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SPATIAL CONTEXTS OF LANGUAGE SHIFT AND HERITAGE LANGUAGE RETENTION WITHIN A HIGHLY DIVERSE POPULATION: SYDNEY, AUSTRALIA.

  • Published In: Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography), 2023, v. 114, n. 4. P. 336 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: FORREST, JAMES 3 of 3

Abstract

In immigrant countries like America, Canada and Australia, heritage language retention and language shift (to the language of the receiving society) have long been associated with classical spatial theory, of initial segregation into inner city ethnic enclaves and subsequent intra-urban migration into majority 'white' or 'mainstream' residential suburbia, respectively. First through third generation spatial dynamics of shift and retention in Sydney are analysed for the ten largest post-1945 labour workforce immigrant streams from Europe and the ten post-1960s mainly skilled immigrant streams from the Middle East and Asia. Quartile and diversity analyses show that the association of intergenerational heritage language retention with spatial concentration and language shift with spatial dispersion has been superceded by a new set of spatial dynamics. Instead, patterns of retention and shift are responding to high levels of population diversity and minority majority suburbs where culturally hegemonic mainstream and minority cultural groups are intermixed across 80 per cent of Sydney's suburbs. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography). 2023/09, Vol. 114, Issue 4, p336
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:0040-747X
  • DOI:10.1111/tesg.12580
  • Accession Number:173390122
  • Copyright Statement:Copyright of Tijdschrift voor Economische en Sociale Geografie (Journal of Economic & Social Geography) is the property of Wiley-Blackwell 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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