@inproceedings{ousidhoum-etal-2026-beyond,
title = "Beyond Good Intentions: When Does the Framing of Multilingual and Low-Resource {NLP} Research Become a Caricature?",
author = "Ousidhoum, Nedjma and
Zambare, Noopur and
Abdalla, Mohamed",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.619/",
pages = "14209--14222",
ISBN = "979-8-89176-459-0",
abstract = "Building language technologies and conducting NLP research for low-resource languages{---}particularly when led by native speakers or involving participatory research practices{---}are often framed as means of addressing inequality, serving local communities, and, at times, contributing to *decolonisation*. In this paper, we examine recently published NLP and ML papers, focusing on the narratives used to characterise multilinguality, low-resource languages, and underrepresented cultures. We propose a framework for analysing research framings and identify recurring rhetorical patterns that may hinder accountability and constrain equitable knowledge production for{---}and by{---}underserved communities. We further assess the evidential basis of assertions regarding community benefit and find that such statements are often weakly supported or left unsubstantiated. Although community ownership and participation are frequently presented as key objectives, our analysis, supported by statistics from the ACL Anthology, suggests that research outputs more often prioritise resource creation and benchmarking{---}important but distinct goals{---}over evidence of broader structural change. We conclude by offering practical recommendations to help authors, reviewers, and readers critically assess these assertions and avoid potentially misleading framings."
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<abstract>Building language technologies and conducting NLP research for low-resource languages—particularly when led by native speakers or involving participatory research practices—are often framed as means of addressing inequality, serving local communities, and, at times, contributing to *decolonisation*. In this paper, we examine recently published NLP and ML papers, focusing on the narratives used to characterise multilinguality, low-resource languages, and underrepresented cultures. We propose a framework for analysing research framings and identify recurring rhetorical patterns that may hinder accountability and constrain equitable knowledge production for—and by—underserved communities. We further assess the evidential basis of assertions regarding community benefit and find that such statements are often weakly supported or left unsubstantiated. Although community ownership and participation are frequently presented as key objectives, our analysis, supported by statistics from the ACL Anthology, suggests that research outputs more often prioritise resource creation and benchmarking—important but distinct goals—over evidence of broader structural change. We conclude by offering practical recommendations to help authors, reviewers, and readers critically assess these assertions and avoid potentially misleading framings.</abstract>
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%0 Conference Proceedings
%T Beyond Good Intentions: When Does the Framing of Multilingual and Low-Resource NLP Research Become a Caricature?
%A Ousidhoum, Nedjma
%A Zambare, Noopur
%A Abdalla, Mohamed
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F ousidhoum-etal-2026-beyond
%X Building language technologies and conducting NLP research for low-resource languages—particularly when led by native speakers or involving participatory research practices—are often framed as means of addressing inequality, serving local communities, and, at times, contributing to *decolonisation*. In this paper, we examine recently published NLP and ML papers, focusing on the narratives used to characterise multilinguality, low-resource languages, and underrepresented cultures. We propose a framework for analysing research framings and identify recurring rhetorical patterns that may hinder accountability and constrain equitable knowledge production for—and by—underserved communities. We further assess the evidential basis of assertions regarding community benefit and find that such statements are often weakly supported or left unsubstantiated. Although community ownership and participation are frequently presented as key objectives, our analysis, supported by statistics from the ACL Anthology, suggests that research outputs more often prioritise resource creation and benchmarking—important but distinct goals—over evidence of broader structural change. We conclude by offering practical recommendations to help authors, reviewers, and readers critically assess these assertions and avoid potentially misleading framings.
%U https://aclanthology.org/2026.emnlp-main.619/
%P 14209-14222
Markdown (Informal)
[Beyond Good Intentions: When Does the Framing of Multilingual and Low-Resource NLP Research Become a Caricature?](https://aclanthology.org/2026.emnlp-main.619/) (Ousidhoum et al., EMNLP 2026)
ACL