In a new paper in the Journal of Language Evolution, Tessa Verhoef and I analyse reviewer ratings for papers submitted to the EvoLang conference between 2012 and 2016 . In the most recent conference, we trialed double-blind review for the first time, and we wanted to see if hiding the identity of authors revealed any biases in reviewers’ ratings.
We found that:
- Proportionately few papers are submitted from female first authors.
- In single-blind review, there was no big difference in average ratings for papers by male or female first authors …
- … but female first-authored papers were rated significantly higher than male first authored papers in the double-blind condition.
There are many possible explanations of these findings, but they are indicative of a bias against female authors. This fits with a wider literature of gender biases in science. We suggest that double-blind review is one tool that can help reduce the effects of gender biases, but does not tackle the underlying problem directly. We were pleased to see better representation of women on the most recent EvoLang talks and plenary speaker list, and look forward to making our field more inclusive.
The paper is available, free and open-access, at the Journal of Language Evolution. The data and statistical code is also available on github.