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Record W2579474802

Bref commentaire sur l'affaire Tervita de 2015 (Comment on the Supreme Court of Canada Decision in the Tervita Case (2015))

2016· article· en· W2579474802 on OpenAlexaffabout
Mistrale Goudreau, Jennifer Quaid

Bibliographic record

VenueSSRN Electronic Journal · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsConcurrenceSupreme courtLawAppealPolitical scienceHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

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.).

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.242
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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Same venueSSRN Electronic JournalSame topicTaxation and Legal IssuesFrench-language works237,207