Scientific objectivity and the cool assessment of facts are the hallmarks of the science, technology, engineering, and math (STEM) disciplines. So, of course, stereotypes have no place in these research labs and university departments. Or so you might think. But, when evaluating identical resumes, scientists may be significantly less likely to agree to mentor, offer jobs, or recommend equal salaries to a candidate if the name at the top of the resume is Jennifer, rather than John.
Corinne Moss-Racusin, a social psychologist at Skidmore College, recently spoke at the Stanford University School of Medicine to describe her research on gender bias among STEM faculty, including an experiment that had scientists evaluate identical resumes of a candidate named either “Jennifer” or “John.” Moss-Racusin has devoted her career to understanding how implicit gender bias can lead to discrimination against women and men, especially in the workplace.
Why does this research matter? For one thing, the United States is on track to face a shortfall of a staggering one million qualified STEM workers over the next decade, according to a recent White House report. Recruiting more women could help mitigate the shortfall—after all, women are dramatically underrepresented in STEM fields, and, in some disciplines, the proportion of women is actually declining. Moss-Racusin's research shows one reason why women’s numbers may be so low. What’s more, it shows that the solution to bolstering women's presence in STEM fields may just reside in science itself.
Moss-Racusin wanted to figure out if faculty at academic institutions, despite their training in conducting scientifically objective research, held implicit gender biases that were disadvantaging women who were pursuing STEM careers.
In their study, Moss-Racusin and her colleagues created a fictitious resume of an applicant for a lab manager position. Two versions of the resume were produced that varied in only one, very significant, detail: the name at the top. One applicant was named Jennifer and the other John. Moss-Racusin and her colleagues then asked STEM professors from across the country to assess the resume. Over one hundred biologists, chemists, and physicists at academic institutions agreed to do so. Each scientist was randomly assigned to review either Jennifer or John's resume.
The results were surprising—they show that the decision makers did not evaluate the resume purely on its merits. Despite having the exact same qualifications and experience as John, Jennifer was perceived as significantly less competent. As a result, Jenifer experienced a number of disadvantages that would have hindered her career advancement if she were a real applicant. Because they perceived the female candidate as less competent, the scientists in the study were less willing to mentor Jennifer or to hire her as a lab manager. They also recommended paying her a lower salary. Jennifer was offered, on average, $4,000 per year (13%) less than John.
Despite the scientific valuation of objectivity, gender stereotypes tainted the judgments of the scientists, generating a bias that dampened the STEM career prospects of Jennifer. Even women scientists favored John. This finding supports the understanding among researchers that gender biases are not a result of in-group favoritism. Rather, gender bias is often an outcome of an implicit cognitive process in which pervasive gender stereotypes shape our judgments, regardless of our intentions. Moss-Racusin stressed that the participants in her study were likely unaware they were discriminating against Jennifer.
Moss-Racusin's next step was to figure out what to do about this bias. In a separate study, she and her colleagues developed a diversity course for scientists. Their goals were to reduce implicit gender bias among academic scientists and to increase their motivation to address the underrepresentation of women in STEM.
One hundred twenty six scientists participated in the course. First, the scientists were told about Moss-Ruskin’s original findings and other research on gender bias. Then the scientists discussed and drew their own conclusions about the results. Finally, they practiced strategies to reduce gender bias at their own institutions.
The participating scientists completed surveys about gender and diversity before and after the course to see if it led to any change in attitudes. The research team found that the course significantly reduced gender bias and that the scientists showed a stronger, more assertive approach to pursuing actions that would increase gender diversity after participating. Research-driven diversity interventions such as this one are crucial to closing the gender disparity in STEM fields, argues Moss-Racusin.
In the spirit of true investigative science, STEM faculty have been eager to listen to, and learn from, Moss-Racusin's research. Research and training programs such as the one she designed, coupled with the support of the academic community, can help institutions move towards a future where scientific merit matters and where the name at the top of a resume does not.