37.1187, Confs: Dealing with Biases in Language and Culture: Interdisciplinary Perspectives (Italy)

[The LINGUIST List]

LINGUIST List: Vol-37-1187. Tue Mar 24 2026. ISSN: 1069 - 4875.

Subject: 37.1187, Confs: Dealing with Biases in Language and Culture: Interdisciplinary Perspectives (Italy)

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Date: 23-Mar-2026
From: Elisabetta Jezek [elisabetta.jezek at unipv.it]
Subject: Dealing with Biases in Language and Culture: Interdisciplinary Perspectives


Dealing with Biases in Language and Culture: Interdisciplinary
Perspectives

Date: 01-Sep-2026 - 03-Sep-2026
Location: Pavia, Italy
Contact Email: ec2u at unipv.it

Linguistic Field(s): Discipline of Linguistics

Submission Deadline: 20-Apr-2026

The European Campus of City Universities (EC2U) Conference
Virtual Institute of Quality Education (VIQE)
https://ec2u.eu
Sept. 1-3, 2026, University of Pavia
Dealing with Biases in Language and Culture: Interdisciplinary
Perspectives
In an era where information is easily accessible and shared, the
ability to critically assess information with respect to potential
biases and misinformation is essential, particularly in a higher
education setting. The conference aims to bring together researchers
working on the pervasive presence of biases and misinformation in
texts, (Wardle and Derakhshan, 2017) and on related practices and
consequences in educational and professional contexts — from
misleading headlines like “New study proves coffee cures cancer”,
where sources are omitted and vague language is used (Rodrigo-Ginés et
al 2024), to stereotypes such as “Elderly people are not interested in
technology”, based on anti-elder prejudices (ageism) in cultural
contexts (Fiske 2017).
Biases have a long tradition of study in psychology, intercultural
studies, media studies, discourse studies and linguistics, among other
fields. Recently, bias studies have proven essential in artificial
intelligence, due to the tendency of large language models to inherit
biases from their training data and amplify them through their
technology; however, as noted by Blodgett et al. (2020), while AI
studies have laid vital groundwork, many fail to critically engage
with what constitutes bias in the first place. More generally, most
authors do not engage with the relevant literature outside of their
discipline, which constitutes a significant theoretical and
methodological drawback.
Against this background, the conference encourages an
interdisciplinary approach aiming to combine perspectives from
linguistics, discourse studies, intercultural communication,
psychology, cultural and literary studies, social and political
sciences, and law, with the goal of uncovering common ground and
finding synergies to study the phenomenon of biases, and foster the
engagement of the academic community in promoting a critical
information culture and awareness that safeguards accuracy and
fairness, through appropriate dissemination actions and
best-practices.
Conference Topics:
Contribution from different fields is welcome. Relevant topics for the
conference include, but are not limited to:
 - Analysis of cultural biases, stereotypes, prejudices and clichés
 - Bias taxonomies from different contexts and fields
 - Linguistic markers (i.e., syntactic, pragmatic, etc.) of biased
language
 - Cognitive bias (also from an evolutionary perspective)
 - Unintended (internalized) and unconscious bias
 - The role of biases in education and training
 - Critical awareness of bias in digital and media literacy practices
 - Bias, social interaction and social identities
 - Counteracting bias: ongoing practices in educational and
institutional contexts
 - Biases in AI and Natural Language Processing tasks: detection,
mitigation, measurement
 - Ethics and fairness concerning different types of biases
Abstract Submission:
The conference will feature oral and poster presentations and a round
table. The distribution of accepted contributions across both formats
(oral presentation or poster) will in no way reflect the quality of
the proposal, but will be based on the extent to which the content
adapts to each format.
Proposals for oral presentations (between 3,000 and 4,000 characters,
excluding references) must be submitted by April 20th to
ec2u at unipv.it, with the subject line "Bias 2026 Contribution Proposal"
in the email subject.
Proposals must be submitted in anonymized .pdf format, specifying the
presentation format (oral presentation or poster). Notifications will
be sent by May 6th.
Conference Date and Venue:
1-3 September, 2026
University of Pavia, Aula Bottigella, Palazzo San Tommaso, Piazza del
Lino 2, Pavia
Invited Speakers:
Edoardo Lombardi Vallauri (Roma Tre University, Italy)
Clara Keating (University of Coimbra, Portugal)
Scientific Committee:
Chair: Prof. Elisabetta Jezek, EC2U WP5 Representative, University of
Pavia
Prof. Ilaria Fiorentini, University of Pavia
Prof. Clara Keating, University of Coimbra
Prof. Silvia Monti, University of Pavia
Prof. Christoph Vatter, University of Jena
Local Organizing Committee:
Prof. Elisabetta Jezek
Prof. Ilaria Fiorentini
PhD Antonella Orologiaio
Dr. Costanza Marini
Dr. Serena Coschignano
References:
Blodgett, S.L. Barocas, S., Daumé III H. and H. Wallach. 2020.
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. In
Proceedings of the 58th Annual Meeting of the Association for
Computational Linguistics, pages 5454–5476, Online. Association for
Computational Linguistics.
Fiske, S. T. Prejudices in cultural contexts: Shared stereotypes
(gender, age) versus variable stereotypes (race, ethnicity, religion).
In Perspectives on Psychological Science 12 (2017) 791–799.
Rodrigo-Ginés, F. J., Carrillo-de-Albornoz, J., & Plaza, L. (2024). A
systematic review on media bias detection: What is media bias, how it
is expressed, and how to detect it. In Expert Systems with
Applications, 237, 121641.



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