Don´t Stop Me Now: Gender Attitudes in Academic Seminars Through Machine Learning

Mateo Seré

No 2309, Working Papers from Herman Deleeck Centre for Social Policy, University of Antwerp

Abstract: This study, utilizing a novel dataset from economic seminar audio recordings, investigates gender-based peer interactions, structured around five key findings: (i) Female speakers are interrupted more frequently, earlier, and differently than males; (ii) the extra interruptions largely stem from female, not male, audience members; (iii) male participants pose fewer questions but more comments to female presenters; (iv) audience members of both genders interrupt female speakers with a more negative tone; (v) less senior female presenters receive more interruptions from women. Control variables include seminar series, presentation topic, and factors like presenter affiliation, seniority, and department ranking.

Date: 2023-07
New Economics Papers: this item is included in nep-big and nep-cmp
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