Women in STEM fields
The examples and perspective in this article deal primarily with the United States and do not represent a worldwide view of the subject. (April 2014) (Learn how and when to remove this template message)
Many scholars and policymakers have noted that the fields of science, technology, engineering, and mathematics (STEM) have remained predominantly male with historically low participation among women since their origins during the Age of Enlightenment.
Scholars are exploring the various reasons for the continued existence of this gender disparity in STEM fields. Those who view this disparity as resulting from discriminatory forces are also seeking ways to redress this disparity within STEM fields (these typically construed as well-compensated, high-status professions with universal career appeal). Some proponents view diversity as an inherent human good, and wish to increase diversity for its own sake, regardless of its historical origin or present cause.
Gender imbalance in STEM fieldsEdit
Studies suggest that many factors contribute to the attitudes towards the achievement of young women in mathematics and science, including encouragement from parents, interactions with mathematics and science teachers, curriculum content, hands-on laboratory experiences, high school achievement in mathematics and science, and resources available at home. In the United States, research findings are mixed concerning when boys' and girls' attitudes about mathematics and science diverge. Analyzing several nationally representative longitudinal studies, one researcher found few differences in girls' and boys' attitudes towards science in the early secondary school years. Students' aspirations to pursue careers in mathematics and science influence both the courses they choose to take in those areas and the level of effort they put forth in these courses.
A 1996 study suggested girls begin to lose self-confidence in middle school because they believe that men possess more intelligence in technological fields. The fact that men outperform women in spatial analysis, a skillset many engineering professionals deem vital, generates this misconception. Feminist scholars postulate that boys are more likely to gain spatial skills outside the classroom because they are culturally encouraged to build and work with their hands. Research shows that girls can develop these same skills with the same form of training.
A 1996 study of college freshmen by the Higher Education Research Institute shows that men and women differ greatly in their intended fields of study. Of first-time college freshmen in 1996, 20 percent of men and 4 percent of women planned to major in computer science and engineering, while similar percentages of men and women planned to major in biology or physical sciences. The differences in the intended majors between male and female first-time freshmen directly relate to the differences in the fields in which men and women earn their degree. At the post-secondary level, women are less likely than men to earn a degree in mathematics, physical sciences, or computer sciences and engineering. The exception to this gender imbalance is in the field of life science.
Effects of underrepresentation of women in STEM careersEdit
In Scotland, a large number of women graduate in STEM subjects but fail to move onto a STEM career compared to men. The Royal Society of Edinburgh estimates that doubling women's high-skill contributions to Scotland's economy would benefit it by £170 million per annum.
Men's and women's earningsEdit
Female college graduates earned less on average than male college graduates, even though they shared the earnings growth of all college graduates in the 1980s. Some of the differences in salary are related to the differences in occupations entered by women and men. Among recent science and engineering bachelor's degree recipients, women were less likely than men to be employed in science and engineering occupations. There remains a wage gap between men and women in comparable scientific positions. Among more experienced scientists and engineers, the gender gap in salaries is greater than for recent graduates. Salaries are highest in mathematics, computer science, and engineering, which are fields in which women are not highly represented. In Australia, a study conducted by the Australian Bureau of Statistics has shown that the current gender wage gap between men and women in STEM fields in Australia stands at 30.1 percent as of 2013, which is an increase of 3 percent since 2012.
Education and perceptionEdit
The percentage of PhDs in STEM fields in the U.S. earned by women is about 42%, whereas the percentage of PhDs in all fields earned by women is about 52%. Stereotypes and educational differences can lead to the decline of women in STEM fields. These differences start as early as the third grade according to Thomas Dee, with boys advancing in math and science and girls advancing in reading.
Representation of women worldwideEdit
UNESCO, among other agencies including the European Commission and The Association of Academies and Societies of Sciences in Asia (AASSA), have been outspoken about the underrepresentation of women in STEM fields globally.
Despite their efforts to compile and interpret comparative statistics, it is necessary to exercise caution. Ann Hibner Koblitz has commented on the obstacles regarding the making of meaningful statistical comparisons between countries:
For a variety of reasons, it is difficult to obtain reliable data on international comparisons of women in STEM fields. Aggregate figures do not tell us much, especially since terminology describing educational levels, content of majors, job categories, and other markers varies from country to country.
Even when different countries use the same definitions of terms, the social significance of the categories may differ considerably. Koblitz remarks:
It is not possible to use the same indicators to determine the situation in every country. The significant statistic might be the percentage of women teaching at the university level. But it might also be the proportion of women at research institutes and academies of sciences (and at what level), or the percentage of women who publish (or who publish in foreign as opposed to domestic journals), or the proportion of women who go abroad for conferences, post-graduate study, and so on, or the percentage of women awarded grants by national and international funding agencies. Indices can have different meanings in different countries, and the prestige of various positions and honors can vary considerably.
A fact sheet published by UNESCO in March 2015 presented worldwide statistics of women in the STEM fields, with a focus on Asia and the Pacific region. It reports that, worldwide, 30 percent of researchers are women. In these areas, East Asia, the Pacific, South Asia and West Asia had the most uneven balance, with 20 percent of researchers being women in each of those sub-regions. Meanwhile, Central Asia had the most equal balance in the region, with women comprising 46 percent of its researchers. The Central Asian countries Azerbaijan and Kazakhstan were the only countries in Asia with women as the majority of their researchers, though in both cases it was by a very small margin.
|Countries||Percentage of researchers who are female|
|South and West Asia||20%|
|East Asia and the Pacific||20%|
As of 2004, 13.9% of students enrolled in science programs in Cambodia were female and 21% of researchers in science, technology, and innovation fields were female as of 2002. These statistics are significantly lower than those of other Asian countries such as Malaysia, Mongolia, and South Korea. According to a UNESCO report on women in STEM in Asian countries, Cambodia's education system has a long history of male dominance stemming from its male-only Buddhist teaching practices. Starting in 1924, girls were allowed to enroll in school. Bias against women, not only in education but in other aspects of life as well, exists in the form of traditional views of men as more powerful and dignified than women, especially in the home and in the workplace, according to UNESCO's A Complex Formula.
UNESCO's A Complex Formula states that Indonesia's government has been working towards gender equality, especially through the Ministry of Education and Culture, but stereotypes about women's roles in the workplace persists. Due to traditional views and societal norms, women struggle to remain in their careers or to move up in the workplace. Substantially more women are enrolled in science-based fields such as pharmacy and biology than in mathematics and physics. Within engineering, statistics vary based on the specific engineering discipline; women make up 78% of chemical engineering students but only 5% of mechanical engineering students. As of 2005, out of 35,564 researchers in science, technology, and engineering, only 10,874 or 31% were female.
According to UNESCO, 48.19% of students enrolled in science programs in Malaysia were female as of 2011. This number has grown significantly in the past three decades, during which the country's employment of women has increased by 95%. In Malaysia, over 50% of employees in the computer industry, which is generally a male-dominated field within STEM, are women. Of students enrolled in pharmacy, more than 70% are female, while in engineering only 36% of students are female. Women held 49% of research positions in science, technology, and innovation as of 2011.
According to UNESCO's data from 2012 and 2011 respectively, 40.2% of students enrolled in science programs and 49% of researchers in science, technology, and innovation in Mongolia are female. Traditionally, nomadic Mongol culture was fairly egalitarian, with both women and men raising children, tending livestock, and fighting in battle, which mirrors the relative equality of women and men in Mongolia's modern-day workforce. More females than males pursue higher education and 65% of college graduates in Mongolia are women. However, women earn about 19–30% less than their male counterparts and are perceived by society to be less suited to engineering than men. Thirty percent or less of employees in computer science, construction architecture, and engineering are female while three in four biology students are female.
