JOURNAL ARTICLE
Boundaries of belonging: Language and Swedishness in contemporary Swedish fiction.
Published In: Language, Culture & Society (2543-3164), 2023, v. 5, n. 1. P. 94 1 of 3
Database: Communication Source 2 of 3
Authored By: Ganuza, Natalia; Rydell, Maria 3 of 3
Abstract
This article uses contemporary Swedish fiction to explore sociolinguistic phenomena, and argues that literature constitutes an important arena for studying the (re)production and circulation of sociolinguistic experiences and ideas at a particular time and place. It builds on qualitative analysis of 65 Swedish books, published between 2000 and 2020, which depict protagonists with multilingual and migrant backgrounds. The study examines patterns of repetition in these works of fiction. It foregrounds recurring sociolinguistic experiences that are made relevant in the depiction of the fictional characters' lives, and how they are emotionally interpreted. The analysis shows that the narrated experiences are often told and organized in similar ways and they tend to use the same social images of speakers to highlight processes of boundary-making and social differentiation. Language is used as an important part of the entextualization of these social experiences. For example, the authors often depict "the immigrant" and "the Swede" as binary opposites, which are linked to certain typical forms of speaking and being. By way of repetition, we argue, these recurring fictional experiences contribute to the formation of a grander narrative about language, belonging and social boundary-making in contemporary Sweden, and to the construction of Sweden as a society that is increasingly segregated and stratified. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Language, Culture & Society (2543-3164). 2023/01, Vol. 5, Issue 1, p94
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2023
- ISSN:2543-3164
- DOI:10.1075/lcs.21005.gan
- Accession Number:172808246
- Copyright Statement:Copyright of Language, Culture & Society (2543-3164) 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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