The social structure of signing communities and lexical variation: A cross-linguistic comparison of three unrelated sign languages

Hannah Lutzenberger, Katie Mudd, Rose Stamp, Adam Schembri

Research output: Contribution to journalArticlepeer-review


Claims have been made about the relationship between the degree of lexical variation and the social structure of a sign language community (e.g., population size), but to date there exist no large-scale cross-linguistic comparisons to address these claims. In this study, we present a cross-linguistic analysis of lexical variation in three signing communities: Kata Kolok, Israeli Sign Language (ISL) and British Sign Language (BSL). Contrary to the prediction that BSL would have the lowest degree of lexical variation because it has the largest population size, we found that BSL has the highest degree of lexical variation across the entire community (i.e., at the global level). We find, however, that BSL has the lowest degree of lexical variation at the local level, i.e., within clusters of participants who group most similarly lexically. Kata Kolok and ISL, on the other hand, exhibit less of a distinction between variation at the global and local levels, suggesting that lexical variation does not pattern as strongly within subsets of these two communities as does BSL. The results of this study require us to reassess claims made about lexical variation and community structure; we need to move towards an approach of studying (lexical) variation which treats communities equally on a theoretical level and which respects the unique social-demographic profile of each community when designing the analysis by using a community-centered approach.

Original languageEnglish
Pages (from-to)1-40
Number of pages40
Issue number1
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2023 The Author(s).


This work was supported by a European Research Council Advanced Grant (ERC-ADG 885220 SignMorph) awarded to Adam Schembri, by an Amsterdam Brain and Cognition (ABC) Talent Grant awarded to Katie Mudd, and by the Israeli Science Foundation (grant no. 2757/20) and the Data Sciences Institute small grant awarded to Rose Stamp. For the Kata Kolok data, we would like to thank all Kata Kolok signers, especially those who participated in this study and our research assistants assisting with data collection, especially Ni Made Sumarni. For the ISL data, we gratefully thank all those who contributed towards the Corpus of ISL project. Thanks to Eliran Ben HaRosh, Shlomi Biton, Karin Biton, Dana Kadosh, Sara Lanesman, Debi Menashe, Ora Ohanin, and Avihai Shbo, and a special thanks to all of the deaf individuals who agreed to participate. For the BSL data, we would like to thank Jordan Fenlon, Ramas McRae (formerly Rentelis), Sally Reynolds, Kearsy Cormier, and other members of the BSL Corpus team, as well as the 249 members of the British deaf community who gave up their time to participate in the project. We also thank Yannick Jadoul, Marnix van Soom, and Bart de Boer for their helpful feedback and ideas for the analysis and three anonymous reviewers for very helpful comments which were invaluable for improving this manuscript.

FundersFunder number
Avihai Shbo
Data Sciences Institute
Jordan Fenlon
European Research CouncilERC-ADG 885220
Institut Franco-Allemand de Recherches de Saint-Louis
Israel Science Foundation2757/20
Amsterdam Brain and Cognition


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