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To promote a better sense of fit and belonging among faculty, Trower recommends that departments provide mentoring for all faculty. Mentoring helps address the feelings of isolation and marginalization that women in academic settings often report. Among STEM faculty in the COACHE survey, women rated the importance of formal mentoring significantly higher than men did. Trower told AAUW, “Mentoring is crucial for STEM women because without it they might not be privy to the good old boys’ club or behind the scenes conversations that are crucial to fitting in the department and to getting tenure.” Interestingly, women AAUW 70 rated the importance of informal mentoring even higher than formal mentoring. Trower believes that this may be because “informal relationships arise organically, and because they are not part of a formal process, they may feel more natural, closer, more trusting and honest, which may be especially important to women in STEM, who are often in a numerical minority in their departments.”
T h E r o l E o F FA M i ly r E S P o n S i b i l i T i E S
The ability to balance work and family responsibilities also contributes to overall satisfaction, especially for STEM women in the COACHE sample. Overall, female faculty were less likely than male faculty to agree that their institutions supported having and raising a child while on the tenure track. Female STEM faculty were the least likely to agree with those sentiments and were significantly less satisfied than their male peers were with the balance between professional and personal time. Although difficulty trying to balance work and family responsibilities is not specific to women in STEM, Trower suggests that the nature of scientific research may make work-family balance particularly challenging for female STEM faculty: “The lab knows no official stop time—it’s an unrelenting 24/7. It’s difficult to just pack up and go home. Stopping for any period of time, to take advantage of stop-the-tenure-clock leave for instance, could be deadly to your research program.” Although the effectiveness of work-life balance policies were significant predictors of women’s satisfaction, both women and men in science and engineering fields found child care on their campuses lacking. Trower explains: “Child care is a huge issue everywhere I go. Most campuses do not offer adequate, if any, child care.” Women’s representation among STEM faculty has increased significantly during the last four decades; however, women are still underrepresented in STEM fields and are more likely than men to work in lower faculty ranks. The findings from the COACHE survey indicate that both female and male faculty satisfaction are based on similar factors, including the nature of the work and departmental climate. Chilly departmental climates and isolation contribute to dissatisfaction among women, which can result in their departure from higher education.
Family responsibilities and a department’s work-life balance policies also have a greater influence on the satisfaction of female faculty compared with that of male faculty. This research suggests that if institutions improve the climate of their STEM departments as well as their work-life balance policies, they can better recruit and retain female faculty. Furthermore, because the factors that predict satisfaction are the same for female and male faculty in STEM, all faculty and institutions are likely to benefit from these improvements.
Trower recommends that departments focus on fit to improve faculty satisfaction and the
experiences of female faculty in science and engineering disciplines:
• Create an environment that supp or ts retent ion.
Ensure that new faculty are oriented to the university, school, and department. Cultivate an inclusive departmental culture by communicating consistent messages to all faculty, providing opportunities for junior faculty to collaborate with senior faculty, and ensuring the fair treatment of tenure-track faculty.
• Ensure mentor ing f or al l facult y.
Both formal and informal mentoring of junior faculty are important, and the latter is crucial to support the integration of women into science and engineering departments. Formal mentoring programs should be monitored and evaluated for effectiveness, and departments should foster informal mentoring by encouraging senior faculty to actively reach out to junior faculty.
• S upp or t facult y work-lif e balance.
Departments and universities should implement effective policies that support work-life balance. Stop-tenure-clock policies should allow both female and male faculty to stop their tenure clock for parental leave for anywhere from three months to a year after the birth or adoption of a child. These policies ensure that parents are not penalized for reduced productivity during the tenure-evaluation period. Providing on-site, high-quality child care also supports work-life balance and is important to female faculty satisfaction in particular.
AAUW 72 Chapter 8.
Implicit Bias A widespread belief in American culture suggests that group membership should not constrain the choices and preferences of group members. Being a girl need not prevent one from becoming a police officer, senator, or mathematician. Being a boy need not prevent one from becoming a nurse, kindergarten teacher, or primary caregiver. In fact, all programs promoting equal opportunity seek the removal of external constraints for individual pursuits.
Yet until the internal, mental constraints that link group identity with preference are removed, the patterns for self-imposed segregation may not change.
— Brian Nosek, Mahzarin R. Banaji,10 and Anthony Greenwald Many people say they do not believe the stereotype that girls and women are not as good as boys and men in math and science. The research of Mahzarin Banaji, however, shows that even individuals who consciously refute gender and science stereotypes can still hold that belief at an unconscious level. These unconscious beliefs or implicit biases may be more powerful than explicitly held beliefs and values simply because we are not aware of them.
Even if overt gender bias is waning, as some argue, research shows that less-conscious beliefs underlying negative stereotypes continue to influence assumptions about people and behavior.
Banaji is a professor of social ethics at Harvard University and a co-developer of the implicit association test (IAT) with Anthony Greenwald, professor of psychology at the University of Washington, and Brian Nosek, professor of psychology at the University of Virginia.
Together they created and operate the Project Implicit website (https://implicit.harvard.edu), a virtual laboratory housing implicit association tests that measure the association between two concepts to determine attitudes about different social groups. For example, the genderscience IAT, which is the focus of this discussion, measures the association between math-arts and male-female (see figure 20).
