Hannah Devinney

they/them (en) hen/hen (sv)

About Me

I'm a PhD student at the Department of Computing Science, in association with the Graduate School for Gender Studies, at Umeå University, supervised by Henrik Björklund and Jenny Björklund. My thesis in the field of computer science, more specifically within NLP.

Thesis (monograph)

My thesis work explores gendered biases, trans and nonbinary inclusivity, and queer representation within Natural Language Processing (NLP) through a feminist and intersectional lens. The thesis tackles this in three key areas: the ways in which "gender" is theorized and operationalized by researchers investigating gender bias in NLP; gendered associations within datasets used for training language technologies; and the representation of queer (particularly trans and nonbinary) identities in the output of both low-level NLP models and large language models (LLMs). Throughout, I demonstrate that nonbinary people and genders are erased by bias in NLP tools and datasets, but also by research/ers attempting to address gender biases. Via a case study, I explore ways to mitigate some of this disparity in one foundational part of a "classic" NLP pipeline, part-of-speech tagging.

Completed Papers (organized by topic)

"Gender" in Gender Bias

Gender Biases in Data

Model Output and Representation

Planned Papers for inclusion in the thesis:

Papers not appearing in the thesis: