Blog against sexism (in science) day!
Today is Blog Against Sexism Day, and while we at FairerScience.org hope that we blog against sexism on a regular basis, this is a fine excuse to talk explicitly about sexism, science, and why defining people and their interests by their gender is a harmful oversimplification.
Thanks to Larry Summers, among others, there's a lot of talk these days about why women are underrepresented in the sciences, and I, for one, am excited to see it. We can't find a solution to a problem we're not talking about, after all. So, let's keep talking. It's even great to see people arguing, especially when the arguments consist of evidence gleaned from careful and relevant research.
To that end, we'd like to see more careful and relevant research being done and being disseminated. We're really tired of reading old myths disguised as researched facts, and we hope you are, too. When scientists package "common sense" about gender differences to support a theory, we weep and rend our clothing, because this hurts everyone: scientists and the good name of science, women, men, students, and society as a whole.
Am I being overdramatic? I think not. After all, the definitional result in sexism is reduced options for women... and men. We're all in this together, and as long as we tell people that they way they act, their behavior, their interests, are defined by their genetics or their hormone levels, we're closing the door for people who don't fit the norm, whether that norm is imagined or real.
We all know there are differences between women and men, just as we know there are similarities. We also all know that there are difference between one man and another, or between one woman and another. And I think we can all agree it's useful to examine norms and understand what group difference may or may not exist, just as long as we can also understand that describing a norm is a far cry from describing an individual.
So, my Blog Against Sexism Day challenge to you is this: Whatever research you read today, examine it carefully. Be especially wary of research whose conclusions uncomplicatedly support gender stereotypes or involve overbroad generalizations.
And then do it again tomorrow.