Bibliographic record
Abstract
The author of this paper questions the role of the experts in heritage policies and practices. Is the voice of the heritage expert now guided by thevox populi? The current evidence for these trends, long considered anathema to heritage purists, suggests that an epoch-making change in heritage practice is now underway. The announcement of a Memorandum of Understanding between the World Bank and UNESCO to provide “very positive input for the improvement of aid effectiveness, and make the most of culture as a motor for social development and poverty alleviation, through employment and job creation” and the theme of the 17th ICOMOS General Assembly, “Heritage, a Driver of Development” are both clear indications of a pressing new concern: that heritage contribute to the economic – not only cultural – well-being of contemporary society. No less significant is the emphasis on public rights and responsibilities in the formulation of heritage policy, once the exclusive prerogative of antiquarians and professional conservators. This turn to the public as full-fledged heritage stakeholders is expressed clearly by the Council of Europe’s FrameworkConvention on the Value of Cultural Heritage for Society(2005) and the efforts of UNESCO to promote the active participation – and economic advancement – of traditional practitioners of intangible cultural heritage.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.061 |
| Scholarly communication | 0.025 | 0.027 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 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".