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Article published In:
Linguistic Landscape
Vol. 6:1 (2020) ► pp.52–79

Survey area selection in Variationist Linguistic Landscape Study (VaLLS)

A report from Vienna, Austria

| University of Vienna

This article addresses the unresolved issue of systematic survey area selection for large-scale quantitative Linguistic Landscape (LL) studies. It presents a strategy of ‘hypothesis-driven stratified sampling’ whereby survey areas are picked out in a nested, multi-step process on the basis of the configuration of local LL audiences (regarding age, multilingualism, and tourism) and ambient activity types (commercial vs. residential). The rationale for this strategy is drawn from variationist sociolinguistics; and the undertaking is accordingly cast as ‘Variationist Linguistic Landscape Study (VaLLS)’. The details of the design are showcased and implications discussed in the context of the large-scale project ‘ELLViA – English in the Linguistic Landscape of Vienna, Austria’. More generally, it is shown how the application of state-of-the-art variationist principles and methodology to quantitative LL research significantly enhances the latter’s scientific rigor, which has been a major point of criticism.

Keywords: sociolinguistics, variationist sociolinguistics, linguistic landscapes, quantitative linguistic landscape study, data sampling, survey area, methodology, Austria, Vienna, English, German
Article outline
  • 1.Introduction
  • 2.Integrating variationist sociolinguistics and quantitative LL study
  • 3.Hypothesis-driven stratified sampling in ELLViA
    • 3.1Hypothesis-driven stratification and selection of sub-areas and streets for surveying
    • 3.2Picking out stretches on the streets to be surveyed
  • 4.The benefits of the sampling scheme: First results from the ELLViA VaLLS survey
  • 5.Conclusion and outlook
  • Acknowledgements
  • Notes
  • References
Available under the Creative Commons Attribution (CC BY) 4.0 license.

For any use beyond this license, please contact the publisher at [email protected].

Published online: 16 March 2020
DOI logo
https://doi.org/10.1075/ll.00017.sou
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