As of 2011, 26.17% of Nepal's science students were women and 19% of their engineering students were also women. In research, women held 7.8% of positions in 2010. These low percentages correspond with Nepal's patriarchal societal values. In Nepal, women that enter STEM fields most often enter forestry or medicine, specifically nursing, which is perceived as a predominantly female occupation in most countries.
In 2012, 30.63% of students enrolled in science programs in South Korea were female, a number that has been increasing since the digital revolution. Numbers of male and female students enrolled at most levels of education are comparable as well, though the gender difference is larger in higher education. Confucian beliefs in the lower societal value of women as well as other cultural factors could influence South Korea's STEM gender gap. In South Korea, as in other countries, the percentage of women in medicine (61.6%) is much higher than the percentage of women in engineering (15.4%) and other more math-based stem fields. In research occupations in science, technology, and innovation, women made up 17% of the workforce as of 2011. In South Korea, most women working in STEM fields are classified as "non-regular" or temporary employees, indicating poor job stability. In a study conducted by the University of Glasgow which examined math anxiety and test performance of boys and girls from various countries, researchers found that South Korea had a high sex difference in mathematics scores, with female students scoring significantly lower than and experiencing more math anxiety on math tests than male students.
Ann Hibner Koblitz reported on a series of interviews conducted in 2015 in Abu Dhabi with women engineers and computer scientists who had come to the United Arab Emirates and other Gulf states to find opportunities that were not available to them in their home country. The women spoke of a remarkably high level of job satisfaction and relatively little discrimination. Koblitz comments that
...most people in most countries outside of the Middle East have no idea that the region, in particular the UAE, is a magnet for young, dynamic Arab women making successful careers for themselves in a variety of high-tech and other scientific fields; "land of opportunity," "a tech-person's paradise," and yes, even "mecca" were among the terms used to describe the UAE by the women I met.
In the European Union only 16.7% on average of ICT (Information and communication technology) specialists are women. Only in Romania and Bulgaria do women hold more that 25 percent of these roles. The gender distribution is more balanced, particularly in new member states when taking into account ICT technicians (middle and low-ranking positions).
In 2012 the percentage of women PhD graduates was 47.3% of the total, 51% of the social sciences, business and law, 42% of the science, mathematics and computing, and just the 28% of PhD graduates in engineering, manufacturing and construction. In the computing subfield only 21% of PhD graduates were women. In 2013 in the EU as an average men scientists and engineers made up 4.1% of total labour force, while women made up only 2.8%. In more than half of the countries women make up less than 45% of scientists and engineers. The situation has improved, as between 2008 and 2011 the number of women amongst employed scientists and engineers grew by an average of 11.1% per year, while the number of men grew only by 3.3% over the same period.
In 2018 European Commissioner for Digital Economy and Society Mariya Gabriel announced plans to increase the participation of women in the digital sector by challenging stereotypes; promoting digital skills and education and advocating for more women entrepreneurs.
According to the National Science Foundation, women comprise 43 percent of the U.S. workforce for scientists and engineers under 75 years old. For those under 29 years old, women comprise 56% of the science and engineering workforce. Of scientists and engineers seeking employment 50% under 75 are women, and 49% under 29 are women. About one in seven engineers are female.
Men are much more likely than women to have a STEM career regardless of educational attainment. Women in STEM fields earn considerably less than men, even after controlling for a wide set of characteristics such as education and age. On average, men in STEM jobs earn $36.34 per hour while women in STEM jobs earn $31.11 per hour.
|Bachelor's Degree Field||Men (%)||Women (%)|
|Computer and information sciences||3.1||1.0|
|Engineering/ engineering technologies||6.1||1.8|
|Biology/ biomedical sciences||2.3||3.5|
|Total graduates (%)||44.3||55.7|
|Total graduates (thousands)||6403.3||8062.5|
Women dominate the total number of persons with bachelor's degrees, as well as those in STEM fields defined by the National Center for Education Statistics. However, they are underrepresented in specific fields including Computer Sciences, Engineering, and Mathematics.
Although Asian women are over-represented in STEM fields in the U.S., African American, Hispanic, Pacific Islander, and Native American women are underrepresented, though not as much as men of the same ethnicity. Within academia, these minority women represent less than 1% of tenure-track positions in the top 100 U.S. universities despite constituting approximately 13% of total US population. A 2015 study suggested that attitudes towards hiring women in STEM tenure track positions has improved, with a 2:1 preference for women in STEM after adjusting for equal qualifications and lifestyles (e.g., single, married, divorced).
|American Indian/Alaska Native||0.32||0.46||0.27||0.44|
|Two or more races||0.97||1.15||1.11||1.19|
According to the National Household Survey, 39% of women graduates in Canada pursued a STEM field, however 66% in non-STEM fields. A study conducted by the University of British Columbia discovered that only 20–25% of computer science students from all Canadian college and universities are women. As well, only about 1 in 5 of that percentage will graduate from those programs.
Statistically, women are less likely to choose a STEM program, regardless of mathematical ability. Young men with lower marks in mathematics are more likely to pursue STEM fields than their women-identified peers with higher marks in mathematics.
In terms of the most prestigious awards in STEM fields, fewer have been awarded to women than to men. Between 1901 and 2017 the female:total ratio of Nobel Prizes were 2:207 for physics, 4:178 for chemistry, 12:214 for physiology/medicine, and 1:79 for economic sciences. The ratios for other fields were 14:114 in literature and 16:104 for peace. Maryam Mirzakhani was the first woman and first Iranian to receive the Fields Medal in 2014. The Fields Medal, is one of the most prestigious prize in mathematics, and has been awarded 56 times in total.
Fewer female students participate in prestigious STEM-related competitions such as the International Mathematical Olympiad. In 2017, only 10% of the IMO participants were female and there was one female on the South Korean winning team of six.
Recent advances in technologyEdit
Abbiss states that "the ubiquity of computers in everyday life has seen the breaking down of gender distinctions in preferences for and the use of different applications, particularly in the use of the internet and email." Both genders have acquired skills, competencies and confidence in using a variety of technological, mobile and application tools for personal, educational and professional use at high school level, but the gap still remains when it comes to enrollment of girls in computer science classes, which declines from grades 10 to 12. For higher education programs in information and communications technology, women make up only 3% of graduates globally.
A review of UK patent applications, in 2016, found that the proportion of new inventions registered by women was rising, but that most female inventors were active in stereotypically female fields such as "designing bras and make-up". 94% of inventions in the field of computing, 96% in automotive applications and mining, and 99% in explosives and munitions, were by men. In 2016 Russia had the highest percentage of patents filed by women, at about 16%.
Explanations for low representation of womenEdit
There are a variety of proposed reasons for the relatively low numbers of women in STEM fields. These can be broadly classified into societal, psychological, and innate explanations. However, explanations are not necessarily restricted to just one of these categories.
Schiebinger claims discrimination, both overt and covert, faced by women in STEM fields leads to fewer women in STEM fields.:33 In the 1980s, researchers demonstrated a general evaluative bias against women.
In a 2012 study, email requests were sent to meet to professors in doctoral programs at the top 260 U.S. universities. It was impossible to determine whether any particular individual in this study was exhibiting discrimination, since each participant only viewed a request from one potential graduate student. However, researchers found evidence for discrimination against ethnic minorities and women relative to Caucasian men. In another study, science faculty were sent the materials of student who was applying for a lab manager position at their university. The materials were the same for each participant, but each application was randomly assigned either a male or a female name. The researchers found that faculty members rated the male candidates as both more competent and more hirable than the females candidate, despite applications being otherwise identical. If individuals are given information about a prospective student's gender, they may infer that he or she possesses traits consistent with stereotypes for that gender. A study in 2014 found that men are favored in some domains, such as tenure rates in biology, but that the majority of domains were gender-fair. The authors interpreted this to suggest that the underrepresentation of women in the professorial ranks was not solely caused by sexist hiring, promotion, and remuneration.
