Bibliographic record
Abstract
Les contentieux climatiques contre les entreprises se multiplient à travers le monde à la faveur d’une réglementation, toujours plus riche, exigeant des acteurs davantage de transparence et de vigilance en matière climatique. S’il est pour l’instant difficile d’en faire un bilan, on peut néanmoins d’ores et déjà percevoir les contours de ces contentieux. Empruntant des chemins différents, dont certains sont « classiques » (notamment la responsabilité civile délictuelle), d’autres plus originaux (infractions du droit pénal des affaires ou du droit de la consommation), ils poursuivent un même objectif ultime : responsabiliser les entreprises face à leur impact et les rendre juridiquement responsables des dommages climatiques passés et en cours, et des dommages climatiques futurs. La présente contribution dresse une typologie non exhaustive de ces contentieux, selon qu’ils concernent directement ou indirectement la question du changement climatique.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".