There has never been a better time for women to enter academic careers in math-intensive science fields. That’s the message Cornell University psychologist Stephen Ceci says he was hoping to get across in last Sunday’s controversial op-ed in The New York Times, “Academic Science Isn’t Sexist,” co-authored by Wendy Williams, also a psychologist at Cornell. But that’s not how the article, which attempts to summarize a 67-page paper they co-authored with economists Donna Ginther of the University of Kansas, Lawrence, and Shulamit Kahn of Boston University, came across to some readers.
In addition to the provocative headline, statements such as “the experiences of young and midcareer women in math-intensive fields are, for the most part, similar to those of their male counterparts” and that female underrepresentation in some fields is “rooted in women’s earlier educational choices, and in women’s occupational and lifestyle preferences” sparked outcry from the blogosphere and on Twitter and prompted heated discussion within the scientific community. Those discussions have focused on whether the findings are valid, the potential implications, and the best way to move forward.
Sure, women make choices, but the choices are heavily constrained by environmental factors. … There’s quite a bit of writing about the misuse of the concept of choice that masks discrimination.
Most agree that, in today’s academy, things are much better than they used to be. Today, “although women are underrepresented in math-based fields, those women who go into them do as well as the men who go into them,” Ceci says in an interview with Science Careers. That statement, which some critics argue is too simple, is one of the major results of the paper, which includes a broad review of the literature and primary analysis of relevant data mainly from the National Science Foundation (NSF). Specifically, the authors report that women who compete for assistant professor positions in math-intensive science fields are just as likely to be hired as men are, if not more so, and that women are not discriminated against in tenure and promotion decisions. The reason these fields are not gender-balanced in the academy, the authors argue, is because girls opt out of math, especially in high school, leaving them poorly prepared for careers in math-intensive science fields.
“I think it’s an important message,” says psychologist Diane Halpern of the Keck Graduate Institute in Claremont, California, who wrote a commentary that accompanies the paper. Women in math-intensive fields “are not being discriminated against in the academic job market. I think that’s really something to celebrate.”
Others, though, are cautious in interpreting the findings, which rely heavily on observational data from the NSF Survey of Earned Doctorates. “The problem with observational data is that you can’t determine cause and effect very easily,” says psychologist Virginia Valian of the City University of New York’s Hunter College. “You don’t know what the underlying mechanism is.”
“Measures of equal performance or equal opportunity in hiring do not mean there is no bias,” says University of Texas, Austin, sociologist Jennifer Glass. “They mean that women have overcome any bias that may exist.”
“It’s not that I don’t think their data is accurate,” she adds. “It’s that I think their interpretations should be taken with a grain of salt.”
Ginther says that correlational data, while offering some challenges, can still be valuable for addressing the questions the study set out to answer. The point, she says, is that the study’s authors looked hard for evidence of bias and didn’t find it, or not much. “It’s very difficult to uncover bias in the data. In the aggregate, it’s really difficult to tease out. Sometimes I have some studies that show that bias may be a potential explanation, but in much of the data that we present here, we don’t see a lot of evidence of bias in careers.”
The complement to correlational data, of course, is experimental data. During her postdoc at Yale University, Corinne Moss-Racusin was the lead author on a study showing that both male and female science professors evaluate a resume more favorably if they perceive that the applicant is male, reflecting their implicit bias about gender and scientific aptitude. “When we do a controlled lab experiment, we’re able to conclude pretty convincingly that bias exists,” says Moss-Racusin, who is now an assistant professor of psychology at Skidmore College in Saratoga Springs, New York. She is concerned that Ceci’s study does not give enough weight to these experimental studies. The authors “seem to underrate the large body of experimental evidence pointing to the importance of bias and stereotyping and the experiences of discrimination that are driving women out of these fields,” she says.
This sentiment is echoed by others in the field, including University of Wisconsin, Madison, psychologist Janet Hyde. “I don’t think [the authors] give sufficient credence” to the experimental results about implicit bias and stereotype threat, Hyde says. “I think they just didn’t take it seriously enough. … They too readily dismiss evidence of sexism in academic science.”
Tyranny of choice
Another flashpoint for this article was the author’s invocation of the role choice and preferences play in the gender imbalance in math-intensive fields. The authors frame much of the discussion around women’s choices about, for example, which high school math classes to take, what college major to enroll in, and whether to pursue an academic career. (The paper has a section titled “The Role of Women’s Choices to Opt Out.”) Some other researchers object to this framework because, they say, it doesn’t reflect the cultural pressures that influence such choices. “These are not free choices,” Hyde says. “Sure, women make choices, but the choices are heavily constrained by environmental factors. … There’s quite a bit of writing about the misuse of the concept of choice that masks discrimination.”
The intent of investigating girls’ stated preferences, Ginther responds, was to identify the point at which intervention could be the most effective, not to blame them for their choices. “If you’re going to treat a symptom”—the underrepresentation of women in math-intensive fields—“you’ve got to know where it’s happening and focus your efforts on where things start to diverge.” One of the paper’s main recommendations is for math interventions for girls at the precollege level, which the authors say could improve the gender balance in math-intensive areas.
Everyone agrees that there has been a lot of progress. “It was amazing for me how much things have changed” in just the years between 2000 and 2010, Ginther says. The article has spurred strong responses in part because of its likely impact on continuing change. Ceci hopes that the results will encourage young female scientists by counteracting the negative stories they are likely to hear about being a woman in science. “We think it’s a propitious time for young women to be launching careers in academic science. … It would be very unfortunate if a talented young woman opted out of a career in science because she read anecdotal reports or testimonials that say it’s a hostile work environment.”
Others, though, worry that the paper and the accompanying op-ed could hurt the ongoing effort to increase gender balance in the sciences. Hyde is concerned that downplaying the challenges young women are likely to face will make them more vulnerable to those challenges. “They’re going to hit their first instance of sex bias and they’re going to be totally floored. It’s going to be worse than if you said, ‘There will be instances of this, but you can overcome this.’ ” She also worries that the op-ed headline, which made it sound as though the job of combating bias in the academy is done, could diminish support from university administrations for programs promoting diversity in science, which could undercut efforts that are still needed to push academic science toward equality. “There has been real progress, but that progress has come about because people have worked very hard to make it come about,” Valian says.
Most everyone agrees that it is a complex issue with many causal factors that will likely require multiple ongoing interventions. As for the current work, Ginther says, “we tried to get our arms around a vast literature, and I hope that we can move the discussion past the headline and the op-ed and more towards points that we agree on, the points that we disagree on, and where we need to concentrate our efforts in order to have a diverse academic science professoriate.”
► This new study shows that in math-intensive fields where women are underrepresented, women who enter do about as well as men. That’s the paper’s basic message, and it’s good news. ► Gender imbalance persists, the authors say, because of choices girls and women make well before they attain professorships—especially the choice that many make during school: not to study math. Improving this situation, others emphasize, will require fundamental cultural changes in the way we think about math, science, and gender. ► The authors hope this insight—that women professors do just as well as men do—will help attract more girls and women into math-intensive fields, pushing those fields closer to real gender balance. ► Critics worry that this message may make girls and young women less prepared for bias they are bound to encounter and may undercut support for continuing efforts by institutions to attain gender balance in math-based sciences.