Correspondence tests: uncovering biases against women in science

Part of the controversy surrounding affirmative action and other systems which give preferential treatment to minority groups comes from the ideal notion that people are judged on their merits -- and not their gender/race/etc [6]. In such an ideal world, for instance, a female scientist would be equally likely to be hired, given tenure, or accolades as an identical male scientist.

Science likes to bill itself as a meritocracy, in which scientists are evaluated only their work. A lot of the unease many scientists have about preferential treatment is that it goes against that ideal of meritocratic science [5]. So, it's worth asking: is a female scientist equally likely to be hired/tenured/etc as an identical male scientist?

Probably the best study design for probing this type of question are correspondence tests. These refer to studies where you describe either a female individual or a male individual to a group of participants -- keeping everything but gender (or race, ethnicity, etc) constant -- and see if participants respond differently to to the woman/man.

Correspondence tests are generally easier to run than audit studies, where you hire actors to be identical to one another except for gender/race/etc. Both types of studies are useful for identifying discrimination against particular groups. Another approach is to pair real male and female scientists with equal on-paper qualifications and see whether they are equally likely to be given tenure. This approach, however, suffers from the problem of pairing: are that female and male scientist really identical except for on-paper qualifications?

In this post, I'll be describing the results of three correspondence tests looking at discrimination against women in science. These three studies are also the only such studies that I know of to have been published since the 90s. (There's an older one from the 70s that is now a bit dated.)