Bibliographic record
Abstract
Afin de renseigner les lecteurs du Bulletin, le Service de recherches entreprend une chronique mensuelle de Jurisprudence du travail. En principe, cette chronique portera sur les cas courants de jurisprudence soit des cours civiles, comme la Cour Supérieure ou la Cour du Banc du Roi, soit des tribunaux d'arbitrage ou encore sur les décisions intéressantes des diverses commissions administratives provinciales ou fédérales. Il pourra même arriver qu'on étudie des décisions intéressantes des cours étrangères. Bien que notre but soit surtout de nous attacher aux cas courants, il pourra arriver que cette chronique fasse un retour sur le passé afin de présenter aux lecteurs l'analyse de cas qui demeurent, malgré le temps, d'une grande actualité. On n'est pas sans savoir, en effet, que la jurisprudence prend ses sources les plus fermes dans des décisions qui datent.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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; both teacher heads agree on what is shown here.
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".