 253–72

    127. Hannah Riley Bowles (Harvard University), Linda Babcock (Carnegie Mellon University), and Lei Lai (Tulane University)

    128. Gerhart & Rynes, 1991 10.1037/0021‐9010.76.2.256

    129. Ryan, Michelle K. and Haslam, S. Alexander, The Glass Cliff: Evidence that Women are Over‐Represented in Precarious Leadership Positions. British Journal of Management, Vol. 16, No. 2, pp. 81‐90, June 2005. Available at SSRN: https://ssrn.com/abstract=734677

     

    130. Alger WR. The Friendships of Women. Roberts brothers; 1879.
    Schopenhauer A, Saunders TB. The essays of Arthur Schopenhauer: the wisdom of life. Tredition Gmbh; 2011.

    131. Derks B, Van Laar C, Ellemers N, De Groot K. Gender‐bias primes elicit queen‐bee responses among senior policewomen. Psychological Science. 2011 Oct;22(10):1243‐9. https://doi.org/10.1177/0956797611417258

    Derks B, Ellemers N, Van Laar C, De Groot K. Do sexist organizational cultures create the Queen Bee?. British Journal of Social Psychology. 2011 Sep 1;50(3):519‐35. DOI: 10.1348/014466610X525280

    132. Vaillancourt T, Sharma A. Intolerance of sexy peers: Intrasexual competition among women. Aggressive behavior. 2011 Nov 1;37(6):569‐77.
    DOI: 10.1002/ab.20413

    133. Manuca R, Li Y, Riolo R, Savit R. The structure of adaptive competition in minority games. Physica A: Statistical Mechanics and its Applications. 2000 Jul 15;282(3):559‐608. https://doi.org/10.1016/S0378‐4371(00)00100‐X

    134. (Herminia Ibarra, Robin J. Ely, Deborah M. Kolb. 2013. Women Rising: The Unseen Barriers https://hbr.org/2013/09/women‐rising‐the‐unseen‐barriers)

     

    135. Glynn SJ. Breadwinning mothers are increasingly the US norm. Center for American Progress. https://www.americanprogress.org/issues/women/reports/2016/12/19/295203/breadwinning‐mothers‐are‐increasingly‐the‐us‐norm/. Posted December. 2016;19. 136 (AAUW 2017. The SIMPLE TRUTH ABOUT THE GENDER PAY GAP)

    137. Mason MA, Goulden M, Frasch K. Why graduate students reject the fast track. Academe. 2009 Jan 1;95(1):11.

    Xie & Shauman, 2003 DOI: https://doi.org/10.1007/978‐94‐010‐0007‐9_8

    138. Xu (2008) DOI: 10.1007/s11162‐008‐9097‐4

    139. Xie & Shauman, 2003 DOI: https://doi.org/10.1007/978‐94‐010‐0007‐9_8;

    Ginther & Kahn, 2006 DOI: 10.3386/w12691

    140. Mason and Goulden (2002) DOI: DOI: 10.2307/40252436

    141. Mason and Goulden study (2004) Academe doi:10.2307/40252436

    142. Shen (2013) https://doi.org/10.1038/495022a

    143. Stack, 2004 DOI: 10.1007/s11162‐004‐5953‐z

    144. Simard, C, Gilmartin S, Senior technical women: a profile of success, 2008, Anita Borg Institute for gender and technology, www.gender.stanford.edu

    144. Xu (2008) DOI: 10.1007/s11162‐008‐9097‐4

    145. https://societyofwomenengineers.swe.org

    Frehill LM, Di Fabio NM, Hill ST. 2008. Confronting the new American dilemma: Underrepresented minorites in engineering: A data‐based look at diversity. White Plains, NY: National Action Council for Minorities in Engineering.

    146. Hewlett SA, Carolyn BL, Lisa JS. 2008. “The Athena Factor: Reversing the Brain Drain in Science, Engineering, and Technology”. Harvard Business Review Research Report 10094.

    147. Journal of Vocational Behavior https://doi.org/10.1016/j.jvb.2017.10.001

    148. Ecklund and Lincoln (2011) https://doi.org/10.1371/journal.pone.0022590

    149. Academy of Management Journal https://doi.org/10.5465/amj.2013.0599

    150. Heilman & Okimoto, 2008 DOI: 10.1037/0021‐9010.93.1.189

    151. Etaugh & Nekolny, 1990, DOI: 10.1007/BF00290048

    152. https://www.economist.com/blogs/democracyinamerica/2015/01/women‐and‐work

    153. Henry, B 2016, ‘Plan to beat gender bias in public service’, Canberra Times, p. 5.

Gender Fact Sheet

This is an abbreviated version of Women’s empowerment and diversity in the workplace, key facts without referencing.

Photos by Oli Sansom

The business case for increased gender diversity in leadership

There is a widely held view that leadership capability is gender-neutral and that merit is the only valid criterion to consider and, therefore, it is irrelevant what proportion of senior positions are held by women.

