A bit more about gender and science

After my last post, some friends of mine drew my attention to some useful resources. This is a subject I’m strongly interested in, but I’m definitely not an expert, so I’m grateful for additional information.

My friend Rig Hernandez is director of Project OXIDE, which runs workshops “to reduce inequities that have historically led to disproportionate diversity representation on academic faculties.” Their web site is still under development, but there’s a Diversity Portal which contains what appear to be useful links to more information. Rig also reminded me about Project Implicit, a bunch of studies attempting to measure implicit (unconscious) biases.

I want to expand a bit on one thing I mentioned in my last post. The big difference between the recent study and a lot of the previous work I’ve heard about is that this was a controlled study: rather than examining real-world data, in which there are all kinds of hard-to-control variables, the researchers made sure that the applications people reviewed were identical in every way except the applicant’s gender.

I certainly don’t claim that the real-world studies aren’t worthwhile. I think that they can provide valuable insights. But there’s one thing they can never do. They can’t distinguish between the  hypothesis that invidious discrimination is at work and the hypothesis that the dearth of women in science is due to actual differences between men and women (whether biological or cultural). If (unlike me) you’re partial to the Larry Summers hypothesis, for instance, you’ll be able to interpret the results of the real-world studies in that light. But you can’t interpret the more recent study in that way.

If you think that gender bias is a problem (which I do) and want to advocate for policy changes to fix it (which I do), then you need to convince people who don’t already agree with you. Those people can much more easily ignore the results of studies with all sorts of uncontrolled variables. That’s why I think the new study is especially worth trumpeting.

For comparison, consider a study that examined recommendation letters written for actual faculty job applicants. This study showed that letter-writers used different sorts of words to characterize male and female applicants: women tended to be described using “communal” words, men using “agentic” words. Moreover, there was a negative correlation between the use of communal words and the perceived hireability of the applicant.

Leave aside for now any correlation-causation qualms you might have,  and suppose that this study showed that the use of communal words caused female applicants to fare more poorly. You still can’t tell whether that’s because of implicit bias on the part of the letter writers or because the female applicants actually are, on average, more “communal” (whatever that means).

For what it’s worth, in this case I happen to find the implicit-bias hypothesis very plausible, but there’s no way to know for sure from this study. Scientists tend to be a skeptical bunch, so if you’re trying to convince a scientist who’s not already a believer that implicit bias is a problem, this sort of study is probably not going to do it.

(One thing you should certainly take away from that study: if you’re writing a recommendation letter for a female candidate (and you want her to get the job), pay attention to your use of communal and agentic words.)

2 Responses to “A bit more about gender and science”

  1. Of course, one can move beyond just male/female to the question of gender bias, where gender is understood in a broader sense.

    Four points: Those concerned with equality should be concerned with equality in every field, not just their own field and not just fields which are generally seen as positive. Second, one should not assume that a lack of equality is due to a lack of opportunity. There are certainly fields where this is the case, but, logically, it does not automatically follow that any lack of equality is due to lack of opportunity. If one does make this assumption, then forcing equality when the reason for the lack of it is not the lack of equal opportunity is not a desirable goal. Third, don’t look exclusively at the financial aspects. Fourth: be inclusive. LGBT (lesbian, gay, bi and trans) is now the standard initialism (though it grew out of less inclusive terms and there are proposed more inclusive terms which are not yet that common). While it might be more or less accepted in some societies to be in a long-term monogamous homosexual relationship, polyamorous people are in some respects in the same situation gays were in 30 or 40 years ago.

  2. Brent Follin says:

    This doesn’t directly address the gender gap in the field, but there was a recent experiment* that showed spending a half hour of class time writing about personal interests (not necessarily related to physics) eliminated the gender gap in success in introductory physics classes (as measured in final exam grades). There is definitely a long path between better grades in Physics 101 and more female role models in the field (the likely long-term answer to the gender gap in physics), but definitely a practical starting point.

    *which I read about here: http://blogs.discovermagazine.com/notrocketscience/2010/11/25/15-minute-writing-exercise-closes-the-gender-gap-in-university-level-physics/

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