Public Discussion Affects Question Asking at Academic Conferences

Am J Hum Genet. 2019 Jul 3;105(1):189-197. doi: 10.1016/j.ajhg.2019.06.004. Epub 2019 Jun 27.

Abstract

Women are under-represented in science, technology, engineering, and mathematics (STEM). Despite the recent emphasis on diversity in STEM, our understanding of what drives differences between women and men scientists remains limited. This, in turn, limits our ability to intervene to level the playing field. To quantify the representation and participation of women and men at academic meetings in human genetics, we developed high-throughput and crowd-sourced approaches focused on question-asking behavior. Question asking is one voluntary and self-initiated scientific activity we can measure. Here we report that women ask fewer questions than expected regardless of their representation in talk audiences. We present evidence that external barriers affect the representation of women in STEM. However, differences in question-asking behavior suggest that internal factors also impact women's participation. We then examine the effects of specific interventions and show that wide public discussion of the relative under-participation of women in question-and-answer sessions alters question-asking behavior. We suggest that engaging the community in such projects promotes visibility of diversity issues at academic meetings and allows for efficient data collection that can be used to further explore and understand differences in conference participation.

Keywords: bioinformatics; culture; gender; gender studies; genetics; quantitative social sciences; science; science and society.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Communication*
  • Congresses as Topic / organization & administration
  • Congresses as Topic / statistics & numerical data*
  • Female
  • Humans
  • Male
  • Natural Science Disciplines / standards*
  • Public Opinion*
  • Research Personnel / psychology*
  • Research Personnel / statistics & numerical data
  • Sex Factors
  • Societies, Scientific / organization & administration
  • Societies, Scientific / statistics & numerical data*