It is not.

There is certainly a burden of ideology that stacks up on either side of this argument, but the evidence is irrefutable, so it is worth providing some headline findings from some of the most reputable studies.

Proposition 1: Men and women are different

Seemingly self-evident; however, the view that it doesn’t matter whether senior roles are filled by men or women would belie this. If there are benefits to a more diverse range of views in senior teams1 , then what is the basis of this diversity?

If we look at the normative data for CEB’s SHL Occupational Personality Questionnaire (OPQ), which is one of the most widely used and respected measures of workplace behavioural style in the world, there are five (out of 32) personality characteristics where there are statistically significant differences that are deemed to have a meaningful impact2:

Data-rational, controlling, tough-minded
Men describe themselves as being higher in these traits than women, but the difference is less than a STEN3 on average
Competitive
Men describe themselves as being higher in this trait than women, with the difference being a STEN on average.
Caring
Caring shows the largest gender difference in scores of all of them. There is an average difference of nearly one and a
half STENS between the two groups.

Proposition 2: Women demonstrate some key leadership capabilities to a greater degree than do men

MCKINSEY & CO

Arguably the world’s leading management consulting firm, McKinsey & Co have identified nine leadership behaviours that most significantly improve organisational performance4:

Across their sample of 9000 men and women, they found significant differences in the frequency with which they use certain leadership styles:

HAY GROUP

Much has been written about the so-called ‘soft skills’ of leadership and these were frequently cited by CH2M interviewees in discussing what women bring to leadership roles. One of the most robust measures of these skills is the Emotional and Social Competence Inventory (ESCI), developed by Daniel Goleman (Harvard) and Richard E Boyatzis (Case Western Reserve University).

According to new research by the Hay Group division of Korn Ferry, women score higher than men on nearly all emotional intelligence competencies, except emotional self-control, where no gender differences are observed5.

Data from 55,000 professionals across 90 countries and all levels of management, collected between 2011 and 2015, using the ESCI, found that women more effectively employ the emotional and social competencies correlated with effective leadership and management than men.

ZENGER AND JOSEPH FOLKMAN

A review of the 360-degree assessment results of 7280 leaders showed that the 2629 women in the sample demonstrated 15 out of a total 16 competencies shown to drive business performance, more frequently than did men6.

PROPOSITION 3: ORGANISATIONS THAT HAVE GREATER GENDER DIVERSITY IN SENIOR LEADERSHIP OUTPERFORM THOSE THAT DO NOT

MCKINSEY & CO

This has been researched by McKinsey & Co, first in 20077 and again in 20108; the results each time were unequivocal.

DEVELOPMENT DIMENSIONS INTERNATIONAL (DDI)

Similar findings emerged from Development Dimensions International’s (DDI) research undertaken in 20159, evaluating survey responses from 13,124 leaders: 1528 global human resource executives representing 2031 participating organisations.

Once again, when segmented by financial performance, there were large differences in the proportion of women in leadership roles.

CREDIT SUISSE

In a recent Credit Suisse report10 it was “found that, overall, companies with a market cap greater than US$10 billion that have at least one woman on the board of directors outperformed those that had no women at all by 26% for large caps over the six years leading up to 2011. From 2012 to June 2014, companies with at least one woman on the board have seen a 5% out performance on a sector neutral basis.”

It was also found that “countries in the Asia- Pacific saw the greatest out performance with a 55% excess cumulative return.”

REIBEY INSTITUTE

In their 2011 study of gender diversity in the Australian Stock Exchange (ASX) the Reibey Institute found the following with regards to larger Australian public companies11:

REFERENCES/Footnotes

1 We would argue that this is true of many bases of diversity (i.e. age, racial and cultural background, etc.), but this is beyond the scope of the current research.

2 Occupational Personality Questionnaire 32: Dimension descriptions, SHL Group Ltd

3 A STEN is a statistical measure that is equivalent to 0.5 of one standard deviation.

4 From ‘Female leadership: A competitive edge for the future’, Women Matter series, McKinsey & Company, 2008

5 Source: www.kornferry.com/press/new-research-shows-women-are-better-at-using-soft-skills-crucial-for-effective-leadership/

6 Jack Zenger & Joseph Folkman, ‘Are women better leaders than men?’ Harvard Business Review, 5 March 2012

7 ‘Gender diversity: A corporate performance driver’, Women Matter series, McKinsey & Company, 2007

8 ‘Women at the top of corporations: Making it happen’, Women Matter series, McKinsey & Company, 2010

9 ‘Global Leadership Forecast 2014|2015’, Development Dimensions International (DDI)

10 The CS Gender 3000: Women in Senior Management (2014)

11 http://www.reibeyinstitute.org.au/wp-content/uploads/2011/10/ASX500_Women-Leaders-2011.pdf