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Gender & Medical Education

sheMD Gender Medical Education

Editor Note: This is part one in a three part series.

I was raised as “the son my father never had.” I grew up fishing and hunting with the boys or roaming the middle of the soccer field as “controlled chaos”. I was called “bossy” and “outspoken,” as I was typically telling other kids what to do, coming up with ideas and plans and then implementing them. I was raised in a home with a physician father and a full-time working mother, one of the highest-ranking female employees in her bank in our state. I truly did not see gender differences in my childhood. I believed I was equal to males. Medical school was the first time I noticed gender differences at all. I remember calling my mother with a sense of wonder. “This is a thing? I'm different than boys?” But I couldn't put my finger on what exactly the differences were. I just knew I felt it. Then I went to residency, and “woah”. Despite being at the top of my class, my evaluations made me cry, regularly. Ugly cry. I had to learn to “play nice” with nurses, techs and ancillary staff to get things done in a way that the males around me never had to do - I cleaned the pelvic exam room more times on a shift than ANY resident, EVER. It wasn’t until I graduated and started hearing other women’s stories and researching gender differences that I began to appreciate that this wasn’t a “ME” thing but a “WE” thing. It WAS and IS a gender thing.

To start delving into this topic, it is best to have some background in gender bias and the related theories from psychology literature. Overt gender bias is an explicitly endorsed personal belief about a sex, whereas implicit bias is more elusive. One is unaware that it is operating, and it may be at odds with what that person actually believes, but still influences their judgment and actions (1). Most of what we will be focusing on is implicit bias, although overt gender bias is not extinct in our society. There are also descriptive and prescriptive forms of gender bias. Descriptive gender bias is how men and women actually are, describing qualities or behavioral tendencies that are desirable for each sex (1-2). Descriptive norms are considered synonymous with gender “stereotypes”(2) or character traits. Prescriptive gender bias describes how men and women “should be,” thus defining norms for acceptable behavior (1-2). The combination of descriptive and prescriptive expectations make up the “gender role” (1). These “gender roles” define males as “agentic,” possessing characteristics, such as assertiveness, controlling, independent, self-confident and dominating, whereas women are characterized by “communal” traits (concerned with the welfare of others), such as affectionate, nurturing, dependent, and gentle (2-3). The prescriptive gender biases state women should act in a “communal” fashion, but they also specify what women should NOT do. Women should NOT engage in stereotypically male or “agentic” behaviors or possess those “agentic” character traits (1-3).

sheMD Agentic vs Communal Leadership Traits

That was a LOT of psychology and definitions. What does it all mean? Society expects women to act in a nurturing, sympathetic, caring way and NOT to act in a competitive, driven, and assertive manner. So what happens to us “Type A” women who are driven to succeed, who want to compete in the classroom/work environment and who want to achieve? Well, first of all, we may have to work HARDER to be considered competent when compared to our male colleagues. And second, we will pay a price for our success, since we are acting out of line with our gender norms.

sheMD Women In Medicine Work Harder

Why do we have to work harder? Medicine, science and leadership are all considered agentic domains, so women “should be” less likely to be competent or successful in these fields based off prescriptive gender norms (3). Studies have shown that in agentic domains, identical work is rated lower when performed by a woman, and evaluators require MORE proof of women’s skills than men’s skills to be convinced that they are competent (2-3). A study was done having undergraduate students rate an employee based on their CV for a job that was stereotypically male. The gender and the individual’s prior success were the details that were adjusted in the study. They found no significant difference between males and females in terms of competence rating when the individual’s prior success was made explicit. When, however, the information about performance was left ambiguous, the female employee was rated as significantly less competent than the male (2). So women are often assumed to be less competent (by both male and female evaluators) until they have clearly proven their competence, whereas males are often presumed competent from the start.

sheMD Likeability Penalty

Once they have proven themselves competent in this agentic domain, women then pay a price for their success, titled a “likeability penalty” or “backlash”. This penalty is because their success in an agentic career or leadership position violates their prescriptive gender roles. They often manifest stereotypically “male” or agentic characteristics instead of the expected communal attributes. This leads to unfavorable evaluations. Sheryl Sandberg gives a great example of this in her book, Lean In (4). She discussed a study done in 2003 by Frank Flynn and Cameron Anderson where they tested perceptions of men and women in the workplace. They took a case study about a female entrepreneur who used her personality and professional network to gain success. Half of the students read the story with the name of the entrepreneur as Heidi. The other half read the same case story but with the name Howard. The students were then polled and found Heidi and Howard to be equally competent, but Howard was a more appealing colleague. Heidi was seen as selfish and not someone that you would want to work for or work with. When women are successful, they are deemed less likeable, more interpersonally hostile and more personally derogated (1). This “likeability penalty” is not just office drama. It can strongly affect a woman’s evaluations, promotions, job opportunities and salary (1). Success and likeability are, unfortunately, negatively correlated for women.

Editor Note:

This is part one in a three part series. To read part 2, click here. To read part 3, click here.

This post was initially published on and also shared on


1. Eagly, Alice H., and Steven J. Karau. “Role Congruity Theory of Prejudice toward Female Leaders.” Psychological Review 109, no. 3 (2002): 573–98.

2. Heilman, Madeline E., Aaron S. Wallen, Daniella Fuchs, and Melinda M. Tamkins. “Penalties for Success: Reactions to Women Who Succeed at Male Gender-Typed Tasks.” Journal of Applied Psychology 89, no. 3 (2004): 416–27.

3. Carnes, Molly; Christie Bartels; Carol Isaac; Anna Kaatz; and Christine Kolehmainen. 2015. “Why is John More Likely to Become Department Chair than Jennifer?” American Clinical and Climatological Society. 126: 197–214.

4. Sandberg, S. (2013). Lean in: Women, work, and the will to lead (First edition.). New York: Alfred A. Knopf.

5. Dayal, Arjun, Daniel M. O’Connor, Usama Qadri, and Vineet M. Arora. “Comparison of Male vs Female Resident Milestone Evaluations by Faculty During Emergency Medicine Residency Training.” JAMA Internal Medicine 177, no. 5 (May 1, 2017): 651.

6. Mueller, Anna S., Tania M. Jenkins, Melissa Osborne, Arjun Dayal, Daniel M. O’Connor, and Vineet M. Arora. “Gender Differences in Attending Physicians’ Feedback to Residents: A Qualitative Analysis.” Journal of Graduate Medical Education 9, no. 5 (October 2017): 577–85.

7. Kolehmainen, Christine, Meghan Brennan, Amarette Filut, Carol Isaac, and Molly Carnes. “Afraid of Being ‘Witchy With a “B”’: A Qualitative Study of How Gender Influences Residents’ Experiences Leading Cardiopulmonary Resuscitation.” Academic Medicine 89, no. 9 (September 2014): 1276–81.

8. Choo, Esther K. “Damned If You Do, Damned If You Don’t: Bias in Evaluations of Female Resident Physicians.” Journal of Graduate Medical Education 9, no. 5 (October 2017): 586–87.

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