For the gender-science IAT, participants (who take the test anonymously) complete two rounds of categorization. In each round, participants are asked to categorize 16 randomly ordered words, eight representing either “male” (for example, boy, son) or “female” (for example, daughter, girl) and eight representing either “science” (for example, physics, engineering) or “arts” (for example, English, history). In one round, participants use one key to indicate words representing male or science and another key to indicate words representing female or arts. In the second round the pairings are switched, and participants hit one response key to Mahzarin Banaji is the Richard Clarke Cabot Professor of Social Ethics and head tutor in the Department 10 of Psychology at Harvard University. Her research focuses primarily on mental systems that operate in implicit or unconscious mode. With Brian Nosek and Anthony Greenwald, she maintains the educational website at https://implicit.harvard.edu, which was designed to create awareness about unconscious biases in self-professed egalitarians.
AAUW 74 indicate if a word represents male or arts and another key if a word represents female or science.11 The participants’ response time for both rounds is measured, and the average response time when science is paired with male is compared with the average response time when science is paired with female.
Source: Retrieved November 2009 from https://implicit.harvard.edu/implicit.
The sequence of whether male is paired with science or arts first and female with the other is decided randomly for 11 each test taker.
Banaji did not begin her career in social psychology with an interest in gender bias. As a graduate student (supported by an AAUW fellowship) at Ohio State University, she studied social cognition, a broad field that looks at how people make decisions about other people and themselves. “I don’t think that the word gender appeared even once in conversations in my five years in graduate school,” Banaji remembers. In her first faculty position at Yale University, however, the results of a particular experiment caught her attention.
Jacoby et al. (1989) found that when individuals were shown random names, such as Sebastian Weisdorf, from a phone book, a few days later they were likely to identify that name as the
name of a famous person from a list of both famous and unknown persons. Banaji explains:
“Memory works in odd ways. Something that we have seen before lingers in our mind, and sometimes we use that information to incorrectly make decisions.” She wondered if the same thing would happen with female names and replicated the experiment using the name Sally Weisdorf alongside Sebastian Weisdorf. Surprisingly, Banaji found that people were less likely to identify Sally as famous, even though both Sally and Sebastian were unknown. Women, it seemed, did not falsely “become famous” overnight like men. Based on this finding, Banaji concluded that people must unconsciously associate “male” and “fame” more readily than “female” and “fame.” When asked if gender had anything to do with their choices, study participants said no, indicating that they were not conscious of their bias. This finding led Banaji to try to understand unconscious forms of bias. She told AAUW that these unconscious beliefs can help explain “how good people end up unintentionally making decisions that violate even their own sense of what’s correct, what’s good.”
i M P l i C i T b i A S E S A n d G r o U P i d E n T i F i C AT i o n
In their first series of lab experiments to measure the strength of implicit attitudes between gender and math and science, Banaji and her colleagues worked with a sample of undergraduate students (40 women and 39 men) at Yale University. In one study, the researchers found that although both female and male participants had negative implicit attitudes toward AAUW 76 math-science compared with language-arts, women showed a more negative evaluation of math-science (Nosek et al., 2002b). Additionally, women identified more strongly with arts than with math, but men showed no preference for either math or arts. Insofar as this result is
representative of the population of the United States as a whole, Banaji says:
The first effect is that our culture does not support the idea that studying math and science is a cool thing to do. That alone is something to worry about. However, girls and boys seem to know that if one or the other group is better at it, it’s boys. When we look at how quickly men associate self with math, it’s a lot more easily than do women. Often we hear from girls that it’s not that they can’t do math; it’s that they don’t identify with it. And that’s critical—when you don’t see yourself connected to a particular path, whether it is math-science or motherhood, the likelihood is that you will steer clear of it.
In the second study of another group of Yale undergraduates, Banaji and her colleagues measured the implicit math-gender stereotype and degree of gender identity. They found that both women and men held equally strong implicit stereotypes linking math to male.
They also found that the degree to which female and male students identified with their gender group was related to their attitude toward math, math identity, and the endorsement of math-gender stereotypes (ibid.). For example, women who more closely identified with female identity showed more negative math attitudes and weaker math identity. According to Banaji, “The sad but clear implication of that result is that the more you associate with your group (female), the less you are likely to associate with math. Something has to give, so to speak, and it’s not going to be the connection to your gender; math is psychologically more dispensable.”
iMPliCiT GEndEr-SCiEnCE biASES And GEndEr GAPSin PErForMAnCE
Implicit gender-science biases may go beyond influencing individual behavior. The overall level of the implicit association of science with male in a country may be related to gender disparities in math and science performance. A recent study conducted by several researchers from several countries, including Banaji, examined whether national differences in implicit genderscience stereotypes could predict gender differences in performance in math and science.
The researchers hypothesized that a two-way relationship may exist between the level of gender-science stereotyping and gender differences in science performance. Stereotypes linking science with male may create gender differences in performance among students, and those gender differences in performance may reinforce the stereotypes linking science with male (Nosek et al., 2009). To test this idea the researchers examined whether a country’s mean level of the implicit gender-science stereotype could predict gender difference in eighth