JOURNAL ARTICLE

The (in)visibility of Indian languages in Singapore's multilingual landscape: A study of the linguistic landscape of little India.

  • Published In: Journal of Asian Pacific Communication (John Benjamins Publishing Co.), 2025, v. 35, n. 1. P. 58 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Jia Xuan, Lim; Aman, Norhaida 3 of 3

Abstract

Literature on Singapore's linguistic landscape (LL) points to the prominence of English, and Mandarin, to a lesser extent. This is attributed to the city-state's bilingual education policy and majority Chinese population. There is, however, lack of research on minority languages, and this paper addresses this gap by investigating the LL of Little India. This area serves multiple sociocultural functions: it is an enclave for the Indian minority in Singapore, a popular tourist attraction, and a gathering spot for migrant workers. While the findings show a strong dominance of English, in parts of Little India, there is greater prominence of the Indian languages, specifically Tamil, one of Singapore's official languages, and Bengali, a language spoken by Bangladeshi migrant workers, typically employed in low-wage, labour-intensive jobs. English has both symbolic and informational functions in appealing to a wider demographic of tourists and Singapore's multi-ethnic population, while Bengali serves an informational function. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Asian Pacific Communication (John Benjamins Publishing Co.). 2025/01, Vol. 35, Issue 1, p58
  • Document Type:Article
  • Subject Area:Language and Linguistics
  • Publication Date:2025
  • ISSN:0957-6851
  • DOI:10.1075/japc.25012.lim
  • Accession Number:187726014
  • Copyright Statement:Copyright of Journal of Asian Pacific Communication (John Benjamins Publishing Co.) 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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