The findings that women are treated differently (in fields where they are underrepresented) are strong. Whether finding a job after undergraduate studies or becoming a full professor later on in their career, women seem to be evaluated by different standards than men - mostly to a disadvantage of the women. There are only very few studies that show an advantage of women over equally qualified men. Most papers in this section are based on audit studies. Audit studies are field experiments in which the researcher ("auditors") sends job applications to employers in which the resumes are matched on all characteristics except the one being tested for discrimination.
Audit study and survey experiment in the U.S. with 2,016 job applications in the audit study and 261 hiring decision-makers in the survey experiment. The researchers manipulated the grade point average, gender, and college major—English, math and business for the applicants and tested how this affected their chances to be invited for a job interview.
In the audit study, the grade point average matters little for men, while women benefit from moderate achievement but not high achievement. As a result, high-achieving men are called back significantly more often than high-achieving women—at a rate of nearly 2-to-1. In math, high-achieving women are especially penalized: High-achieving male math majors are called back three times as often as their female counterparts. Moderate-achieving women in math were called back more often than a high-achieving women.
The survey experiment suggests that these patterns are due to employers’ gendered standards for applicants. Employers value competence and commitment among men applicants but instead privilege women applicants who are perceived as likable. This standard helps moderate-achieving women, who are often described as sociable and outgoing but hurts high-achieving women, whose personalities are viewed with more skepticism. These findings suggest that achievement invokes gendered stereotypes that penalize women for having good grades and create unequal returns to academic performance at labor market entry.
A laboratory experiment in the U.S. testing negative sex-based stereotypes in mathematics with n=507 "picking decisions". In the experiment, subjects were “hired” to perform an arithmetic task: correctly summing as many sets of four two-digit numbers as possible over 4 min. The experiment has two steps: First, all subjects performed the task and were informed of the number of problems they solved correctly. Subsequently, two subjects were selected randomly to be "candidates"; the remaining ones were to act as “employers,” hiring one of the candidates from the pair to perform a second arithmetic task of the same type as the original.
Four treatments were implemented:
The findings on the study are that, on average, both genders perform equally well on the arithmetic task. But in the treatment where employers only see candidate’s appearance (which makes sex clear), both male and female subjects are twice more likely to hire a man than a woman. The discrimination survives if performance on the arithmetic task is self-reported because men tend to boast about their performance, whereas women generally under-report it. The discrimination is reduced, but not eliminated, by providing full information about previous performance on the task. By using the Implicit Association Test, the authors show that implicit stereotypes are responsible for the initial average bias in sex-related beliefs and for bias in updating expectations when performance information is self-reported. That is, employers biased against women are less likely to take into account the fact that men, on average, boast more than women about their future performance, leading to suboptimal hiring choices that remain biased in favor of men.
Audit study at U.S. universities in which fictional prospective students seek to discuss research disciplines before applying to a doctoral program. In total over 6,500 professors at top universities were drawn from 89 disciplines and 259 institutions. In the experiment, professors were contacted by fictional prospective students. Names of students were randomly assigned to signal gender and race (White, Black, Hispanic, Indian, Chinese), but messages were otherwise identical. The study finds that when considering requests from prospective students seeking mentoring, faculty were significantly more responsive to White males than to all other categories of students, collectively, particularly in higher-paying disciplines and private institutions. This was true to different extends in many academic disciplines except fine arts. The representation of women and minorities and discrimination were uncorrelated, that is it does not help a female student to contact a female professor. This finding suggests that greater representation cannot be assumed to reduce discrimination.
Audit study in the U.S. in which science faculty in biology, chemistry, and physics (n = 127) from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a fictitious position as a laboratory manager. Participants rated the student’s competence and hireability, as well as the amount of salary and amount of mentoring they would offer the student. The male applicant was rated as significantly more competent and hireable than the (identical) female applicant. The participants also selected a higher starting salary and offered more career mentoring to the male applicant. The gender of the faculty participants did not affect responses, such that female and male faculty were equally likely to exhibit bias against the female student. Mediation analyses indicated that the female student was less likely to be hired because she was viewed as less competent. The authors also assessed faculty participants’ preexisting subtle bias against women using a standard instrument and found that preexisting subtle bias against women played a moderating role, such that subtle bias against women was associated with less support for the female student, but was unrelated to reactions to the male student.
Audit study at eight large public U.S. research universities asking biology and physics professors (n = 251) to read one of eight identical curriculum vitae (CVs) depicting a hypothetical doctoral graduate applying for a post-doctoral position in their field. The professors rated the hypothetical candidates for competence, hireability, and likeability. The candidate’s name on the CV was used to manipulate race (Asian, Black, Latinx, and White) and gender (female or male), with all other aspects of the CV held constant across conditions. The authors of the study instructed the participants that the main purpose of the study was to examine how CV formatting and design styles influenced the science faculty’s perceptions of postdoctoral candidates. This should reduce demand characteristics and socially desirable responding, Therefore, questions on the format of the CV were included at the beginning of the survey before participants assessed the hireability, competence, likeability, and competitiveness of the candidate.
Faculty in physics exhibited a gender bias favoring the male candidates as more competent and more hirable than the otherwise identical female candidates. Further, physics faculty rated Asian and White candidates as more competent and hirable than Black and Latinx candidates, while those in biology rated Asian candidates as more competent and hirable than Black candidates, and as more hireable than Latinx candidates. Women were rated more likeable than men candidates across departments.
