Bibliographic record
Abstract
Les dommages-intérêts punitifs ont toujours été reçus avec une certaine méfiance en droit québécois. Le présent texte analyse les récents arrêts de Montigny et Ward, rendus par la Cour suprême, qui précisent des questions importantes qui divisaient la doctrine et la jurisprudence québécoises. La Cour suprême a tout d’abord établi que les dommages-intérêts punitifs constituaient une réparation autonome, qui peut être réclamée même en l’absence de dommages-intérêts compensatoires. Elle a aussi affirmé que l’octroi de tels dommages-intérêts peut viser des objectifs de punition, de dissuasion et de dénonciation. Enfin, la Cour lance un message de modération dans l’évaluation du montant accordé.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.012 | 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".