JOURNAL ARTICLE
Syntactic outcomes of socially (un)restricted bilingualism in Spain: Word order with unergative and unaccusative verbs across two generations of Basque speakers.
Published In: Linguistic Approaches to Bilingualism, 2024, v. 14, n. 3. P. 340 1 of 3
Database: Communication Source 2 of 3
Authored By: Gondra, Ager 3 of 3
Abstract
The present study uses the apparent-time construct to analyze cross-generational variability of word order in unergative and unaccusative constructions in Basque (e.g., negar ein 'to cry' and heldu 'to arrive', respectively). It considers the results of an acceptability judgment as well as elicitation tasks carried out among two generations of Basque native speakers (55–75 years old, and 35–45 years old). Unlike the younger participants, the older participants lack the syntactic focus strategy. It is proposed that this lack among the older participants was conditioned by the socially restricted bilingualism that they experienced during the dictatorship of Francisco Franco (1939–1975), while the younger participants appeared to have acquired (i.e. recovered) the syntactic focus strategy because they experienced the legitimacy and vitality of Basque in public life and in formal education following the Normalization Law of 1982. Studies in Basque sociolinguistics have identified language changes through feature loss, dialectal leveling and contact-induced change, but no studies to date have identified the recovery of a previously lost syntactic structure. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Linguistic Approaches to Bilingualism. 2024/05, Vol. 14, Issue 3, p340
- Document Type:Article
- Subject Area:History
- Publication Date:2024
- ISSN:1879-9264
- DOI:10.1075/lab.21042.gon
- Accession Number:176343248
- 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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