The Influence of Sexual Orientation and Race on Gender Prescriptive Stereotypes with Sa-kiera Hudson

Gender stereotypes are powerful forces that shape collective expectations and are socialized from an early age; these stereotypes are not just descriptive, but also prescriptive, stating what sorts of things men and women should and should not do based on their gender.

Rule congruity theory helps to explain why these prescriptive stereotypes are often a source of backlash: men and women are evaluated negatively when the role that they occupy is incongruent with the stereotypes of their gender. Negative evaluations can come from both descriptive and prescriptive stereotypes – women can spark descriptive backlash in leadership roles if there are few other women in leadership, and prescriptive backlash if the traits she displays violates one’s notions of how women should behave.

Rule congruity theory has sparked a great deal of research, but researchers generally haven’t interrogated who or what we mean when we say “men” or “women.” Research on role congruity theory and gender generally presumes straight, white, middle-class individuals, which gives reason to believe that prescriptive stereotypes of women don’t fully encompass lesbian women or women of color.

Taking an intersectional perspective may reveal that societal expectations are unique based on other identities. Importantly, less than 20% of studies on race include women, and less than 10% of studies on gender include race: there is an enormous amount of work to be done in intersectional psychology.

The first WAPPP Seminar of the semester featured Sa-kiera Hudson, PhD Candidate in Psychology at Harvard University and WAPPP Fellow, presenting research on intersectional identities and gender stereotypes. In particular, Hudson questions whether rule congruity theory is adequate to explain intersectional identities and, if not, how the theory should be modified.

Study 1

Hudson’s first study incorporated sexual orientation as an additional identity. Existing literature suggests that in the realm of stereotypes, gay men and straight women are presumed to be similar, as are lesbian women and straight men, because of their similar sexual preferences.

In this study, individuals were given a list of 70 traits, some of which were more stereotypically masculine, feminine, or neutral (e.g. “assertive,” “warm and kind,” “honest”), and asked to rate whether that trait was desirable for straight and gay men and women, for men and women without a sexual orientation identifier, and for straight or gay people, without specifying gender.

Hudson hypothesized three expected patterns: stability in gender stereotypes, evidence of heterocentrism, and evidence of gender inversion.

1. Stability in gender stereotypes: Hudson’s findings were substantially the same as a similar study from 2002, which indicates that prescriptive gender stereotypes are relatively stable and haven’t changed much in the last 15 years.

2. Evidence of heterocentrism: There was no trait for which respondents’ rankings of desirable traits for a “man” deviated from those for a “straight man,” nor “woman” from “straight woman” or “person” from “straight person.” This finding suggests that when individuals are rating a person without a sexual orientation identifier, they presume straightness. While this isn’t surprising, it is useful: very few studies directly demonstrate heteronormativity in judgments like these.

3. Gender inversion: Hudson expected to see evidence of gender inversion, similarities between gay men and straight women and between lesbian women and straight men, in addition to differences between gay and straight men that mirror the differences between straight men and straight women. Of the 70 traits, there was evidence of gender inversion for 9: for example, it was less desirable for straight women to be assertive compared to straight men, but more desirable for lesbian women to be assertive compared to gay men.

An additional 12 traits showed evidence of gender asymmetry, where desirability ratings for men or women were the same regardless of sexual orientation, but diverged for the opposite gender. For example, cleanliness was equally desirable for gay and straight men, but for women, there was more pressure for straight women to be clean than for lesbian women. Thirty-four traits displayed evidence of sexual orientation asymmetry – there was gender differentiation for straight and gay men and women, but no difference between gay men and lesbian women. This finding suggests that gender might not matter as much as sexual orientation in terms of how we perceive gay men and lesbian women.

