Quantifying gender bias towards politicians in cross-lingual language models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AZ5U4IK2E" target="_blank" >RIV/00216208:11320/23:Z5U4IK2E - isvavai.cz</a>

Result on the web

<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277640" target="_blank" >https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277640</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0277640" target="_blank" >10.1371/journal.pone.0277640</a>

Result language

angličtina

Original language name

Quantifying gender bias towards politicians in cross-lingual language models

Original language description

"Recent research has demonstrated that large pre-trained language models reflect societal biases expressed in natural language. The present paper introduces a simple method for probing language models to conduct a multilingual study of gender bias towards politicians. We quantify the usage of adjectives and verbs generated by language models surrounding the names of politicians as a function of their gender. To this end, we curate a dataset of 250k politicians worldwide, including their names and gender. Our study is conducted in seven languages across six different language modeling architectures. The results demonstrate that pre-trained language models’ stance towards politicians varies strongly across analyzed languages. We find that while some words such as dead, and designated are associated with both male and female politicians, a few specific words such as beautiful and divorced are predominantly associated with female politicians. Finally, and contrary to previous findings, our study suggests that larger language models do not tend to be significantly more gender-biased than smaller ones."

Czech name

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Czech description

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Type

J_ost - Miscellaneous article in a specialist periodical

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

"Plos one"

ISSN

1932-6203

e-ISSN

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Volume of the periodical

18

Issue of the periodical within the volume

11

Country of publishing house

US - UNITED STATES

Number of pages

24

Pages from-to

1-24

UT code for WoS article

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EID of the result in the Scopus database

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