Women in academia: a warning on selection bias in gender studies from the astronomical perspective

TL;DR

This paper critiques a recent study on mentorship in academia, highlighting how selection biases in astronomical research can lead to misleading causal claims about gender dynamics and the challenges women face in science.

Contribution

It exposes methodological flaws related to selection bias in a prominent gender study, emphasizing the importance of proper bias correction in causal inference.

Findings

Selection biases affect survey response rates and database choices.

Ignoring biases can lead to unwarranted causality claims.

Biases may obscure real obstacles faced by women in academia.

Abstract

The recent paper by AlShebli et al. (2020) investigates the impact of mentorship in young scientists. Among their conclusions, they state that female prot\'eg\'es benefit more from male than female mentorship. We herein expose a critical flaw in their methodological design that is a common issue in Astronomy, namely "selection biases". An effect that if not treated properly may lead to unwarranted causality claims. In their analysis, selection biases seem to be present in the response rate of their survey (8.35%), the choice of database, success criterion, and the overlook of the numerous drawbacks female researchers face in academia. We discuss these issues and their implications -- one of them being the potential increase in obstacles for women in academia. Finally, we reinforce the dangers of not considering selection bias effects in studies aimed at retrieving causal relations.