This post describes a new – and disturbing – PNAS paper documenting gender bias among scientists. Evidence of gender bias is hardly new–see, for example, the classic study by Wennerås and Wold, which showed that, when compared to the average male applicant, female applicants to the Swedish Medical Research Council had to be 2.5 times more productive to be viewed as equally competent. But this new PNAS study shows that it is still a problem in the sciences. One of the most important things to note is the women are just as biased against women in science as men. When I’ve discussed this in classes, something I encourage people to do ahead of time is to take the Project Implicit quiz on Gender and Science. One thing that research in this area suggests is important is simply being aware of one’s implicit biases, so that we can work to overcome them when evaluating applicants.
The other thing I’ve been pondering is this post by Kate Clancy on the sports psychology of academia, plus this follow up by Sci Curious, and then this follow up by Kate. In many ways, it’s about understanding what factors are outside of one’s control, and not getting overly fixated on one’s inability to control them. Rather, one should focus on being prepared for them, and how to react to them. This semester is a bit crazy for me, and I found this thinking useful – especially in thinking about some of the complexities of teaching a new (to me), giant, introductory course.
This one is for Meg, Brian, and Chris, to encourage them to stick around for the long term: why you should blog more. I mean, besides the obvious “to further embarrass me by continuing to attract way more traffic than I ever have.” 😉
I find under-representation in the sciences and academia to be perplexing, and enjoy such informative posts. Thanks!
You do have to keep in mind the timescale at which things change. The survey Meg linked to notes under-representation of women on the science faculties of major research universities, some of which is a historical legacy of hiring decisions made decades ago. I note this not in order to minimize the importance of the issue or to imply that it used to be an issue but isn’t any longer. But if you want to understand where things are now and how they’re changing, snapshots of the current composition of faculty (or of other groups like postdocs or grad students) are only going to give you some of the information you need.
I agree, a lot of what we see now is a product of the past, much like paradigms about inequalities based on gender or ethnic backgrounds. Which is why these topics are perplexing to me, I was raised in an environment where equality was taught regardless of demographics. I personally believe that different races do not exist, and are mere social constructions which, in and of themselves, contribute to racism. Without races, there is no racism. Gender issues are perhaps more complex, with obvious biological difference, and social difference contentiously studied.
I’ve gotten behind on the literature, but, the last I read, it is NOT an issue that will work itself out on its own as the current crop of students moves through. Women are lost at all the transitions — at the transition to postdoc, at the transition to assistant prof, etc. I should get more up-to-date on the literature again, and ideally do a post on it.
(I realize you weren’t saying that we should just wait and everything will be fine. It’s just that this is such a common misconception — and something that seems really logical — that I wanted to address it.)
In the context of the above PNAS study & this TREE study from a while back, I’d love to see the Dynamic Ecology bloggers tackle the question of double-blind peer review. I’ve never received a satisfactory answer for double-blind review shouldn’t be the default – most people just say “Well, reviewers would know who wrote the paper anyway” which isn’t a compelling argument against it.
Good post idea! My current problem is that I am accumulating ideas for posts at a rate that far exceeds my ability to write them!
I think point 2 in this post:
is an important follow up to that PNAS article:
“When scientists judged the female applicants more harshly, they did not use sexist reasoning to do so. Instead, they drew upon ostensibly sound reasons to justify why they would not want to hire her: she is not competent enough. … Practically, this fact makes it all the more easy for women to internalize unfair criticisms as valid.”
In general, people can always find reasonable-sounding (at least to them) rationalizations for whatever it is they want to believe. Being clear-eyed about your own biases and blind spots is really, really hard.
Agreed, which is part of why I think the quizzes like those at Project Implicit are so valuable. They can help people identify those biases and blind spots.
The problem I had with the Project Implicit quiz is that it just seems like such an interpretive leap from the sort of task performance the quiz is measuring to implicit biases. But this probably just reflects my ignorance of psychological research. The quiz has all the obvious controls and randomizations I’d expect it to have, and I can’t offer any obvious alternative hypotheses to explain why the typical results skew the way they do. I suppose I’m just more comfortable with the sort of science where whatever it is we’re measuring is either what we want to measure, or has some very tight and verifiable connection to what we want to measure. Which probably explains why I’m not a psychologist, and would be a bad one if I were.