@inproceedings{fijavz-etal-2026-thesis,
title = "Thesis Proposal: Measuring Prejudice at Scale",
author = "Fijav{\v{z}}, Zoran and
Pollak, Senja and
Bajt, Veronika",
editor = "Baez Santamaria, Selene and
Somayajula, Sai Ashish and
Yamaguchi, Atsuki",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 4: Student Research Workshop)",
month = mar,
year = "2026",
address = "Rabat, Morocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-srw.56/",
pages = "760--775",
ISBN = "979-8-89176-383-8",
abstract = "This thesis proposal addresses methodological gaps in applying NLP to social science by shifting from categorical classification to comparative scaling of grounded constructs. We first extend predictive capacity on existing specialized political datasets with prompt optimization and distillation approaches. We then develop an active learning framework for efficient comparative annotation to scale latent dimensions from large corpora. Finally, we apply this pipeline to measure benevolent sexism in Slovenian media and migration threat perception in parliamentary discourse. This work establishes a scalable workflow for moving NLP from ad-hoc classification to theoretically grounded comparative measurement."
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%0 Conference Proceedings
%T Thesis Proposal: Measuring Prejudice at Scale
%A Fijavž, Zoran
%A Pollak, Senja
%A Bajt, Veronika
%Y Baez Santamaria, Selene
%Y Somayajula, Sai Ashish
%Y Yamaguchi, Atsuki
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-383-8
%F fijavz-etal-2026-thesis
%X This thesis proposal addresses methodological gaps in applying NLP to social science by shifting from categorical classification to comparative scaling of grounded constructs. We first extend predictive capacity on existing specialized political datasets with prompt optimization and distillation approaches. We then develop an active learning framework for efficient comparative annotation to scale latent dimensions from large corpora. Finally, we apply this pipeline to measure benevolent sexism in Slovenian media and migration threat perception in parliamentary discourse. This work establishes a scalable workflow for moving NLP from ad-hoc classification to theoretically grounded comparative measurement.
%U https://aclanthology.org/2026.eacl-srw.56/
%P 760-775
Markdown (Informal)
[Thesis Proposal: Measuring Prejudice at Scale](https://aclanthology.org/2026.eacl-srw.56/) (Fijavž et al., EACL 2026)
ACL
- Zoran Fijavž, Senja Pollak, and Veronika Bajt. 2026. Thesis Proposal: Measuring Prejudice at Scale. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 760–775, Rabat, Morocco. Association for Computational Linguistics.