La gouvernance d'entreprise après Enron: Une comparaison entre les États-Unis, le Canada et la France
Bibliographic record
Abstract
L'objectif de l'étude est de comparer la gouvernance des entreprises entre les États-Unis, le Canada et la France dans la période post-Enron. Les scandales retentissants qui ont défrayé la chronique au début des années 2000 depuis cette affaire ont poussé les États à prendre leurs responsabilités en faisant voter successivement des lois. Ces dernières qui ne sont en réalité que la consolidation des rapports rédigés auparavant par des groupes de travail nationaux sur la gouvernance, semblaient indiquer une convergence en matière de gouvernance. Or, plusieurs divergences notables sont relevées au niveau de l'application des lois et des pratiques de gouvernance entre les trois pays. Une réflexion est alors amorcée quant à l'impraticabilité d’un modèle de gouvernance universel.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".