In addition, Hudson presented three other interesting wrinkles from this study:

• It is more desirable for lesbians to be assertive, competitive, and forceful compared to straight women, but there was no difference in trait desirability for business sense, career-oriented, or leadership ability, which suggests that it is acceptable for lesbian women to display dominant personality traits, but not in ways that might disturb the status quo of gender hierarchy.
• The differences between straight and gay men are much larger than the differences between straight and lesbian women, which suggests that gay men may lose some of the status that comes with being male by virtue of their sexual orientation, while lesbian women don’t gain much status above that accorded to straight women.
• Finally, Hudson’s study revealed some evidence that homosexuality is associated with low status – study respondents found it less desirable for gay men and lesbian women to be loyal, dependable, honest, or enthusiastic, traits that are typically considered neutral and positive. 

Study 2

Hudson’s second study replicated the first study’s methods using race rather than sexual orientation. There are different stereotypes of men and women of different races; for example, white women are stereotyped as submissive and feminine, black women as confident and aggressive. What studies do exist demonstrate that black and white women are treated differently with respect to normative traits – black women are not sanctioned as heavily for “aggressive leadership behaviors” as black men and white women. Something about the interaction of race and gender stereotypes specific to black women may mediate backlash.

Just as in the first study, Hudson found stability of gender stereotypes over time and evidence of eurocentrism: when respondents rated traits for a person without a race marker, their answers most closely matched those given for white individuals, suggesting that they viewed white as the default.

Hudson initially hypothesized that this study would yield evidence of gendered race theory, which posits that black individuals are masculinized. However, the results produced limited evidence for gendered race theory! For black men, it was less desirable to be masculine and more desirable to be feminine compared to the control male target. For black women, it was less desirable to be feminine and more desirable to be masculine compared to the control female target, suggesting that both black men and women are distanced from their gender stereotypes. For 38 traits, there was little gender differentiation among black targets but a significant amount for white targets, again suggesting that gender is not as important as race for stereotypes regarding men and women of color.

Both of these studies revealed that the prescriptive norms for gays and lesbians and for black men and women are mostly feminized norms, which suggests that status might play a role in how gender prescriptive stereotypes are generated for intersectional targets – these stereotypes are less about gender per se and more about relative status. The results of these studies underscore just how much intersectionality matters for contemporary research and the importance of updating existing theories accordingly.

Role Models as "Social Vaccines"

Do you have everyday role models? Successful people in your field who look like you and aren’t superhuman?


Though I have become comfortable at male-dominated tables, I always look for fellow women in politics. I don’t just mean Hillary Clinton. She certainly inspires me, but she is a super star! It’s the regular women – the chiefs of staff, the policy advisors, and some Members of Congress – that I can look to and think “yeah, that could be me in a few years.”

Nilanjana (Buju) Dasgupta, Professor of Psychology at UMass Amherst, demonstrates that exposure to such role models can act like a “social vaccine” against negative stereotypes. This kind of vaccination by inspiration is especially important for minority groups in high-achievement fields – think women in politics, business, or science, technology, engineering and math (STEM) careers.


Professor Dasgupta and her team tested the Social Inoculation Model with numerous quasi-experimental studies in the real world. They focused on women in the STEM field, which is increasingly going to drive the economy. In STEM careers, women are both a numeric minority and a group facing negative stereotypes (perceptions that women are bad with numbers, etc).

In one study, unsuspecting college students signed up for a calculus class – a required gateway course for all STEM majors. There were 7 female and 8 male professors teaching 15 sections. The professors were also unaware of the experiment’s hypotheses. They had similar experience levels and teaching styles. The syllabi and tests were the same and the grading was done blindly by all professors across the sections.

Twice during the semester the researchers measured students’ attitudes toward math, their self-confidence with math (what grade they thought they would get), and their personal identification with the professor. They found that the female students taught by male professors were less likely to self-identify with math than did their female peers in the sections taught by female professors. Female students were also found to have negative attitudes toward math in sections taught by men, but not by women.

Women in male-taught sections were less self-confident about their mathematical ability – they estimated a lower final grade than did women in the sections taught by women. It is striking that with their final grades the female students in this study significantly outperformed men, regardless of their professor’s gender.

