In STEM Fields, Many Employers Hire “John” over “Jennifer”June 11, 2015
Renowned scientist and Nobel Prize winner Tim Hunt said recently that female scientists cause “trouble” for men in the lab. Hunt even went as far as to express support for sex-segregated labs. His remarks are just the latest public example of sexism facing women in science; two female researchers have shared the response they received after submitting a manuscript to a scientific journal — the peer reviewer suggested that they “improve” their research by bringing male scientists onto their team.
As if there’s not enough anecdotal evidence of women facing sexism in science, technology, engineering, and math (STEM) fields, one simple study exposed how adversely gender stereotypes and biases affect hiring outcomes for women in science. The study, which AAUW highlights in our research, found that women are being shortchanged in more ways than one.
For the study, researchers from Yale University asked more than 100 science faculty members at academic institutions across the country to evaluate one of two student résumés. The résumés were identical except for one small part: The candidate’s name was either John or Jennifer. Despite both candidates having the exact same qualifications and experience, science faculty members were more likely to perceive John as competent and select him for a hypothetical lab manager position.
And it didn’t stop there. Female and male science faculty members alike offered John a higher salary than they did Jennifer and were more willing to offer him mentoring opportunities.
The discrepancy in John and Jennifer’s treatment is important because women are woefully underrepresented in STEM fields, especially in engineering and computing. Gender bias contributes to scenarios in which women like “Jennifer” are evaluated as less competent, less hirable, and less valuable than identically qualified male counterparts.
Another study by researchers at Columbia University, Northwestern University, and the University of Chicago found that participants acting as employers systematically underestimated the mathematical performance of women compared with men. The result? The experiment’s employers hired lower-performing men over higher-performing women for mathematical work.
So what can done? As a first step, we can acknowledge that we are all influenced by gender biases, whether or not we consciously endorse them. Second, individuals tasked with making evaluations or hiring decisions — including employers, academics, and peer reviewers alike — can help reduce the influence of bias by removing information about an individual’s age, race, and gender from decision-making contexts (like résumés and cover letters). And third, whenever possible, managers should base their hiring and promotion decisions on objective past performance information.
It’s critical that we work to end gender bias in all fields, including STEM. Diversity in the workforce contributes to creativity, productivity, and innovation. Finding solutions to many of the big problems of this century, including climate change, universal access to water, disease, and renewable energy, will require the skills of scientists, engineers, and computer scientists. When women are not well represented in these fields, everyone misses out on the novel solutions that diverse participation brings.
Find out why there are still so few women in engineering and computing — and what we can do about it.
Here are ten things you can do, whether you’re an employer, professor, professional, or parent.
“I was exhausted all the time, I was having nightmares, and I started to talk with other women I worked with, and they shared that the same thing was happening to them.”