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Visitor experience as translation: Intertextuality and identity in experiences of an American Chinese museum.

  • Published In: Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción, 2024, v. 70, n. 5. P. 615 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Neather, Robert 3 of 3

Abstract

This paper explores the museum visitor experience as a form of translation. It argues that if a given exhibition can be seen as a cultural translation, then it is also true that the visitor's reading of that exhibition constitutes a further layer of translation, as the visitor enacts their own transformation of the culture on display. The paper draws on intertextuality as a means to understand the ways in which this transformation occurs. It delineates a three-level typology of intertexts employed by the visitor and considers how the use of such intertexts constructs the visitor's positionality in regard to the exhibition. The paper focuses on data from a diasporic museum, the Museum of Chinese in America, and applies a methodology involving analysis of TripAdvisor reviews and post-visit diaries to the online museum. The paper concludes that diaspora museums are a case in which the particular nexus of identity issues at work provide a more complex view of the visitor experience as translation. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Babel: International Journal of Translation / Revue Internationale de la Traduction / Revista Internacional de Traducción. 2024/09, Vol. 70, Issue 5, p615
  • Document Type:Article
  • Subject Area:Literature and Writing
  • Publication Date:2024
  • ISSN:0521-9744
  • DOI:10.1075/babel.00397.nea
  • Accession Number:178992994
  • 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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