These women obviously had the aptitude for math, but they doubted their own competence...unless their professor was female.


Professor Dasgupta conducted a number of other studies to test various aspects of her theory, trying to understand the mechanisms by which the “social vaccine” worked. She also looked at effects of peers, exposure to experts through media and the effects of the teacher’s gender on students of younger ages.

Drawing on her experiments and the body of related literature, Professor Dasgupta makes a compelling case that for underrepresented groups in high-achievement fields ability alone is not sufficient to succeed. Exposure to relatable role models can mean the difference between staying in and dropping out.

That is why being able to look around and think “sure, I can do what she does” is so important for me and other professional women outnumbered in their fields. And it is even more important for the young girls considering a career in STEM, politics or business.


Anya Malkov is an MPP candidate at the Harvard Kennedy School, a WAPPP Cultural Bridge Fellow, and an alumna of From Harvard Square to the Oval Office.

Professors Are Biased Too

An ordinary e-mail once caught the eye of Modupe Akinola,Assistant Professor of Management at Columbia Business School. It was from a prospective Ph.D. student, an African-American woman, asking for a meeting.

Dr. Akinola wondered: “Would I have reacted differently if this was from a man? Would it make a difference if the request was for today and not next week?” She joined with colleagues Katherine Milkman and DollyChugh to turn these questions into research questions in a field experiment measuring discrimination in academia.

The creative and elaborate experiment started with putting together a representative sample of over 6,500 faculty members from 260 universities. The team used publicly available demographic information on professors to ensure a good sample. The researchers then created a few prospective Ph.D. students. The names of these imaginary students were tested and proved to be easily recognizable as either male or female and as Caucasian, Black, Hispanic, Indian or Chinese.

At 8:00 am on a Monday, e-mails from Brad Andersons, Latoya Browns and 18 others went out to unsuspecting subjects, asking to meet “today” in half the cases and “next Monday” in the other half. The research team was impressed by how quickly most faculty wrote back and how often they agreed to meet, but when and with whom they agreed to meet was more interesting.

One would think academia, with its affirmative action and enlightened world views, might be a post-racial, post-gender sphere. As it turns out – not so much, especially not when there is time to think about it.

In the now condition, Akinola, Milkman and Chugh found no significant difference between number of responses to white males and to others, but when the request was for later, white men received both more responses and more meeting acceptances than any other prospective students. The white men fared better than all other racial categories across almost all disciplines. The effect remained even when the race or gender of faculty and student matched.

According to construal level theory (CLT) immediate events demand concrete reasoning focused on feasibility, whereas decisions about distant events trigger abstract thinking and a focus on desirability of the event. Thus, future events create more room for unconscious stereotypes and biases to enter the decision-making process. In this study, for instance, the responses received to the “now” requests systematically displayed a focus on “how,” whereas the “later” e-mails were more likely to be answered with a request for credentials or more information – a “why” response.

The point of this experiment and other studies that spotlight the influence of stereotypes and biases on consequential decisions is not to call people racist or sexist. The point is to come up with ways to address the biases and to improve minority outcomes. For instance, referring all prospective students to the Ph.D. program coordinator would take the burden off individual professors and ensure that all students get their questions answered. This is just one option that an experiment like this might bring up for discussion.

Unfortunately, some faculty did not take kindly to the experiment. When debriefed and told that they had been used in a study of bias, many expressed outrage and demanded to speak with the Institutional Review Board.

To me, their reaction suggests the thorny subjects of race and gender are not studied enough in academia. Perhaps academia, more so than other spheres, makes it taboo to have biases, but shaming does not make biases go away! Nobody wants to be called a racist or sexist, not even a little bit, but simply feeling guilty is not productive. We can structure decision-making in ways that level the playing field, and we need creative researchers like Akinola, Milkman and Chugh to make that happen.

Anya Malkov is an MPP2 at the Harvard Kennedy School, a WAPPP Cultural Bridge Fellow, and an alumna of From Harvard Square to the Oval Office.