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An asymmetry in word-internal Chinese-English code-switching: A PFIC-based account

Published online by Cambridge University Press:  14 January 2026

Jen Ting*
Affiliation:
National Taiwan Normal University , Taiwan
*
Corresponding author: Jen Ting; Email: ting@gapps.ntnu.edu.tw
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Abstract

This study investigates an asymmetry in (Mandarin) Chinese-English word-internal code-switching: while Chinese inflectional morphemes readily attach to English verbs, Chinese derivational morphemes are consistently rejected when combined with English lexical bases. This pattern raises questions about how the free morpheme constraint should be formulated in bilingual grammar. Building on the phonetic form (PF) interface condition, as proposed in MacSwan’s [Generative approaches to codeswitching. In B. E. Bullock & A. J. Toribio (Eds.), The Cambridge handbook of linguistic code-switching (pp. 309–335). Cambridge University Press (2009)], we argue that the asymmetry is best explained in a lexicalist model that permits post-syntactic affixation. In this approach, inflectional morphology may attach at PF through PF merger, whereas derivational morphology is assembled prior to syntax. The observed asymmetry thus follows from the distribution of morphology across components and the conditions governing the mapping from syntax to phonology. The findings show that derivational timing shapes code-switching, support the viability of lexicalist models that permit post-syntactic affixation, and indicate that word-internal code-switching is permitted under specific interface conditions.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press or the rights holder(s) must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
© The Author(s), 2026. Published by Cambridge University Press
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Table 1. Descriptive statistics of mean ratings and standard deviations

Figure 1

Table 2. Summary of ordinal regression model coefficients