Commercialization without over-commercialization: normative conundrums across heritage rationalities
Bibliographic record
Abstract
In aligning its priorities around the Sustainable Development Goals, UNESCO officially acknowledges the need to reconcile the market and heritage. Yet inscriptions of commercial practices on the Intangible Cultural Heritage lists are qualified as ‘traumatic’ by actors that design normative principles for ‘good’ heritage governance. Based on ethnographic observations of the meetings of the governing bodies of the Convention for the Safeguarding of the Intangible Cultural Heritage, I analyse the controversies generated by the ‘risks of over-commercialization’, shedding light on the disputed entanglements between ICH and the market. In exploring the notion of ‘commercialization without over-commercialization’ meant to resolve the tension between heritage and the market, I highlight how ‘over-commercialization’ refers to notions of ‘misappropriation’ and ‘decontextualization’ and the ways it, therefore, intersects with the logics of Intellectual Property. This allows to elucidate a constitutive ambiguity in the implementation of the Convention, torn between the rationalities of heritage and property regimes.
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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 | 0.048 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.170 |
| Scholarly communication | 0.028 | 0.035 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".