Stereotypes about what someone in a STEM field should look and act like may cause established members of these fields to overlook individuals who are highly competent. The stereotypical scientist or individual in another STEM profession is usually thought to be male. Women in STEM fields may not fit individuals' conception of what a scientist, engineer, or mathematician "should" look like and may thus be overlooked or penalized. The Role Congruity Theory of Prejudice states that perceived incongruity between gender and a particular role or occupation can result in negative evaluations. In addition, negative stereotypes about women's quantitative abilities may lead people to devalue their work or discourage these women from continuing in STEM fields.
Both men and women who work in "nontraditional" occupations may encounter discrimination, but the forms and consequences of this discrimination are different. Individuals of a particular gender are often perceived to be better suited to particular careers or areas of study than those of the other gender. A study found that job advertisements for male-dominated careers tended to use more agentic words (or words denoting agency, such as "leader" and "goal-oriented") associated with male stereotypes. Social Role Theory, proposed in 1991, states that men are expected to display agentic qualities and women to display communal qualities. These expectations can influence hiring decisions. A 2009 study found that women tended to be described in more communal terms and men in more agentic terms in letters of recommendation. These researchers also found that communal characteristics were negatively related to hiring decisions in academia.
Although women entering traditionally male professions face negative stereotypes suggesting that they are not "real" women, these stereotypes do not seem to deter women to the same degree that similar stereotypes may deter men from pursuing nontraditional professions. There is historical evidence that women flock to male-identified occupations once opportunities are available. On the other hand, examples of occupations changing from predominantly female to predominantly male are very rare in human history. The few existing cases—such as medicine—suggest that redefinition of the occupations as appropriately masculine is necessary before men will consider joining them.
Although men in female-dominated occupations may contend with negative stereotypes about their masculinity, they may also experience certain benefits. In 1992 it was suggested that women in male-dominated occupations tended to hit a glass ceiling; while men in female-dominated occupations may hit a "glass escalator". While the glass ceiling can make it difficult for women and minorities to reach the top of an occupation, the "glass escalator" allows men to excel in a profession that is female dominated.
Black Sheep effectEdit
The Black Sheep effect occurs when individuals are likely to evaluate members of their in-group more favorably than members of their out-group when those members are highly qualified. However, when an individual's in-group members have average or below average qualities, he or she is likely to evaluate them much lower than out-group members with equivalent qualifications. This suggests that established women in STEM fields will be more likely than established men to help early career women who display sufficient qualifications. However, established women will be less likely then men to help early career women who display insufficient qualifications.
Queen Bee effectEdit
The Queen Bee effect is similar to the Black Sheep effect but applies only to women. It explains why higher-status women, particularly in male-dominated professions, may actually be far less likely to help other women than their male colleagues might be. A 2004 study found that while doctoral students in a number of different disciplines did not exhibit any gender differences in work commitment or work satisfaction, faculty members at the same university believed that female students were less committed to their work than male students. What was particularly surprising was that these beliefs by faculty members were most strongly endorsed by female faculty members, rather than male faculty members. One potential explanation for this finding is that individual mobility for a member of a negatively stereotyped group is often accompanied by a social and psychological distancing of oneself from the group. This implies that successful women in traditionally male-dominated careers do not see their success as evidence that negative stereotypes about women's quantitative and analytical abilities are wrong, but rather as proof that they personally are exceptions to the rule. Thus, such women may actually play a role in perpetuating, rather than abolishing, these negative stereotypes.
In STEM fields, the support and encouragement of a mentor can make a lot of difference in women's decisions of whether or not to continue pursuing a career in their discipline This may be particularly true for younger individuals who may face many obstacles early on in their careers. Since these younger individuals often look to those who are more established in their discipline for help and guidance, the responsiveness and helpfulness of potential mentors is incredibly important.
Lack of supportEdit
Women in STEM may leave due to not being invited to professional meetings, the use of sexually discriminating standards against women, inflexible working conditions, the perceived need to hide pregnancies, and the struggle to balance family and work. Women in STEM fields that have children either need child care or to take a long leave of absence. When a nuclear family can not afford child care, typically it is the mother that gives up her career to stay at home with the children. This is due in part to women being paid statistically less in their careers. The man makes more money so the man goes to work and the woman gives up her career. Maternity leave is another issue women in STEM fields face. In the U.S. maternity leave is required by The Family and Medical Leave Act of 1993 (FMLA). The FMLA requires 12 weeks of unpaid leave annually for mothers of newborn or newly adopted children. This is one of the lowest levels of leave in the industrialized world. Unlike the United States, most countries have the right to paid time off. If a new mother does not have external financial support or savings, they may not be able to take their full maternity leave. Few companies allow men to take paternity leave and it may be shorter than women's maternity leave. Longer paternity leaves for men could allow women to go back to work while their partners stay home with the children.
Lack of role modelsEdit
In engineering and science education, women made up almost 50 percent of non-tenure track lecturer and instructor jobs, but only 10 percent of tenured or tenure-track professors in 1996. In addition, the number of female department chairs in medical schools did not change from 1976 to 1996. Moreover, women who do make it to tenured or tenure-track positions may face the difficulties associated with holding a token status. They may lack support from colleagues and may face antagonism from peers and supervisors. However, in 2014 a team of psychologists and economists conducted extensive analyses of national data and concluded that the state of women in STEM has changed greatly in the past two decades and any conclusions about their status based on data prior to 2000 are likely to be outdated. In general, they concluded that women had very sizable gains in academic science, including remuneration, promotion, and job satisfaction.
Although it has been posited that more female role models would encourage more women to enter fields dominated by men, research has indicated this is not the case, and that women's lack of interest in STEM fields may instead in part stem from stereotypes about employees and workplaces in STEM fields, to which stereotypes women are disproportionately responsive.
Clustering and leaky pipelineEdit
In the early 1980s Rossiter put forth the concept of "territorial segregation" or occupational segregation, which is the idea that women "cluster" in certain fields of study.:34 For example, "women are more likely to teach and do research in the humanities and social sciences than in the natural sciences and engineering",:34 and the majority of college women tend to choose majors such as psychology, education, English, performing arts, and nursing.
Rossiter also used "hierarchical segregation" as an explanation for the low number of women in STEM fields.[clarification needed] She describes "hierarchical segregation" as a decrease in the number of women as one "moves up the ladder of power and prestige.":33 This is related to the leaky STEM pipeline concept. The metaphor of the leaky pipeline has been used to describe how women drop out of STEM fields at all stages of their careers. In the U.S., out of 2,000 high school aged persons, 1944 were enrolled in high school fall 2014. Assuming equal enrollment for boys and girls, 60 boys and 62 girls are considered "gifted." By comparing enrollment to the population of persons 20–24 years old, 880 of the 1000 original women, and 654 of the original 1000 men will enroll in college (2014). In freshmen year 330 women and 320 men will express an intent to study science or engineering. Of these only 142 women and 135 men will actually obtain a bachelor's degree in science or engineering, and only 7 women and 10 men will obtain a PhD in science or engineering.
Lack of interestEdit
A meta-analysis concluded that men prefer working with things and women prefer working with people. When interests were classified by RIASEC type (Realistic, Investigative, Artistic, Social, Enterprising, Conventional), men showed stronger Realistic and Investigative interests, and women showed stronger Artistic, Social, and Conventional interests. Sex differences favoring men were also found for more specific measures of engineering, science, and mathematics interests.
In a 3-year interview study, Seymour and Hewitt (1997) found that perceptions that non-STEM academic majors offered better education options and better matched their interests was the most common (46%) reason provided by female students for switching majors from STEM areas to non-STEM areas. The second most frequently cited reason given for switching to non-STEM areas was a reported loss of interest in the women's chosen STEM majors. Additionally, 38% of female students who remained in STEM majors expressed concerns that there were other academic areas that might be a better fit for their interests. Preston's (2004) survey of 1,688 individuals who had left sciences also showed that 30 percent of the women endorsed "other fields more interesting" as their reason for leaving.
