Bibliographic record
Abstract
Aujourd'hui, il est courant de qualifier les rapports humains les plus importants comme étant les rapports économiques. Les économies nationales subissent toutes sortes de perturbations économiques (des perturbations naturelles, résultant de décisions politiques ou encore de nouvelles technologies. Nos gouvernements sont appelés à y répondre. Doivent-ils laisser ces changements s'effectuer d'eux-mêmes ou résister à ceux-ci ? Doivent-ils tenter de les freiner ou au contraire les faciliter ? Il est clair qu'il n'existe pas de réponse unique applicable dans toutes les circonstances. Chacune des situations particulières exigera la recherche d'un équilibre entre l'efficience économique et la justice sociale. Il ne faut pas présumer que la notion de justice dans le domaine juridique peut se réduire à la simple notion d'efficacité économique. Et il ne convient pas non plus de supposer que la notion de justice dans le domaine économique peut se limiter à la simple recherche de la richesse maximale.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".