The Political Economy of Texts: A Case Study in the Structuration of Tourism
Bibliographic record
Abstract
The field of tourism, particularly in linguistic minority contexts, shows how texts are situated within struggles over the legitimization of symbolic and material resources. In order to understand this field, we distance ourselves from some of the prevailing assumptions in discourse analysis, which presents texts and contexts as separate entities for which a certain autonomy can be assumed. We offer instead a view of texts as some among many artifacts produced in communicative practice (and hence in social processes), and which therefore require apprehension as processual, and not as objects. We argue that an ethnographic approach to text production and circulation is central to such forms of analysis. We analyze a sample of texts as embedded in their production by linguistic minority stakeholders in historically situated institutions. We interpret these texts as evidence of discursive and social changes brought about by globalization. We argue that behind texts that formally recall modernizing discourses of language and identity, what we encounter are processes of adjustment towards new economic and political conditions that lead minorities to commodify identity within global markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.021 | 0.019 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".