Introduction: Sociolinguistics and tourism – mobilities, markets, multilingualism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the introduction to this special issue on Sociolinguistics and Tourism , we focus on language in tourism as an important window into contemporary forms of economic, political, and social change. Our aim is twofold: (1) to establish and extend ‘sociolinguistics and tourism’ as another social and applied domain of sociolinguistic research; and (2) to use tourism as a lens for a broader discussion of the sociolinguistics of late modernity. To this end, we outline the contours of language and tourism research to date; we consider the (re)conceptualization of key thematics or notions in sociolinguistic research – such as ‘community’, ‘identity’, and ‘language’ itself – as particularly germane to the study of tourism's fleeting encounters; we examine the inevitable tensions between commodification and authenticity; and we explore the links between performances of ‘self’ and ‘other’, and the contestation of different identity positions with regard to social actors’ multilingual repertoires. We illustrate these issues with data examples from several tourist sites, where multilingual resources are deployed for identification, authentication and commodification. Finally, we briefly introduce the papers in this special issue and conclude by commenting on some sociolinguistic consequences of the study of language/s in tourism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it