JOURNAL ARTICLE

Crosslinguistic influence from Catalan and Yucatec Maya on judgments and processing of Spanish focus.

  • Published In: Linguistic Approaches to Bilingualism, 2023, v. 13, n. 4. P. 529 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Hoot, Bradley; Leal, Tania 3 of 3

Abstract

Although a bilingual's knowledge of one language can affect the other, crosslinguistic influence (CLI) is constrained: certain domains, such as the syntax-discourse interface, are more likely to be affected. Linguists have debated CLI's nature and cause: the Structural Overlap Hypothesis identifies surface overlap between the languages as the key factor determining CLI, while the Interface Hypothesis highlights the role of processing overloads. Our study presents evidence from processing and judgments of a syntax-discourse interface property – information focus – in the Spanish of Yucatecan Spanish monolinguals, Yucatec Maya-Spanish bilinguals, and Catalan-Spanish bilinguals. The comparison across language dyads that realize information focus in different ways allows us to test predictions for language-specific effects of CLI. Using a forced-choice task to measure offline sentence preferences and a self-paced reading task to measure real-time processing, we find (i) language-specific CLI for Yucatec Maya bilinguals but (ii) no CLI for Catalan bilinguals and (iii) no significant differences in real-time processing. We conclude that these results provide partial support for the Structural Overlap Hypothesis but do not align with the Interface Hypothesis. We also examine the role of language dominance on CLI but find no such effects. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Linguistic Approaches to Bilingualism. 2023/07, Vol. 13, Issue 4, p529
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2023
  • ISSN:1879-9264
  • DOI:10.1075/lab.21020.hoo
  • Accession Number:166739894
  • Copyright Statement:Copyright of Linguistic Approaches to Bilingualism is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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