Pronoun shifts in political discourse: The English translations of the Thai Prime Minister Prayut Chan-o-cha's statements on the international stage.

  • Published In: Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción, 2024, v. 70, n. 6. P. 825 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Phanthaphoommee, Narongdej; Munday, Jeremy 3 of 3

Abstract

This article examines the English translations of former Prime Minister Prayut Chan-o-cha's statements on the international stage and the shifts in the first-person pronoun. Looking at interpersonal positioning through a systemic functional linguistic lens, we found that the translations underline the explicitness of agency, highlighting the variation of stylistic choices and interplay with source-text politics. The shifts come with a modified degree of willingness, a more active agency, an increase in the modality of inclination, and more force in attitude. These interpersonal overtones largely contribute to recasting the image of the Thai government to ensure its legitimacy, promote national unity, and appeal to the international community. These crafted translated texts seem to hone the leader's public persona in front of global audiences by continuing to enhance the country's reputation, thereby maintaining the speaker's dignity and prestige–an essential for the national leader's image. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción. 2024/11, Vol. 70, Issue 6, p825
  • Document Type:Article
  • Subject Area:Political Science
  • Publication Date:2024
  • ISSN:0521-9744
  • DOI:10.1075/babel.00388.pha
  • Accession Number:181812327
  • Copyright Statement:Copyright of Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción 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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