Advanced math skills do not often result in a woman being interested in a STEM career. A Statistics Canada survey found that even young women of high mathematical ability are much less likely to enter a STEM field than young men of similar or even lesser ability.
Lack of confidenceEdit
Research has found that women steer away from STEM fields because they believe they are not qualified for them; the study suggested that this could be fixed by encouraging girls to participate in more mathematics classes. One of the factors behind girls' lack of confidence might be unqualified or ineffective teachers. Teachers' gendered perceptions on their students' capabilities can create an unbalanced learning environment and deter girls from pursuing further STEM education. They can also pass these stereotyped beliefs unto their students. Studies have also shown that student-teacher interactions affect girls' engagement with STEM. Teachers often give boys more opportunity to figure out the solution to a problem by themselves while telling the girls to follow the rules.:56 Teachers are also more likely to accept questions from boys while telling girls to wait for their turns. This is partly due to gender expectations that boys will be active but that girls will be quiet and obedient. Prior to 1985, girls were provided fewer laboratory opportunities than boys. In middle and high school, science, mathematics, mechanics and computers courses are mainly taken by male students and also tend to be taught by male teachers. A lack of opportunities in STEM fields could lead to a loss of self-esteem in math and science abilities, and low self-esteem could prevent people from entering science and math fields.
Out of STEM-intending students, 35% of women stated that their reason for leaving calculus was due to lack of understanding the material, while only 14% of men stated the same. The study reports that this difference in reason for leaving calculus is thought to develop from women's low level of confidence in their ability, and not actual skill. This study continues to establish that women and men have different levels of confidence in their ability and that confidence is related to how individual's performance in STEM fields. It was seen in another study that when men and women of equal math ability were asked to rate their own ability, women will rate their own ability at a much lower level. Programs with the purpose to reduce anxiety in math or increase confidence have a positive impact on women continuing their pursuit of a career in the STEM field.
Not only can the issue of confidence keep women from even entering STEM fields, but even women in upper-level courses with higher skill are more strongly affected by the stereotype that they (by nature) do not possess innate ability to succeed. This can cause a negative effect on confidence for women despite making it through courses designed to filter students out of the field.
Stereotype threat arises from the fear that one's actions will confirm a negative stereotype about one's in-group. This fear creates additional stress, consuming valuable cognitive resources and lowering task performance in the threatened domain. Individuals are susceptible to stereotype threat whenever they are assessed in a domain for which there is a perceived negative stereotype about a group to which they belong. Stereotype threat undermines the academic performance of women and girls in math and science, which leads to an underestimation of abilities in these subjects by standard measures of academic achievement. Individuals who identify strongly with a certain area (e.g., math) are more likely to have their performance in that area hampered by stereotype threat than those who identify less strongly with the area. This means that even highly motivated students from negatively stereotyped groups are likely to be adversely affected by stereotype threat and thus may come to disengage from the stereotyped domain. Negative stereotypes about girls’ capabilities in mathematics and science drastically lower their performance in mathematics and science courses as well as their interest in pursuing a STEM career. Studies have found that gender differences in performance disappear if students are told that there are no gender differences on a particular mathematics test. This indicates that the learning environment can greatly impact success in a course.
Stereotype threat has been criticized on a theoretical basis. Several attempts to replicate its experimental evidence have failed. The findings in support of the concept have been suggested to be the product of publication bias.
A study was done to determine how stereotype threat and math identification can affect women who were majoring in a STEM related field. There were three different situations, designed to test the impact of stereotype on performance in math. One group of women were informed that men had previously out-performed women on the same calculus test they were about to take. The next group was told men and women had performed at the same level. The last group was told nothing about how men had performed and there was no mention of gender before taking their test. Out of these situations, women performed at their best scores when there was no mention of gender. The worst scores were from the situation where women were told that men had performed better than women. For women to pursue the male-dominated field of STEM, previous research shows that they must have more confidence in math/science ability.
Innate versus learned skillEdit
Some studies propose the explanation that STEM fields (and especially fields like physics, math and philosophy) are considered by both teachers and students to require more innate talent than skills that can be learned. Combined with a tendency to view women as having less of the required innate abilities, researchers propose this can result in assessing women as less qualified for STEM positions. In a study done by Ellis, Fosdick and Rasmussen, it was concluded that without strong skills in calculus, women cannot perform as well as their male counterparts in any field of STEM, which leads to the fewer women pursuing a career in these fields. A high percentage of women that do pursue a career in STEM do not continue on this pathway after taking Calculus I, which was found to be a class that weeds out students from the STEM pathway.
There have been several controversial statements about innate ability and success in STEM. A few notable examples include Lawrence Summers, former president of Harvard University who suggested cognitive ability at high end positions could cause a population difference. Summers later stepped down as president. Former Google engineer, James Damore, wrote a memo entitled Google's Ideological Echo Chamber suggesting that differences in trait distributions between men and women was a reason for gender imbalance in STEM. The memo stated that affirmative action to reduce the gap could discriminate against highly qualified male candidates. Damore was fired for sending out this memo.
Strategies for increasing representation of womenEdit
There are a multitude of factors that may explain the low representation of women in STEM careers. Anne-Marie Slaughter, the first woman to hold the position of Director of Policy Planning for the United States Department of State, has recently suggested some strategies to the corporate and political environment to support women to fulfill to the best of their abilities the many roles and responsibilities that they undertake. The academic and research environment for women may benefit by applying some of the suggestions she has made to help women excel, while maintaining a work-life balance.
A number of researchers have tested interventions to alleviate stereotype threat for women in situations where their math and science skills are being evaluated. The hope is that by combating stereotype threat, these interventions will boost women's performance, encouraging a greater number of them to persist in STEM careers.
One simple intervention is simply educating individuals about the existence of stereotype threat. Researchers found that women who were taught about stereotype threat and how it could negatively impact women's performance in math performed as well as men on a math test, even when stereotype threat was induced. These women also performed better than women who were not taught about stereotype threat before they took the math test.
One of the proposed methods for alleviating stereotype threat is through introducing role models. One study found that women who took a math test that was administered by a female experimenter did not suffer a drop in performance when compared to women whose test was administered by a male experimenter. Additionally, these researchers found that it was not the physical presence of the female experimenter but rather learning about her apparent competence in math that buffered participants against stereotype threat. The findings of another study suggest that role models do not necessarily have to be individuals with authority or high status, but can also be drawn from peer groups. This study found that girls in same-gender groups performed better on a task that measured math skills than girls in mixed-gender groups. This was due to the fact that girls in the same-gender groups had greater access to positive role models, in the form of their female classmates who excelled in math, than girls in mixed-gender groups. Similarly, another experiment showed that making groups achievements salient helped buffer women against stereotype threat. Female participants who read about successful women, even though these successes were not directly related to performance in math, performed better on a subsequent math test than participants who read about successful corporations rather than successful women. A study investigating the role of textbook images on science performance found that women demonstrated better comprehension of a passage from a chemistry lesson when the text was accompanied by a counter-stereotypic image (i.e., of a female scientist) than when the text was accompanied by a stereotypic image (i.e., of a male scientist). Other scholars distinguish between the challenges of both recruitment and retention in increasing women's participation in STEM fields. These researchers suggest that although both female and male role models can be effective in recruiting women to STEM fields, female role models are more effective at promoting the retention of women in these fields. Female teachers can also act as role models for young girls. Reports have shown that the presence of female teachers positively influences girls' perceptions of STEM and increases their interest in STEM careers.
