There’s been a lot of bloggage recently about a new study in the Proceedings of the National Academy of Sciences indicating bias toward male students on the part of faculty who thought they were evaluating an application for a laboratory manager. Half of the faculty in the study were given an application with “Jennifer” at the top, the other half one with “John” as the first name, and both male and female faculty rated the male student more highly, and would offer the male student a higher salary. Sean Carroll and Ilana Yurkiewicz talk about the study and the results in more detail.
So, without getting into the details of the study, let’s say I’m convinced by this that gender bias is a problem in hiring. Presumably, this would extend up to the faculty level, as well, where it’s even more important to take bias out of the process because the stakes are higher in a lot of respects. Now, one possible solution to this would be to try to make the hiring process blind– as has been shown effective in orchestra auditions, for example. So, if you wanted to make the faculty hiring process gender-blind (or race-blind, for that matter), how would you do that?
(This is not entirely a theoretical question, by the way, as there’s a non-trivial chance we will be hiring a visiting faculty member in the very near future, and a tenure-track job is not out of the question down the road a bit.)
Obviously, you couldn’t do a blind search all the way through, because at some point you’re going to invite a few candidates to campus for interviews. But would it be possible to do the search blind up to that point?
At first glance, it seems like a Hard Problem, because the materials that figure into a typical search are kind of difficult to anonymize to the necessary degree. For a faculty search, we ask for some statements from the candidate about their teaching and research, a CV, and three letters of recommendation. The statements are not necessarily gendered– though we occasionally get “As a woman in physics, I…” statements, those could probably be avoided. The CV is somewhat more problematic– while you could blank out the name at the top, the really important thing is the publication list, and there it’s a little hard to avoid identifying the author who is common to all the papers. It’s not a complete show-stopper– a lot of authors are identified only by initials, not full first names– but it’s trickier. Reference letters are the hardest of all, unless the people writing the letters are extremely scrupulous about avoiding gendered pronouns– in fact, we have sometimes had to resort to the reference letters for the purpose of identifying the gender of applicants with unusual names when we’re required to give some accounting of the number of applicants from underrepresented groups at the conclusion of a job search.
None of those are completely insurmountable– if the requirement were stated in the job ad, you could probably get the letter-writers to search-and-replace “Firstname” with “Dr. Lastname,” and the publication lists are primarily used to count the number of publications and the journals where they appeared, and only rarely does anyone look them up to be able to check the names. In the spherical frictionless world where support departments are supportive, you could probably have somebody in Human Resources transcribe any necessary documents and remove gender references. (We’ll pause here to give those who have had contact with real-world Human Resources offices a chance to stop laughing and collect themselves.) It’s not impossible, but the extra resources required make it seem like a bit of a hard sell.
I assume somebody must have thought seriously about this before, though I don’t have the time to Google for it. If there’s an effective and relatively simple way to go about this, though, I’d love to hear it. Even better would be a way to convince other faculty of the need for going through whatever additional hassle would be involved.
(The alternative, of course, is to be even more gender conscious, and make an affirmative effort to give extra consideration to applications from women (and other underrepresented groups, if we extend this to include other factors). I am somewhat skeptical that this would really be effective, though, as the judgments involved are inherently kind of subjective and prone to the semi-unconscious decision making that Kahneman talks about. And it’s not like we’re not already getting a lot of exhortations to hire from underrepresented groups– we’re aware of the general problem. I’d have more confidence in something that eliminated the possibility of bias at an earlier stage, shifting the effort involved to somebody else.)
(Obligatory disclaimer: Nothing in the above should be taken as a statement of institutional policy or a binding commitment to do anything in particular when next we hire. This is personal opinion and speculation, nothing more. If this post generates suggestions that seem workable and fit within existing institutional policies and applicable state and federal laws, I may try to implement them. My ability to force any kind of policy change is pretty much nonexistent, though, so I can not promise anything.)