Changing the culture in science
Video clip: Molly believes that there is a pervasive stereotype that men are better than women at ‘quantitative endeavours’, which may disadvantage women.
But there was something that happened at a recent conference. I do work that involves computational modelling and there are very few women who do this kind of work, and I was, I was giving a talk and I presented this work and a female colleague of mine who also does modelling work was sitting in the audience and she told me afterwards that at the point in my talk when I put up the slides with the models, her male colleague sitting next to her turned to her and said, ‘Who did Molly’s modelling for her?’
Assuming you had a male boss?
Assuming that my male colleague, collaborator had done it for me, that I can’t write the code to do it myself. And that is extremely damaging because I did do it myself, and yeah, it’s totally demoralising because then you think, you know again because there are fewer women in the field and any paper is going to have multiple co-authors it’s inevitable that I will have male co-authors on my papers and your worry is that, is the public perception that, “Oh it’s the men on the paper who are devoting the, the brute brain power to the project.”
I mean I think just generally, I can’t speak for other fields, I can only speak for psychology and neuroscience but I do see the field moving in a more mathematical, quantitative direction. And in light of that I think we will really have to be vigilant about the influence of gender stereotypes because there is a pervasive stereotype that men are better than women at quantitative endeavours. And if there is a systematic discrimination where a female applicant is writing a grant proposal to do computational work and a male applicant is writing a proposal to do computational work, and these two candidates are matched on CV etcetera, if there is a stereotype that women are bad at Math, and these are quantitative computational proposals, the woman, the woman will be at a disadvantage, even at an unconscious level. And I don’t know how to deal with that. Maybe blinding the applications is an answer. But that’s something that I worry about because as the field is moving in this more quantitative direction that is going to be a risk factor for heightened gender discrimination and we have to make sure that that doesn’t happen.