Dans les coulisses de la science. Entretien avec Christina CAMERON, professeure,titulaire de la Chaire de recherche du Canada en patrimoine bâti – Université de Montréal (Québec, Canada)
Bibliographic record
Abstract
Comment en vient-on à travailler sur le patrimoine mondial ?Mon parcours s’explique par ma participation, d’abord comme membre puis comme chef, dans la délégation canadienne auprès du patrimoine mondial de 1987 à 2008. Pendant un peu plus de20 ans, en tant que haut fonctionnaire du gouvernement fédéral, je représentais le Canada, mais ce n’était pas seulement un poste de fonctionnaire pour moi. Mon intérêt personnel pour ces questions et mes intérêts de recherche liés à mon doctorat m’ont co...
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".