Although classifier constructions generally aim for highly iconic depictions, like any other part of language they may be constrained by phonology. We compare utterances containing motion events between signers of Cena, an emerging rural sign language in Brazil, and Libras, the national sign language of Brazil, to investigate whether a difference in time-depth—a relevant factor in phonological reorganisation—influences trade-offs involving iconicity. First, we find that contrary to what may be expected, given that emerging sign languages exhibit great variation and favour highly iconic prototypes, Cena signers exhibit neither greater variation nor the use of more complex handshapes in classifier constructions. We also report a divergence from findings on Nicaraguan Sign Language (NSL) in how signers encode movement in a young language, showing that Cena signers tend to encode manner and path simultaneously, unlike NSL signers of comparable cohorts. Cena signers therefore pattern more like non-signing gesturers and signers of urban sign languages, including the Libras signers in our study. The study contributes an addition to the as-yet limited investigations into classifiers in emerging sign languages, demonstrating how different aspects of linguistic organisation, including phonology, can interact with classifier form.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.