Researchers have investigated the usefulness of self-affirmation in alleviating stereotype threat. One study found that women who affirmed a personal value prior to experiencing stereotype threat performed as well on a math test as men and as women who did not experience stereotype threat. A subsequent study found that a short writing exercise in which college students, who were enrolled in an introductory physics course, wrote about their most important values substantially decreased the gender performance gap and boosted women's grades. Scholars believe that the effectiveness of such values-affirmation exercises is their ability to help individuals view themselves as complex individuals, rather than through the lens of a harmful stereotype. Supporting this hypothesis, another study found that women who were encouraged to draw self-concept maps with many nodes did not experience a performance decrease on a math test. However, women who did not draw self-concept maps or only drew maps with a few nodes did perform significantly worse than men on the math test. The effect of these maps with many nodes was to remind women of their "multiple roles and identities," that were unrelated to, and would thus not be harmed by, their performance on the math test.
Organizations such as Girls Who Code, StemBox, Blossom, Engineer Girl, Girls Can Code in Afghanistan, @IndianGirlsCode, and Kode with Klossy (spearheaded by supermodel Karlie Kloss) aim to encourage women and girls to explore male-dominated STEM fields. Many of these organizations offer summer programs and scholarships to girls interested in STEM fields. The U.S. government has funded similar endeavors; the Department of State's Bureau of Educational and Cultural Affairs created TechGirls and TechWomen, exchange programs which teach Middle Eastern and North African girls and women skills valuable in STEM fields and encourage them to pursue STEM careers. There is also the TeachHer Initiative, spearheaded by UNESCO, Costa Rican First Lady, Mercedes Peñas Domingo, and Dr. Jill Biden which aims to close the gender gap in STEAM curricula and careers. The Initiative also emphasizes the importance of after school activities and clubs for girls.
Current campaigns to increase women's participation within STEM fields include the UK's WISE as well as mentoring programs, such as the Million Women Mentors initiative connecting girls and young women with STEM mentors and Verizon's #InspireHerMind project. The US Office of Science and Technology Policy during the Obama administration collaborated with the White House Council on Women and Girls to increase the participation of women and girls within STEM fields along with the "Educate to Innovate" campaign.
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- Sex and intelligence
- Women in science
- Association for Women in Science
- Association for Women in Mathematics
- Stereotype threat
- Pygmalion effect
- Black sheep effect
- Beyond Bias and Barriers
- Implicit stereotypes
- Glass ceiling
- Inequality in the workplace
- STEM fields
- Heuristics in judgment and decision making
- Category:Organizations for women in science and technology
- Margaret W. Rossiter History of Women in Science Prize
- Matilda effect
- Gürer, Denise and Camp, Tracy (2001). Investigating the Incredible Shrinking Pipeline for Women in Computer Science. Final Report – NSF Project 9812016.
- Ceci, S.J.; Williams, W.M. (2010). "Sex Differences in Math-Intensive fields". Current Directions in Psychological Science. 19 (5): 275–279. doi:10.1177/0963721410383241. PMC .
- Ceci, S.J.; Williams, W.M.; Barnett, S.M. (2009). "Women's underrepresentation in science: Sociocultural and biological considerations". Psychological Bulletin. 135 (2): 218–261. doi:10.1037/a0014412. PMID 19254079.
- Diekman, A.B.; Brown, E.R.; Johnston, A.M.; Clark, E.K. (2010). "Seeking Congruity Between Goals and Roles". Psychological Science. 21 (8): 1051–1057. doi:10.1177/0956797610377342. PMID 20631322.
- Griffith, A.L. (2010). "Persistence of women and minorities in STEM field majors: Is it the school that matters?". Economics of Education Review. 29 (6): 911–922. doi:10.1016/j.econedurev.2010.06.010.
- Catherine André/VoxEurop/EDJNet; Marzia Bona/OBC Transeuropa/EDJNet (19 April 2018). "The ICT sector is booming. But are women missing out?". Retrieved 27 August 2018.
- S.L. Hanson, "Lost Talent, Women in the Sciences", Philadelphia, PA.: Temple University Press, 1996.
- Pajares, F (1996). "Self-efficacy beliefs and mathematical problem-solving of gifted students". Contemporary Educational Psychology. 21 (4): 325–44. doi:10.1006/ceps.1996.0025.
- Hill, Catherine, and Christianne Corbett. Why so Few? Women in Science, Technology, Engineering, and Mathematics. Washington, D.C.: AAUW, 2010.
- Sorby, S. A. (2009). "Educational research in developing 3-D spatial skills for engineering students". International Journal of Science Education. 31 (3): 459–80. doi:10.1080/09500690802595839.
- "Stem Talent Girl: to empower girls and women to ensure they develop their talent". 2017.
- Higher Education Research Institute, Graduate School of Education and Information Studies, The American Freshman: National Norms for Fall 1996, University of California, Los Angeles, 1996.
- Tapping All our Talents, United Kingdom: The Royal Society of Edinburgh, April 2012, ISBN 9780902198661, retrieved 4 March 2015
- National Science Foundation, Women, Minorities and Persons with Disabilities in Science and Engineering: 1996, Washington, D.C.: 1996, appendix table 5-8.
- "Women in STEM in Australia" (PDF). Professionals Australia.
- "TABLE 7-3. Doctoral degrees awarded to men, by field: 2004–14". National Science Foundation. Retrieved 19 Nov 2017.
- "Table 318.30. Bachelor's, master's, and doctor's degrees conferred by postsecondary institutions, by sex of student and discipline division: 2014–15". National Center for Education Statistics. Retrieved 25 Nov 2017.
- Dee, Thomas S. "Teachers and the Gender Gaps in Student Achievement." The Journal of Human Resources, vol. 42, no. 3, 2007, pp. 528–554. JSTOR 40057317
- "A Complex Formula: Girls and Women in Science, Technology, Engineering and Mathematics in Asia" (PDF). UNESCO. UNESCO Bangkok Office. 2015. Retrieved 29 October 2016.
- "She figures 2012 – Research policy and organisation – EU Bookshop". doi:10.2777/38520.
- "Women in Science and Technology in Asia". The InterAcademy Partnership. AASSA, Gyeonggi-Do. 1 September 2015. Retrieved 29 October 2016.
- Ann Hibner Koblitz, "Life in the fast lane: Arab women in science and technology," Bulletin of Science, Technology & Society, vol. 36, no. 2 (2016), p. 107–117.
- Ann Hibner Koblitz, "Mathematics and gender: Some cross-cultural observations," in Gila Hanna, ed., Towards Gender Equity in Mathematics Education: An ICMI Study, Kluwer Academic Publishers, 1996, p. 99.
- "Women in Science" (PDF). UNESCO.
- Stoet, Gijsbert; Bailey, Drew H.; Moore, Alex M.; Geary, David C. (2016-04-21). "Countries with Higher Levels of Gender Equality Show Larger National Sex Differences in Mathematics Anxiety and Relatively Lower Parental Mathematics Valuation for Girls". PLOS One. 11 (4): e0153857. doi:10.1371/journal.pone.0153857. ISSN 1932-6203. PMC . PMID 27100631.
- She Figures 2015 (PDF) (Report). European Commission. 2016. doi:10.2777/744106. ISBN 978-92-79-48375-2. Retrieved 28 August 2018.
- "Cracking the code: girls' and women's education in science, technology, engineering and mathematics (STEM)" (PDF). www.unesco.org. Retrieved 28 April 2018.
- "More women in the Digital sector: a key to Europe's successful digital future". Digital Single Market. European Commission. 6 March 2018. Retrieved 27 August 2018.
- "Table 9-9. Employment status of scientists and engineers, by age, sex, ethnicity, race, and disability status". National Science Foundation. 2015. Retrieved 19 Nov 2017.