Probit Regression of Italian data across different academic disciplines with 26,307 applications for associate (n=15,422) and full professor (n=10,885). In the Italian system, candidates first participate in a nationwide competition to obtain a scientific qualification and then successful candidates compete to obtain a position at the department level. Committees awarding the scientific qualification had full autonomy on the criteria to be used in the evaluation but some criteria were suggested by the Ministry of Education, University and Research about the research productivity of candidates in the previous ten years, as measured by some bibliometric indicators. However, evaluation committees assess candidates exclusively based on their publications and CVs.
The authors estimate the gender gaps in the probability of success at these two stages, controlling for several measures of productivity. Whereas no gender differences emerge at the national level, women have a lower probability of promotion at the department level. When the number of available positions is not limited – as in the first nationwide competition – no gender discrimination emerges whereas when the available slots are limited women tend to have worse career opportunities than men: when the number of open positions in the department is very low, the difference in the promotion rate between men and women is around 10 percentage points while when positions are abundant gender discrimination tends to disappear.
Multilevel logistic regression of Italian data across different disciplines with 9,714 observations on the promotion to professor. The authors make use of the institutional set up in the Italian system: First, the candidates for academic positions have to obtain the national qualification (fit-for-the-role national filter), based on merit measured via bibliometric and non-bibliometric indicators. This step does not mean to get a position, it only means to be able to apply for it at the institutional level. The application process at the institutional level is, in comparison to the national qualification, less transparent and more autonomy is granted there. It is also hypothesised that discrimination based on gender may differ according to the percentage of women already at full professor rank by disciplinary field. The authors investigate gender inequality using a binary variable (promoted or not promoted) controlling by scientific productivity, normalised number of available vacancies, the result of national research evaluation, age, current rank-and-file position. Multilevel logistic regression demonstrates that among those who obtained the national qualification and at parity of other conditions, men have around 24% more probability to be promoted at parity of scientific production, which reveals relevant gender discrimination.
Correlational study that examines the effect of gender biases on promotion decisions (n= 4,759 researchers) in an annual nationwide competition (414 members of the evaluation committees) for elite research positions in France. Findings reveal that committees with strong implicit gender biases promoted fewer women at year 2 (when committees were not reminded of the study) relative to year 1 (when the study was announced) if those committees did not explicitly believe that external barriers hold women back. When committees believed that women face external barriers, implicit biases did not predict selecting more men over women. This finding highlights the importance of educating evaluative committees about gender biases.
Dataset of U.S. assistant professors (n=1,560) at research universities in sociology, computer science and English departments. The study looks for causal reasons of the gender gap in promotion to tenure. The dataset combines data from sources including curriculum vitae, Google Scholar, and web archive employment data, resulting in a dataset of assistant professors’ publication records, department affiliations, and job positions. Analyses examine the gender gap in the likelihood of promotion to tenure and in early career trajectories, while accounting for publication productivity and department/university context. The results demonstrate that productivity measures account for a portion of the gender gap in tenure, but in each discipline a substantial share of the gender gap remains unexplained by these factors. Department characteristics do not explain the tenure gender gap.
The results show that women are not only disadvantaged in their likelihood of receiving tenure overall, but are less likely to receive tenure in the departments where they began their assistant professor careers. Women also receive tenure in less prestigious departments than men in their fields, on average. A sizeable portion of the gender gap in tenure is unexplained by productivity and variation in department context, suggesting that gendered inequality in evaluation affects the gender gap. Results suggest that gender inequality in evaluation is the leading culprit for women’s lower promotion rates, though productivity plays a role as well.
Audit study for applications for assistant professor in the U.S. conducted on 873 tenure-track faculty from biology, engineering, economics, and psychology at 371 universities/colleges. In the main experiment, 363 faculty members evaluated narrative summaries describing hypothetical female and male applicants for tenure-track assistant professorships who shared the same lifestyle (e.g., single without children, married with children). Applicants' profiles were systematically varied to disguise identically rated scholarship; profiles were counterbalanced by gender across faculty to enable between-faculty comparisons of hiring preferences for identically qualified women versus men. Contrary to prevailing assumptions, men and women faculty members from all four fields preferred female applicants 2:1 over identically qualified males with matching lifestyles (single, married, divorced), with the exception of male economists, who showed no gender preference. Comparing different lifestyles revealed that women preferred divorced mothers to married fathers and that men preferred mothers who took parental leaves to mothers who did not. However, slightly better-qualified males were always chosen over slightly less-qualified female candidates.
The study uses quantitative analysis of 286 appointment reports and qualitative interviews with 21 scouts in the Netherlands to shed a light on the appointment practices for medical professors. The analysis revealed a dominant pattern of recruitment by invitation by male scouts, leading to three gender mechanisms of inclusion and exclusion through formal/informal networking. When candidates are recruited through homogeneous male networks, the pool of potential candidates is drastically restricted. Women are not seen as obvious choices for professorships since their commitment to the job is questioned. Furthermore, women do not correspond to the image of the ideal manager since they do not appear to conform to the gendered preconceptions of leadership held by the predominantly male scouts. The authors states that by opening the black box of these highly secretive appointments, it is shown how allegedly gender-neutral practices contribute to the perpetuation of gender inequalities in academic medicine.
The authors followed the careers of (n=6,336) scientists from the post-doctoral fellowship stage to becoming a principal investigator (PI) – a critical transition in the academic life sciences. Using a dataset that connects individuals’ National Institutes of Health funding histories to their publication records, the authors find that a large portion of the overall gender gap in the life sciences emerges at this transition. Women become PIs at a 20% lower rate than men. Differences in “productivity” (publication records) can explain about 60% of this differential. The remaining portion appears to stem from gender differences in the returns to similar publication records, with women receiving less credit for their citations.