Beyond Obscuration and Visibility: Thoughts on the Different Strategies of Gender-Fair Language in Italian

  • Martina Rosola*
  • , Simona Frenda
  • , Alessandra Teresa Cignarella
  • , Matteo Pellegrini
  • , Andrea Marra
  • , Mara Floris
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This study focuses on the growing importance of gender-fair language and explores innovative strategies proposed also in other languages to avoid gender-specific endings. We present a set of guidelines for the annotation and reformulation of gender-(un)fair texts and their application to a corpus of 1, 024 portions of university administrative documents in Italian. Overall, the guidelines presented in this study prove to be valuable both practically and theoretically. They help identify and address non-inclusive expressions while highlighting the complexities of obscuration and visibility in gender-fair language reformulation. In addition, the statistical analysis of the created corpus shows how administrative texts tend to contain gender-unfair language, especially the masculine overextended expressions, showing the need to adopt specific and complete guidelines that lead (and support the staff training) to the use of a more gender-fair language.

Original languageEnglish
Title of host publicationProceedings of the Ninth Italian Conference on Computational Linguistics (CLiC-it 2023)
PublisherCEUR-WS
Pages369–378
Number of pages10
Volume3596
ISBN (Print) 9791255000846
Publication statusPublished - 30 Nov 2023
Event9th Italian Conference on Computational Linguistics 2023 - Venice, Italy
Duration: 30 Nov 20232 Dec 2023
https://clic2023.ilc.cnr.it/

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS
ISSN (Print)1613-0073

Conference

Conference9th Italian Conference on Computational Linguistics 2023
Abbreviated titleCLiC-it 2023
Country/TerritoryItaly
CityVenice
Period30/11/232/12/23
Internet address

Keywords

  • Annotation Schema
  • Gender-fair language
  • Italian

ASJC Scopus subject areas

  • General Computer Science

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