- Beede, David, Tiffany Julian, David Langdon, George McKittrick, Beethika Khan, and Mark Doms. U.S. Department of Commerce Economics and Statistics Administrations. www.esa.doc.gov. "Women in STEM: A Gender Gap to Innovation", 2009.
- "Number of persons 25 to 34 years old and percentage with a bachelor's or higher degree, by undergraduate field of study, sex, race/ethnicity, and U.S. nativity and citizenship status: 2014". National Center for Education Statistics. December 2015. Retrieved 18 Nov 2017.
- Towns, Marcy (Spring 2010). "Where Are the Women of Color? Data on African American, Hispanic, and Native American Faculty in STEM" (PDF). National Science Teachers Association.
- Williams, Wendy M.; Ceci, Stephen J. (2015). "National hiring experiments reveal 2:1 faculty preference for women on STEM tenure track". Proceedings of the National Academy of Sciences. 112 (17): 5360–5365. doi:10.1073/pnas.1418878112. ISSN 0027-8424. PMC .
- Hango, Darcy (2015). "Gender differences in science, technology, engineering, mathematics and computer science (STEM) programs at university". statcan.
- "Unlocking the brilliance: author provides insights on how to inspire young women to join the high tech industry". link.galegroup.com. Retrieved 2018-03-18.
- Darcy Hango (18 Dec 2013). "Gender differences in science, technology, engineering, mathematics and computer science (STEM) programs at university". Retrieved 18 March 2018.
- "Nobel Prize Facts". NobelPrize.org. Retrieved 18 Nov 2017.
- "The Work of Maryam Mirzakhani. Press Release" (PDF). International Mathematical Union. Retrieved 30 September 2014.
- UNESCO (2015). A Complex Formula: Girls and Women in Science, Technology, Engineering and Mathematics in Asia (PDF). Paris, UNESCO. pp. 15, 23–24. ISBN 978-92-9223-492-8.
- "International Mathematical Olympiad Timeline". International Mathematical Olympiad. Retrieved 18 Nov 2017.
- "Korea Takes 1st Place at International Math Olympiad". Korea Daily. 25 Jul 2017. Retrieved 18 Nov 2017.
- Abbiss, Jane (2011). "Boys and Machines" (PDF). Gender and Education. 23 (5): 601–617. doi:10.1080/09540253.2010.549108.
- Organization., International Labour (2016). Women at Work : Trends 2016. Geneva: ILO. ISBN 9789221307969. OCLC 958384912.
- Keate, Georgie (27 December 2016). "New generation of inventors wanted: women need to apply". The Times. pp. 22–23.
- Schiebinger, Londa (1999). Has Feminism Changed Science?. Harvard University Press.
- Swim, J.; Borgida, E.; Maruyama, G.; Myers, D.G. (1989). "Joan McKay versus John McKay: Do gender stereotypes bias evaluations?". Psychological Bulletin. 105 (3): 409–429. doi:10.1037/0033-2909.105.3.409.
- Milkman, K.L; Akinola, M.; Chugh, D. (2012). "Temporal Distance and Discrimination: An Audit Study in Academia". Psychological Science. 23 (7): 710–717. doi:10.1177/0956797611434539. PMID 22614463.
- Moss-Racusin, C.A.; Dovidio, J.F.; Brescoll, V.L.; Graham, M.; Handelsman, J. (2012). "Science faculty's subtle gender biases favor male students". Proceedings of the National Academy of Sciences. 109 (41): 16474–16479. doi:10.1073/pnas.1211286109. PMC . PMID 22988126.
- Deaux, K.; Lewis, L.L. (1984). "Structure of gender stereotypes: Interrelationships among components and gender label". Journal of Personality and Social Psychology. 46 (5): 991–1004. doi:10.1037/0022-35188.8.131.521.
- Ceci, S. J.; Ginther, D. K.; Kahn, S.; Williams, W. M. (2014). "Women in academic science: a changing landscape". Psychological Science in the Public Interest. 15 (3): 75–141. doi:10.1177/1529100614541236. PMID 26172066.
- Wells, Gary L. (1985). "The Conjunction Error and the Representativeness Heuristic". Social Cognition. 3 (3): 266–279. doi:10.1521/soco.19184.108.40.2066.
- Good, Jessica J.; Woodzicka, Julie A.; Wingfield, Lylan C. (2010). "The Effects of Gender Stereotypic and Counter-Stereotypic Textbook Images on Science Performance". Journal of Social Psychology. 150 (2): 132–147. doi:10.1080/00224540903366552.
- Eagly, A.H.; Karau, S.J. (2002). "Role congruity theory of prejudice toward female leaders". Psychological Review. 109 (3): 573–598. doi:10.1037/0033-295x.109.3.573. PMID 12088246.
- Garcia-Retamero, R.; Lopez-Zafra, E. (2006). "Prejudice against Women in Male-congenial Environments: Perceptions of Gender Role Congruity in Leadership". Sex Roles. 55 (1–2): 51–61. doi:10.1007/s11199-006-9068-1.
- Ritter, B.A.; Yoder, J.D. (2004). "Gender Differences in Leader Emergence Persist Even for Dominant Women: An Updated Confirmation of Role Congruity Theory". Psychology of Women Quarterly. 28 (3): 187–193. doi:10.1111/j.1471-6402.2004.00135.x.
- Miyake, A.; Kost-Smith, L.E.; Finkelstein, N.D.; Pollock, S.J.; Cohen, G.L.; Ito, T.A. (2010). "Reducing the Gender Achievement Gap in College Science: A Classroom Study of Values Affirmation". Science. 330 (6008): 1234–1237. doi:10.1126/science.1195996. PMID 21109670.
- Gaucher, D.; Friesen, J.; Kay, A.C. (2011). "Evidence that gendered wording in job advertisements exists and sustains gender inequality". Journal of Personality and Social Psychology. 101 (1): 109–128. doi:10.1037/a0022530. PMID 21381851.
- Lyness, K.S.; Heilman, M.E. (2006). "When fit is fundamental: Performance evaluations and promotions of upper-level female and male managers". Journal of Applied Psychology. 91 (4): 777–785. doi:10.1037/0021-9010.91.4.777. PMID 16834505.
- Eagly, A.H.; Wood, W. (1991). "Explaining Sex Differences in Social Behavior: A Meta-Analytic Perspective". Personality and Social Psychology Bulletin. 17 (3): 306–315. doi:10.1177/0146167291173011.
- Madera, J.M.; Hebl, M.R.; Martin, R.C. (2009). "Gender and letters of recommendation for academia: Agentic and communal differences". Journal of Applied Psychology. 94 (6): 1591–1599. doi:10.1037/a0016539.
- Cohn, Samuel. 1985. The Process of Occupational Sex-Typing. Philadelphia: Temple University Press.
- Ehrenreich, Barbara, and Deirdre English. 1978. For Her Own Good: 100 Years of Expert Advice to Women. Garden City, N.Y.: Anchor Press.
- Williams, Christine (1992). "The Glass Escalator: Hidden Advantages for Men in the 'Female' Professions". Social Problems. 39 (3): 253–267. doi:10.1525/sp.1992.39.3.03x0034h. JSTOR 3096961.
- Eidelman, S.; Biernat, M. (2003). "Derogating black sheep: Individual or group protection?". Journal of Experimental Social Psychology. 39 (6): 602–609. doi:10.1016/s0022-1031(03)00042-8.
- Kerr, N.L.; Hymes, R.W.; Anderson, A.B.; Weathers, J.E. (1995). "Defendant-juror similarity and mock juror judgments". Law and Human Behavior. 19 (6): 545–567. doi:10.1007/bf01499374.
- Marques, J.; Abrams, D.; Serodio, R.G. (2001). "Being better by being right: Subjective group dynamics and derogation of in-group deviants when generic norms are undermined". Journal of Personality and Social Psychology. 81 (3): 436–447. doi:10.1037/0022-35220.127.116.116.
