Phylo Blog

Sally Haslanger’s “Changing the Ideology and Culture of Philosophy: Not by Reason (Alone)” has been circulating around several blogs and listservs lately. The article, which is slated to come out in Hypatia next year, reviews the situation for women in current academic philosophy. Haslanger includes statistics on the top 20 departments as well as leading journals.

The statistics are surprising, and not just because of the low percentage of women represented. They’re surprising because we see so little hard data about the field. It takes a huge amount of time and effort on the part of Haslangers (and Nina Emery, who she credits) to assemble this data, and even Haslanger notes throughout the article that we need more data to get a full picture of the situation. (I have heard, however, that the APA is gearing up for a demographic study soon.)

This need got me thinking about how Phylo can help fill the gap. Our database will already contain lots of information on top departments (and hopefully publications as well). By simply coding individuals as male or female, we should be able to generate statistics on

• the percentage of women in top departments
• placement figures for women PhDs
• number of appointments across a career for women
• (the percentage of women published in journals)

and all of this for any time period! The initial data won’t be totally complete because it won’t include all the top departments (or probably publications). But it will provide some good historical data, which we seem to be totally lacking. And with frequent updates and more data, Phylo should be able to provide current statistics so anyone can get a snapshot of the field at any moment.

This potential has led us to plan a new, nonvisual interface for statistical information. Call it “stats.” In principle, it would allow any user to generate statistics on any kind of data that Phylo has. (Some of our displays already do this to visualize aggregate data.) It would also allow users to export data (possibly even raw data) to analyze further in more sophisticated programs.

There’s still a lot of detail to work out here, but “stats” might fill a huge gap in quantitative information about the field. Look for it in the Lab after our big launch.