79 - The glass ceiling in NLP, with Natalie Schluter

In this episode, Natalie Schluter talks to us about a data-driven
analysis of career progression of male vs. female researchers in
NLP through the lens of mentor-mentee networks based on ~20K papers
in the ACL anthology. Directed edges in the network describe a
mentorship relation from the last author on a paper to the last
author, and author names were annotated for gender when possible.
Interesting observations include the increase of percentage of
mentors (regardless of gender), and an increasing gap between the
fraction of mentors who are males and females since the early
2000s. By analyzing the number of years between a researcher’s
first publication and the year at which they achieve mentorship
status at threshold T, defined by publishing T or more papers as a
last author, Natalie also found that female researchers tend to
take much longer to be mentors. Another interesting finding is that
in-gender mentorship is a strong predictor of the mentee’s success
in becoming mentors themselves. Finally, Natalie describes the bias
preferential attachment model of Avin et al. (2015) and applies it
to the gender-annotated mentor-mentee network in NLP, formally
describing a glass ceiling in NLP for female researchers.
https://www.semanticscholar.org/paper/The-glass-ceiling-in-NLP-Schluter/abfb1eb2d27194269503afce8be45909c8f86f4b
See also: Homophily and the glass ceiling effect in social
networks, at ITCS 2015, by Chen Avin, Barbara Keller, Zvi Lotker,
Claire Mathieu, David Peleg, and Yvonne-Anne Pignolet.
https://www.semanticscholar.org/paper/Homophily-and-the-Glass-Ceiling-Effect-in-Social-Avin-Keller/23dcb12dd918fcf29f7abb287dd466478031b8ff
Apologies for the relatively poor audio quality on this one; we did
our best.