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Register a new userUnconscious Gender Bias in Academia: from PhD Students to Professors
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K. Poppenhaeger
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In an academic landscape where female physicists are still strongly underrepresented, underlying causes like unconscious gender bias deserve specific attention. Members of academia are often not aware of their intrinsic, hence unconscious, biases; this can have negative effects on students and staff at all career levels. At the Queens University Belfast, I have developed and conducted a workshop on unconscious gender bias awareness at the School of Mathematics and Physics. The first installment of the workshop was attended by 63 members of the School, among them 26 academic staff (lecturer level and above). Participants attended an informational talk followed by a discussion session, and then took part in the Harvard Implicit Association Test for association of gender with science. The participants self-reported their results and their previous expectations, followed by a group discussion. Here I present the observed magnitude of unconscious gender bias and summarise the discussion points of the participants. The outcomes that bias can have on the success of physics students as well as the careers of physicists in an academic context will be highlighted. Putting the results into context, I discuss steps forward to make physics a level playing field for all genders.
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The recent paper by AlShebli et al. (2020) investigates the impact of mentorship in young scientists. Among their conclusions, they state that female proteges 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.
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