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Calibrate to innovate: Community age vectors and the real time incrementation of language change

Published online by Cambridge University Press:  07 October 2020

Sophie Holmes-Elliott Open the ORCID record for Sophie Holmes-Elliott [Opens in a new window]
Sophie Holmes-Elliott*
Affiliation:
University of Southampton, UK
*
Address for correspondence: Department of Linguistics, Queen Mary, University of London, E1 4NS, United Kingdom[email protected]
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Abstract

This study investigates children's real time incrementation of language change as it is impacted by community-wide patterns of linguistic variability. The investigation combines apparent time analyses across an age-stratified sample of adult speakers, with real time analyses across a panel of speakers spanning childhood to adolescence. Three variables are analysed: GOOSE-fronting, a socially unmarked change; TH-fronting, a socially stigmatised, rapidly expanding change; and T-glottaling, a socially stigmatised, steadily shifting change. Variables are selected based on their social and generational profiles which present learners with more or less challenging community patterns to extract. Real time analyses confirm that community variance impacts on speakers’ ability to increment change in real time. Findings provide support for the momentum-based model of language change and builds on Labov's (2012:267) theory of the ‘outward orientation’ of children, which views learners as capable of extracting age vectors from generational differences. (Language change, incrementation, real time, GOOSE-fronting, TH-fronting, T-glottaling)*

Type
Articles
Information
Language in Society , Volume 50 , Issue 3 , June 2021 , pp. 441 - 474
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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Footnotes

*

This research was supported by the British Academy (grant no. SG-162287). Many thanks to James Turner, the project research assistant. I am grateful to the editors of Language in Society and two anonymous reviewers who helped to improve this manuscript. I would also like to thank Jennifer Smith, Erez Levon, and the audience at UK LVC 2019 for their feedback on an earlier version of the work. Any remaining shortcomings are my own. Special thanks to my speakers from Hastings who made this research possible. I would like to acknowledge that this research was conducted at the Department of Modern Languages and Linguistics, University of Southampton. However, my current affiliation is Queen Mary University of London.

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