JOURNAL ARTICLE
A Scot an' a Sassenach scrieve aboot leid: A three-pairt Scotoethnography: (A Scot and an English Person Write about Language: A Scotoethnography in Three Parts).
Published In: Journal of Autoethnography, 2024, v. 5, n. 1. P. 39 1 of 3
Database: Sociology Source Ultimate 2 of 3
Authored By: Grant, Alec; YOUNG, SUSAN 3 of 3
Abstract
This autoethnography is written in three parts and is influenced by layered account writing principles. In part one, the first author develops his "Scotoethnography." In a poetic and prose mixture of Scots and Standard English, he critically explores his early socialization away from Scots toward Standard English. With examples from his lived experience, his published autoethnographic work, literary texts, and personal communication, he advocates for his use of Scots as an extra conceptual and linguistic resource. In part two he describes his research into the theoretical and empirical grounding of the article. Part three is a critically focused dialogue between the authors. It ranges across defining "Scotoethnography" and the first author's motivation for crafting the paper; the emerging political and cultural implications of othering, colonization, and silencing of Scottish identity; the passion and creativity inherent in Scots relative to Standard English; and, finally, the implications for autoethnographers who wish to rescue their regional dialects from monolinguistic entrapment in Standard English. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Autoethnography. 2024/01, Vol. 5, Issue 1, p39
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2024
- ISSN:2637-5192
- DOI:10.1525/joae.2024.5.1.39
- Accession Number:174712728
- Copyright Statement:Copyright of Journal of Autoethnography is the property of University of California Press 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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