Pour une responsabilité civile européenne élargie des agences de notation de crédit
Bibliographic record
Abstract
Les toutes premières sanctions prononcées par l’Autorité européenne des marchés financiers à l’encontre des agences de notation de crédit, ainsi que les récentes mises en cause de leur responsabilité civile aux États-Unis et en Australie invitent à s’interroger sur l’efficacité de la règlementation européenne en la matière. L’instauration d’un régime de responsabilité limité des agences de notation par le règlement 462/2013 peut-il permettre d’aboutir à des décisions semblables? La question est essentielle tant au regard du rôle fondamental des agences dans l’évaluation du risque de crédit que de leur influence sur la confiance et les décisions prises par les investisseurs sur les marchés. Envisager la mise en place d’une obligation de diligence des agences de notation pourrait permettre une mise œuvre effective de leur responsabilité.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 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".