Academic Science Is Complicated, Like Scrabble

Blogging will continue to be light to nonexistent, as it's crunch time in a lot of ways at the moment, including our double tenure-track search. Which it would be inappropriate to talk about in any more detail than "Wow, this is a lot of work."

There are, however, two academic-job-related things that I probably ought to mention briefly. One is this Inside Higher Ed Essay about metaphors for the academic hiring process, which rightly points out a lot of the problems with the "lottery" analogy that lots of people like to use. In fact, Gerry Canavan argues, it's best understood as a game:

But it's a mistake to think that because the market is conditioned by luck it's reducible to luck, or absolutely irrational in some maximum sense. There's a lot about the way the academic job market functions that is quite rational, including (yes!) some genuinely meritocratic elements along the way.

If the rejected thesis is that the academic job market is meritocracy, and the failed antithesis is that the academic job market is a lottery, my suggestion is that perhaps the proper synthesis here is conceptualizing the academic job market as a game. Outcomes in games are structured by resources, strategies, and luck; games involve competition between parties with differing capabilities, using different strategies, interacting with a set of rules that may not make sense, much less be desirable, rational, or fair.

Specifically, Canavan argues that academic hiring is analogous to Scrabble, but I won't spoil that explanation. Click through and read it yourself. And I don't think it's wholly inappropriate to say that this article put me at risk of spraining my neck from all the nodding along.

The other academic-job-related thing getting a lot of traffic was also an injury risk, in this case from the eyeroll-inducing headline Academic Science Isn't Sexist, applied to the op-ed version of a massive meta-study of women in academic science (60-pagePDF). On the one hand, you know, you're not going to get a prominent placement in the New York Times without punching things up a little, but that's really a bit much.

And, look, the truth is this: Academic science is complicated. It's perfectly true that you can use a particular set of aggregate measures to argue that gender issues in academic science have improved immensely in recent years. You can also look at the exact same dataset in different ways and make the opposite argument. Both of these are true, and both are false, because academic science is made of people, and people are complicated.

And really, there isn't a whole lot more that can be said about that.