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Possessive Processing in Bilingual Comprehension.

  • Published In: Language Learning, 2023, v. 73, n. 3. P. 904 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Lago, Sol; Stone, Kate; Oltrogge, Elise; Veríssimo, João 3 of 3

Abstract

Second language (L2) learners make gender errors with possessive pronouns. In production, these errors are modulated by the gender match between the possessor and possessee noun. We examined whether this so‐called match effect extends to L2 comprehension by attempting to replicate a recent study on gender predictions in first language (L1) German speakers (Stone, Veríssimo, et al., 2021). By comparing Spanish and English learners of L2 German whose languages have different possessive constraints, we were able to examine whether the match effect was modulated by the participants' L1. A first experiment suggested that predictions and match effects were absent in setups with complex visual displays. A second experiment with simpler displays successfully elicited predictions and match effects, but their size was comparable in Spanish and English speakers, inconsistent with crosslinguistic influence. We interpret our results as evidence that processing difficulties with possessives result from memory interference that impacts both L1 and L2 comprehenders. A one‐page Accessible Summary of this article in non‐technical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Language Learning. 2023/09, Vol. 73, Issue 3, p904
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2023
  • ISSN:0023-8333
  • DOI:10.1111/lang.12556
  • Accession Number:169810534
  • Copyright Statement:Copyright of Language Learning is the property of Wiley-Blackwell 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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