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Segment count and weight in y-adjective comparatives: inroads that bite off more than one can chew!

Published online by Cambridge University Press:  11 October 2022

DEBORAH CHUA*
Affiliation:
National Institute of Education Nanyang Technological University NIE3-B1-19 1 Nanyang Walk Singapore 637616 Singapore debchua2004@gmail.com deborah.chua@nie.edu.sg

Abstract

Adjectival syllable count, often used to predict English comparatives more versus -er, is of little help in predicting the comparatives of adjectives ending in <y>, pronounced /i/, here called the y-adjectives. Examples of y-adjectives include silly and worthy. This article considers whether the phonemic segment count (segment count) and penultimate syllable weight (penultimate weight) of y-adjectives may serve as alternatives to syllable count in predicting more versus -er. The segment count and penultimate weight of relevant y-adjective tokens from a set of diachronic corpora are studied, alongside the tokens’ morphological complexity and period of occurrence in two separate, parallel sets of mixed-effects models. Syllabification principles for penultimate weight coding differentiate the two sets of modelling. Findings converge on segment count as a predictor of the comparative form, while the role of morphological complexity remains less clear, emerging significantly from one set of modelling but not the other. A rethinking of adjectival length based on segment count is advanced for our understanding of y-adjective comparatives. Discussed also are downstream implications of variant syllabification theories on accounts of y-adjective comparatives, together with insights shed on morphophonological intersections and the potential place of English y-adjective comparatives within the ambit of English alternations.

Type
Research Article
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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Footnotes

I would like to thank Professor Laurie Bauer for his insightful feedback and suggestions on previous drafts of this article and for his help in verifying some of my transcriptions. I am grateful to Professor Paul Warren for having introduced me to mixed-effects modelling. I would also like to thank two reviewers of English Language and Linguistics for their helpful comments on versions of this article. The initial data and thinking that led to this article would not have come about without my PhD candidature at Victoria University of Wellington (VUW), New Zealand, and I am grateful to VUW for having supported my candidature.

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