Bibliographic record
Abstract
Dans la Recommandation adoptée en 2014 par le Conseil de l’OCDE sur la gouvernance des risques majeurs, il est recommandé aux pays d’« associer tous les acteurs aux niveaux national et local afin de coordonner la participation de diverses parties prenantes dans des processus inclusifs d’élaboration des politiques » pour la gouvernance des risques majeurs. L’objectif d’une approche menée à l’échelle de la société tout entière pour assurer la sécurité et la sûreté des citoyens et de leurs biens consiste à défendre l’intégrité territoriale et à préserver les infrastructures essentielles et le bon fonctionnement des marchés. Les pays de l’OCDE ont démontré leur engagement en faveur d’une gouvernance des risques de très haute qualité, ce qui favorise la bonne mise en œuvre des politiques de gestion des risques. Les particuliers et les entreprises attendent des autorités qu’elles se tiennent prêtes face à un large éventail de crises et de chocs mondiaux possibles, et qu’elles sachent faire face s’ils surviennent.
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.
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 | 0.045 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".