Two Centuries of Sexism in British Parliament: A Computational Analysis of Women’s Representation in the Hansard Corpus
Published:
Mandira Sawkar, Omar Khursheed, Dr. Ashique KhudaBukhsh
Description: Built an LLM-as-judge pipeline to mine 6.7M UK parliamentary speeches for suffrage debates, achieving stance-classification agreement with human experts (k=0.71) that exceeded inter-annotator agreement itself (k=0.64). Designed a psychology-grounded sexism taxonomy and applied it at corpus scale, quantifying that anti-suffrage speeches were 2.6x more likely to contain sexist rhetoric (54% vs. 21%) and revealing a century-long shift from hostile to benevolent sexism..
My contribution: Designed the taxonomy and the human annotation protocol. Conducted prompt-tuning, statistical analysis of sexist rhetoric in the Hansard corpus and co-authored the resulting ARR paper.
Resources: [Code]