- Taylor, T.S.; Hosch, H.M. (2004). "An examination of jury verdicts for evidence of a similarity-leniency effect, an out-group punitiveness effect or a black sheep effect". Law and Human Behavior. 28 (5): 587–598. doi:10.1023/b:lahu.0000046436.36228.71.
- Cooper, V.W. (1997). "Homophily or the Queen Bee Syndrome". Small Group Research. 28 (4): 483–499. doi:10.1177/1046496497284001.
- Ellemers, N.; Van den Heuvel, H.; de Gilder, D.; Maass, A.; Bonvini, A. (2004). "The underrepresentation of women in science: Differential commitment or the queen bee syndrome?". British Journal of Social Psychology. 43 (3): 315–338. doi:10.1348/0144666042037999. PMID 15479533.
- Sonnert, G.; Fox, M.F.; Adkins, K. (2007). "Undergraduate Women in Science and Engineering: Effects of Faculty, Fields, and Institutions Over Time". Social Science Quarterly. 88 (5): 1333–1356. doi:10.1111/j.1540-6237.2007.00505.x.
- Stout, J.G.; Dasgupta, N.; Hunsinger, M.; McManus, M.A. (2011). "STEMing the tide: Using ingroup experts to inoculate women's self-concept in science, technology, engineering, and mathematics (STEM)". Journal of Personality and Social Psychology. 100 (2): 255–270. doi:10.1037/a0021385. PMID 21142376.
- Welsh, Jennifier (16 Oct 2013). "These Are The 7 Things Keeping Women Out of Science Careers". Business Insider. Retrieved 25 Nov 2017.
- "Family and Medical Leave Act". United States Department of Labor. Retrieved 25 Nov 2017.
- "Paid Family Leave – Fathers". State of California, Employment Development Department. Retrieved 25 Nov 2017.
- Pell, A N (1996). "Fixing the leaky pipeline: women scientists in academia". Journal of Animal Science. 74 (11): 2843–8. doi:10.2527/1996.74112843x. ISSN 0021-8812. PMID 8923199.
- Lips, Hilary (2008). Sex & Gender: An Introduction Sixth Edition. New York: McGraw Hill.
- Ceci, Stephen J.; Ginther, Donna K.; Kahn, Shulamit; Williams, Wendy M. (2014). "Women in Academic Science, A Changing Landscape". Psychological Science in the Public Interest. 15 (3): 75–141. doi:10.1177/1529100614541236. ISSN 1529-1006.
- Cheryan, Sapna; Siy, John Oliver; Vichayapai, Marissa; Drury, Benjamin J.; Kim, Saenam. "Do Female and Male Role Models Who Embody STEM Stereotypes Hinder Women's Anticipated Success in STEM?". Social, Psychological, and Personality Science, via Sage Journals. Retrieved 27 July 2015.
- Page, Lewis (15 December 2009). "Ladies put off tech careers by sci-fi posters, Coke cans". Retrieved 27 July 2015.
- Page, Lewis (27 June 2013). "Trick-cyclist's claim: I have FOUND how to get GIRLS INTO TECH". Retrieved 27 July 2015.
- Ruchika Tulshyan. "Top 10 College Majors For Women – 10: Liberal Arts and Sciences, General Studies, Humanities". Forbes.com. Archived from the original on 2013-01-23. Retrieved 2013-03-07.
- "Table 201.20. Enrollment in grades 9 through 12 in public and private schools compared with population 14 to 17 years of age: Selected years, 1889–90 through fall 2015". National Center for Education Statistics. 2015. Retrieved 19 Nov 2017.
- "Table 204.90. Percentage of public school students enrolled in gifted and talented programs, by sex, race/ethnicity, and state: 2004, 2006, and 2011–12". National Center for Education Statistics. 2015. Retrieved 19 Nov 2017.
- "TABLE 1-1. Resident population of the United States, by age and sex: 2014". National Science Foundation. Retrieved 19 Nov 2017.
- "TABLE 2-1. Undergraduate enrollment at all institutions, by citizenship, ethnicity, race, sex, and enrollment status: 2004–14". National Science Foundation. Retrieved 19 Nov 2017.
- "TABLE 2-8. Intentions of freshmen to major in S&E fields, by race or ethnicity and sex: 2014". National Science Foundation. Retrieved 19 Nov 2017.
- "TABLE 5-1. Bachelor's degrees awarded, by sex and field: 2004–14". National Science Foundation. Retrieved 19 Nov 2017.
- "TABLE 7-2. Doctoral degrees awarded to women, by field: 2004–14". National Science Foundation. Retrieved 19 Nov 2017.
- Su, Rong; Rounds, James; Armstrong, Patrick (2009). "Men and Things, Women and People: A Meta-Analysis of Sex Differences in Interests". Psychological Bulletin. 135 (6): 859–884. doi:10.1037/a0017364. PMID 19883140.
- Seymour, Elaine (1997). Talking about leaving : why undergraduates leave the sciences. Boulder, CO, USA: Westview Press. ISBN 0-8133-6642-9.
- Preston, Anne (2004). Leaving science : occupational exit from scientific careers. New York: Russell Sage Foundation. ISBN 0-87154-694-9.
- Hango, Darcy (2013). "Ability in mathematics and science at age 15 and program choice in university: Differences by gender" (PDF). Tourism and Centre for Education Statistics Division. Statistics Canada. Retrieved 21 June 2018.
- Page, Lewis (27 July 2015). "New study into lack of women in Tech: It's NOT the men's fault". Retrieved 27 July 2015.
- Barbara, Lohbeck, Annette|Grube, Dietmar|Moschner, (2017). "Academic Self-Concept and Causal Attributions for Success and Failure Amongst Elementary School Children". International Journal of Early Years Education. 25 (2). ISSN 0966-9760.
- Keller, Carmen (2001-05-01). "Effect of Teachers' Stereotyping on Students' Stereotyping of Mathematics as a Male Domain". The Journal of social psychology. 141: 165–73. doi:10.1080/00224540109600544.
- Johnson, Angela C. (2007). "Unintended consequences: How science professors discourage women of color". Science Education. 91 (5): 805–821. doi:10.1002/sce.20208. ISSN 0036-8326.
- Elstad, Eyvind; Turmo, Are (2009-08-06). "The Influence of the Teacher's Sex on High School Students' Engagement and Achievement in Science". International Journal of Gender, Science and Technology. 1 (1). ISSN 2040-0748.
- "Cracking the code: girls' and women's education in science, technology, engineering and mathematics (STEM)" (PDF). www.unesco.org. Retrieved 28 April 2018.
- http://www.msnbc.msn.com/id/50056290/ns/local_news-phoenix_az/t/popovich-girls-need-be-shown-path-success-through-stem-education/#.UL2VYYNfCSo. Retrieved December 5, 2012. Missing or empty
- Ellis, Jessica; Fosdick, Bailey K.; Rasmussen, Chris (2016). "Women 1.5 Times More Likely to Leave STEM Pipeline after Calculus Compared to Men: Lack of Mathematical Confidence a Potential Culprit". PLOS One. 11 (7): 1–14. doi:10.1371/journal.pone.0157447. ISSN 1932-6203.
- Chipman, Susan (September 1992). "Mathematics Anxiety and Science Careers Among Able College Women". Psychological Science. 3 (5): 292–295.
- Kelly, Stephanie (October 2013). "For Girls in STEM, Belonging, Not Brain Structure, Makes the Difference". Techniques: Connecting Education & Careers. 88 (7): 34–36 – via EBSCO Academic Search Complete.
- Steinberg, Julia (November–December 2012). "Calculus GPA and Math Identification as Moderators of Stereotype Threat in Highly Persistent Women". Basic & Applied Social Psychology. 34 (6): 534–543 – via EBSCO Academic Search Complete.
- Schmader, T.; Johns, M. (2003). "Converging evidence that stereotype threat reduces working memory capacity". Journal of Personality and Social Psychology. 85 (3): 440–452. doi:10.1037/0022-3518.104.22.1680. PMID 14498781.
- 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. doi:10.1037/0022-3522.214.171.1247. PMID 7473032.
- Steele, C.M.; Spencer, S.J.; Aronson, J. (2002). "Contending with group image: The psychology of stereotype and social identity threat". Advances in Experimental Social Psychology. Advances in Experimental Social Psychology. 34: 379–440. doi:10.1016/s0065-2601(02)80009-0. ISBN 9780120152346.
- 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. doi:10.1006/jesp.1998.1373.
- Bork, Christine. "STEM Fields: Where Are the Women?". Huffington Post. Retrieved 25 Nov 2017.
- Arthur Robert Jensen "The g factor: the science of mental ability" 1998 ISBN 0-275-96103-6, Praeger Publishers, 88 Post Road West, Westport, CT 06881, pages 513–515: "the phenomenon of stereotype threat can be explained in terms of a more general construct, test anxiety, which has been studied since the early days of psychometrics. Test anxiety tends to lower performance levels on tests in proportion to the degree of complexity and the amount of mental effort they require of the subject. The relatively greater effect of test anxiety in the black samples, who had somewhat lower SAT scores, than the white subjects in the Stanford experiments constitutes an example of the Yerkes-Dodson law ... by conducting the same type of experiment using exclusively white (or black) subjects, divided into lower- and higher-ability groups, it might be shown that the phenomenon attributed to stereotype threat has nothing to do with race as such, but results from the interaction of ability level with test anxiety as a function of test complexity."
- Stoet, G.; Geary, D. C. (2012). "Can stereotype threat explain the gender gap in mathematics performance and achievement?". Review of General Psychology. 16: 93–102. doi:10.1037/a0026617. Pdf.
- Fryer, R. G.; Levitt, S. D.; List, J. A. (2008). "Exploring the Impact of Financial Incentives on Stereotype Threat: Evidence from a Pilot Study". American Economic Review. 98 (2): 370–375. doi:10.1257/aer.98.2.370.
- Yong, Ed (9 September 2016). "A Worrying Trend for Psychology's 'Simple Little Tricks'". The Atlantic. Retrieved 11 September 2016.
- Ganley, Colleen M.; Mingle, Leigh A.; Ryan, Allison M.; Ryan, Katherine; Vasilyeva, Marina; Perry, Michelle (1 January 2013). "An Examination of Stereotype Threat Effects on Girls' Mathematics Performance" (PDF). Developmental Psychology. 49 (10): 1886–1897. doi:10.1037/a0031412. PMID 23356523.
- Flore, Paulette C.; Wicherts, Jelte M. (2014). "Does stereotype threat influence performance of girls in stereotyped domains? A meta-analysis". Journal of School Psychology. 53 (1): 25–44. doi:10.1016/j.jsp.2014.10.002. ISSN 0022-4405. PMID 25636259.
- Miller, David (9 Jun 2015). "Beliefs about innate talent may dissuade students from STEM". The Conversation. Retrieved 25 Nov 2017.
- "Archive of: Remarks at NBER Conference on Diversifying the Science & Engineering Workforce". Archived from the original on January 30, 2008. Retrieved 2008-01-30.. January 14, 2005.
- Matsakis, Louise; Koebler, Jason; Emerson, Sarah (7 Aug 2017). "Here Are the Citations for the Anti-Diversity Manifesto Circulating at Google". Vice. Retrieved 25 Nov 2017.
- "Anne-Marie Slaughter". Princeton University.
- Finding a work-life-balance, Toronto Star, 11 July 2012
- Johns, Michael; Schmader, Toni; Martens, Andy (2005). "Knowing Is Half the Battle: Teaching Stereotype Threat as a Means of Improving Women's Math Performance". Psychological Science. 16 (3): 175–179. doi:10.1111/j.0956-7976.2005.00799.x. PMID 15733195.
- Marx, D.M.; Roman, J.S. (2002). "Female role models: Protecting women's math performance". Personality and Social bulletin. 28 (9): 1183–1193. doi:10.1177/01461672022812004.
- Huguet, P.; Regner, I. (2007). "Stereotype threat among schoolgirls in quasi-ordinary classroom circumstances". Journal of Educational Psychology. 99 (3): 545–560. doi:10.1037/0022-06126.96.36.1995.
- McIntyre, R.B.; Paulson, R.M.; Lord, C.G. (2003). "Alleviating women's mathematics stereotype threat through salience of group achievements". Journal of Experimental Social Psychology. 39 (1): 83–90. doi:10.1016/s0022-1031(02)00513-9.
- Drury, Benjamin J.; Siy, John Oliver; Cheryan, Sapna (2011). "When Do Female Role Models Benefit Women? The Importance of Differentiating Recruitment From Retention in STEM". Psychological Inquiry. 22 (4): 265–269. doi:10.1080/1047840x.2011.620935.
- "Cracking the code: girls' and women's education in science, technology, engineering and mathematics (STEM)" (PDF). www.unesco.org. Retrieved 28 April 2018.
- Stearns, Elizabeth; Bottía, Martha Cecilia; Davalos, Eleonora; Mickelson, Roslyn Arlin; Moller, Stephanie; Valentino, Lauren (2016-02-01). "Demographic Characteristics of High School Math and Science Teachers and Girls' Success in STEM". Social Problems. 63 (1): 87–110. doi:10.1093/socpro/spv027. ISSN 0037-7791.
- Martens, A.; Johns, M.; Greenberg, J.; Schimel, J. (2006). "Combating stereotype threat: The effect of self-affirmation on women's intellectual performance". Journal of Experimental Social Psychology. 42 (2): 236–243. doi:10.1016/j.jesp.2005.04.010.
- Miyake, A.; Kost-Smith, L.E.; Finkelstein, N.D.; Pollock, S.J.; Cohen, G.L.; Ito, T.A. (2010). "Reducing the Gender Achievement Gap in College Science: A Classroom Study of Values Affirmation". Science. 330 (6008): 1234–1237. doi:10.1126/science.1195996. PMID 21109670.
- Gresky, D.M.; Eyck, L.L.T.; Lord, C.G.; McIntyre, R.B. (2005). "Effects of salient multiple identities on women's performance under mathematics stereotype threat". Sex Roles. 53 (9–10): 703–716. doi:10.1007/s11199-005-7735-2.
- "Introducing StemBox, Birchbox's Super Smart Little Sister". Retrieved 2015-07-22.
- "Advancing the Status of Women and Girls Around the World". Retrieved 2016-09-25.
- WISE. "About us". Wisecampaign.org.uk. Retrieved 20 August 2017.
- "Million Women Mentors". Millionwomenmentors.org. Retrieved 31 August 2017.
- "Verizon Innovative Learning". Verizon.com. Retrieved 20 August 2017.
- "Women in STEM". Archived from the original on 14 May 2016. Retrieved 14 May 2016.
- "Women and Girls in Science, Technology, Engineering, and Math (STEM)" (PDF). Executive Office of the President - White House. Retrieved 2 March 2015.
- American Association of University Women (2010). Why So Few?
- Natarajan, Priyamvada, "Calculating Women" (review of Margot Lee Shetterly, Hidden Figures: The American Dream and the Untold Story of the Black Women Mathematicians Who Helped Win the Space Race, William Morrow; Dava Sobel, The Glass Universe: How the Ladies of the Harvard Observatory Took the Measure of the Stars, Viking; and Nathalia Holt, Rise of the Rocket Girls: The Women Who Propelled Us, from Missiles to the Moon to Mars, Little, Brown), The New York Review of Books, vol. LXIV, no. 9 (25 May 2017), pp. 38–39.