Field of Science

Getting at the truth: gender in the lab

Nobel prize winning biochemist Tim Hunt made an unfortunate series of remarks at a luncheon for women science writers and journalists at the World Conference of Science Journalists in Seoul, South Korea: “Let me tell you about my trouble with girls … three things happen when they are in the lab … You fall in love with them, they fall in love with you and when you criticise them, they cry.”

Today he's said he's sorry for having made those remarks to that particular audience, suggesting first that it was a misunderstood attempt at irony, but he stands by his comments: "I just meant to be honest, actually."

He went on to say that, "It's terribly important that you can criticise people's ideas without criticising them and if they burst into tears, it means that you tend to hold back from getting at the absolute truth....Science is about nothing but getting at the truth and anything that gets in the way of that diminishes, in my experience, the science."

What I'm thinking about is how the documented tendency of men (or should I say boys?) to be overconfident in their self-assessment of ability in science and math might diminish the effective functioning of a research group? Shelley Correll's work showing that "males assess their mathematical competence higher than females who perform at the same ability level and who receive the same feedback about their mathematical competence."makes me wonder if when Tim Hunt criticizes a boy's ideas, the boy discounts the criticism because he is overconfident.  [Amer. J. Soc. 106 (2001): 1691–1730.] #justbeinghonest

Hunt's remarks should come as no surprise, given what he said in this interview:
Labtimes: In your opinion, why are women still under-represented in senior positions in academia and funding bodies? 
Hunt: I'm not sure there is really a problem, actually. People just look at the statistics. I dare, myself, think there is any discrimination, either for or against men or women. I think people are really good at selecting good scientists but I must admit the inequalities in the outcomes, especially at the higher end, are quite staggering. And I have no idea what the reasons are. One should start asking why women being under-represented in senior positions is such a big problem. Is this actually a bad thing? It is not immediately obvious for me... is this bad for women? Or bad for science? Or bad for society? I don't know, it clearly upsets people a lot.
If he wants a hint, it's bad for science.  Restricting the pool means you get fewer breakthroughs. Last fall I built a simple Monte Carlo simulation of "science" to find:

"I wonder if framing the issue of women in science as one of equity to individuals — it's not fair to deny women the opportunity to play the game — blinds us to the costs to science as a whole of unwittingly perhaps, but systematically regardless, hampering the participation of women in science. We see science as a meritocracy, where the best people and the best ideas bubble up and we fear efforts to play fair could undermine the overall quality of science. But are 'fair' and 'best' necessarily at odds with each other in the arena of scientific discovery? Stated another way, at any given time do discoveries go unmade because the person who might make them is not in the scientific workforce?

In an attempt to roughly quantify the answer to this question, I built a simplistic computational model of scientific discovery. The model used a Monte Carlo approach to create a scientific community from a larger population of one million. Inherent scientific ability was assumed to correspond to a single integer variable, with values ranging from a low of zero to a maximum of 200 and to follow a normal distribution (σ = 30); potential scientists were assumed to have a score above 140 on this measure. The parameters were set such that one discovery was expected per thousand potential scientists. Discoveries were not uniformly distributed throughout, but weighted such that higher ability scores were more likely to have the potential to make a breakthrough.

A model scientific community was selected from the full population using a weighted random selection procedure, which again favoured the 'best' end of the pool, and the number of 'discoveries' made by this select group were added up. The simulation was run for a total of one thousand trials. Models that limited the selection of women to 10% of the pool incurred a 10 to 15% average penalty on the number of discoveries made, compared with pools with roughly equal numbers of men and women.

Having 10% of potential scientific breakthroughs go undiscovered may sound insignificant, not worth the bother of figuring out how to bring more women into a field. That is, until you are asked to take a 10% pay cut, or if I ask which of the top-ten organic reactions you would prefer to do without. Heck? Diels–Alder? Within the limits of my model, choosing fairly with respect to gender does not compromise the quality of the scientific community, in fact, the opposite is true." [Nature Chemistry 6 (2014): 842–844.]

Correll, Shelley J. “Gender and the Career Choice Process: The Role of Biased Self‐Assessments.” American Journal of Sociology 106 (2001): 1691–1730.  See also the discussion in Cordelia Fine's Delusions of Gender pp 48-50.

Francl, Michelle. “Seeding Crystallography.” Nature Chemistry 6 (2014): 842–844.  ($)

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