@inproceedings{sjavik-touileb-2025-ableism,
title = "Ableism, Ageism, Gender, and Nationality bias in {N}orwegian and Multilingual Language Models",
author = "Sj{\r{a}}vik, Martin and
Touileb, Samia",
editor = "Fale{\'n}ska, Agnieszka and
Basta, Christine and
Costa-juss{\`a}, Marta and
Sta{\'n}czak, Karolina and
Nozza, Debora",
booktitle = "Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP)",
month = aug,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.gebnlp-1.32/",
doi = "10.18653/v1/2025.gebnlp-1.32",
pages = "379--392",
ISBN = "979-8-89176-277-0",
abstract = "We investigate biases related to ageism, ableism, nationality, and gender in four Norwegian and two multilingual language models. Our methodology involves using a set of templates. constructed around stimuli and attributes relevant to these categories. We use statistical and predictive evaluation methods, including Kendall{'}s Tau correlation and dependent variable prediction rates, to assess model behaviour and output bias. Our findings indicate that models frequently associate older individuals, people with disabilities, and poorer countries with negative attributes, potentially reinforcing harmful stereotypes. However, most tested models appear to handle gender-related biases more effectively. Our findings indicate a correlation between the sentiment of the input and that of the output."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sjavik-touileb-2025-ableism">
<titleInfo>
<title>Ableism, Ageism, Gender, and Nationality bias in Norwegian and Multilingual Language Models</title>
</titleInfo>
<name type="personal">
<namePart type="given">Martin</namePart>
<namePart type="family">Sjåvik</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Samia</namePart>
<namePart type="family">Touileb</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Agnieszka</namePart>
<namePart type="family">Faleńska</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christine</namePart>
<namePart type="family">Basta</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marta</namePart>
<namePart type="family">Costa-jussà</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Karolina</namePart>
<namePart type="family">Stańczak</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Debora</namePart>
<namePart type="family">Nozza</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Vienna, Austria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-277-0</identifier>
</relatedItem>
<abstract>We investigate biases related to ageism, ableism, nationality, and gender in four Norwegian and two multilingual language models. Our methodology involves using a set of templates. constructed around stimuli and attributes relevant to these categories. We use statistical and predictive evaluation methods, including Kendall’s Tau correlation and dependent variable prediction rates, to assess model behaviour and output bias. Our findings indicate that models frequently associate older individuals, people with disabilities, and poorer countries with negative attributes, potentially reinforcing harmful stereotypes. However, most tested models appear to handle gender-related biases more effectively. Our findings indicate a correlation between the sentiment of the input and that of the output.</abstract>
<identifier type="citekey">sjavik-touileb-2025-ableism</identifier>
<identifier type="doi">10.18653/v1/2025.gebnlp-1.32</identifier>
<location>
<url>https://aclanthology.org/2025.gebnlp-1.32/</url>
</location>
<part>
<date>2025-08</date>
<extent unit="page">
<start>379</start>
<end>392</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Ableism, Ageism, Gender, and Nationality bias in Norwegian and Multilingual Language Models
%A Sjåvik, Martin
%A Touileb, Samia
%Y Faleńska, Agnieszka
%Y Basta, Christine
%Y Costa-jussà, Marta
%Y Stańczak, Karolina
%Y Nozza, Debora
%S Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP)
%D 2025
%8 August
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-277-0
%F sjavik-touileb-2025-ableism
%X We investigate biases related to ageism, ableism, nationality, and gender in four Norwegian and two multilingual language models. Our methodology involves using a set of templates. constructed around stimuli and attributes relevant to these categories. We use statistical and predictive evaluation methods, including Kendall’s Tau correlation and dependent variable prediction rates, to assess model behaviour and output bias. Our findings indicate that models frequently associate older individuals, people with disabilities, and poorer countries with negative attributes, potentially reinforcing harmful stereotypes. However, most tested models appear to handle gender-related biases more effectively. Our findings indicate a correlation between the sentiment of the input and that of the output.
%R 10.18653/v1/2025.gebnlp-1.32
%U https://aclanthology.org/2025.gebnlp-1.32/
%U https://doi.org/10.18653/v1/2025.gebnlp-1.32
%P 379-392
Markdown (Informal)
[Ableism, Ageism, Gender, and Nationality bias in Norwegian and Multilingual Language Models](https://aclanthology.org/2025.gebnlp-1.32/) (Sjåvik & Touileb, GeBNLP 2025)
ACL