Bref commentaire sur l'affaire Tervita de 2015 (Comment on the Supreme Court of Canada Decision in the Tervita Case (2015))
Bibliographic record
Abstract
French Abstract: Un bref commentaire sur la decision de la Cour supreme du Canada rendue dans l'affaire Canada (Commissaire de la concurrence) c Tervita Corp, 2015 CSC 3. Cette decision fut la premiere de la Cour portant sur le controle d'une fusion depuis 20 ans. Dans cette decision la Cour statue pour la premiere fois sur le volet empechment de la de l'art 92 de la Loi sur la concurrence ainsi que sur l'art 96 de la Loi, qui prevoit la defense dite gains en efficience. Ce commentaire met a jour l'appreciation qu'a fait les auteurs des incidences pour le droit de la concurrence de la decision de la Cour d'appel federale, rendue dans la meme affaire en 2013 (Cinq decisions en droit de la concurrence en 2013, (2014) 26:2 CPI, 523-552.)English Abstract: A brief case comment on the Supreme Court of Canada decision in Canada (Commissioner of Competition) v Tervita Corp, 2015 CSC 3, the first time in 20 years the Court has ruled on a merger case and the first time ever that it has examined the prevention branch of s. 92 of the merger provisions of the Competition Act as well as the efficiency defense (s 96) to an anticompetitive merger. This comment updates the authors' assessment of the competition law implications of the case following the 2013 Federal Court of Appeal decision in Tervita (Cinq decisions en droit de la concurrence en 2013, (2014) 26:2 CPI, 523-552.).
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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 | 0.003 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".