Is bias “yesterday’s problem”? Addition

When I wrote this yesterday my computer was having one of those stubborn microscoft moments. I’m not sure what it was doing, but it kept on for over two hours, opening pages I had closed and vice versa. I was rattled enough to forget a very important source which, computer willing, I’ll put in at the current end of this post.

The staggering news that women form only 17% of full time philosopher professors might make one disinclined to believe there’s no bias against women in academic disciplines. But maybe the math-intensive disciplines are more advanced. Indeed, in a widely circulated paper, Ceci and Williams argue that biased judgments regarding paper acceptance, hiring and grant allocations are a thing of the past in science and engineering. As their abstract has it

We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, ra

ther than in addressing meaningful limitations deterring women’s participation in science, technology, engineering, and mathematics careers today

Their article cites lots and lots of data. So what could be wrong with it? Actually, a number of things:

1. Though they target math-intensive fields, most of their facts concern the life sciences, which are hardly the most theoretical and math-intensive and where women have made particularly significant strides. The two exceptions are data sets from extremely large, multidisciplinary groups, where individual differences in fields can wash out.  (Similar points are made by Female Science Professor.)

2. They employ a false dichotomy. If women are not flourishing in a field the possible explanations are not limited to quantifiable bias in hiring, etc., or choices women make. As posts on what it is like to be a woman in philosophy show, there are many ways in which sexism cancreate burdens for women.

3. An underlying assumption they make: They assume that if a field has X percent of women applicants, then if women get X percent of grants, we know bias is not operating. But is that right? Perhaps the women who survive training in a field where they have few mentors and surmount barriers most men may have little knowledge of, might actually be better. At least we cannot assume they aren’t.

One might object to the last claim that it would make showing that there is no bias quite hard.  Fortunately, that is not right.  We might have such evidence at some point if we find there are no longer any of the other signs of bias.  These include the anecdotal evidence from very reliable sources, and studies and testing, such as the IAT ( For anecdotes, check out the links in #1 and #2 above.

Added: A very good source for some of the systematic studies of bias in here at NSF. Here is a pamphlet discussing some actions faculty can take to create a more equitable work place.