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Record W1993656729 · doi:10.7202/1027253ar

94 ans et toutes ses dents ? Ou : Exégèse de l’article 32 de la Loi sur la concurrence au regard de la propriété intellectuelle

2014· article· fr· W1993656729 on OpenAlexvenueaboutno aff
André Dorion

Bibliographic record

VenueRevue générale de droit · 2014
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceConcurrencePhilosophy

Abstract

fetched live from OpenAlex

Le présent article analysera la place centrale qu’occupe l’article 32 de la Loi sur la concurrence dans l’application de la politique de concurrence canadienne aux droits de propriété intellectuelle et à leur exercice. Dans un premier temps, nous replacerons la disposition dans son contexte historique, pour ensuite examiner la seule décision judiciaire la concernant, soit D.E.R. c. Warner, et enfin la replacer dans la mosaïque que constitue la Loi sur la concurrence en ce qui a trait aux droits de propriété intellectuelle. Dans un deuxième temps, une analyse exégétique de la disposition, accompagnée de commentaires sur le contexte de la disposition, ses moyens et sanctions ainsi que les usages prohibés de droits de propriété intellectuelle, nous permettra de constater qu’une réflexion en profondeur s’impose sur l’approche de la Loi face à la propriété intellectuelle. En conclusion, nous nous interrogerons sur l’opportunité d’une telle réflexion, eu égard aux nouvelles exigences du cadre normatif international, et des expectatives des acteurs de la propriété intellectuelle. Face à ces exigences et expectatives, force nous est de constater que l’article 32 constitue une piètre réponse, datant d’une autre époque et déplacée dans le cadre moderne de la Loi. L’interface primordiale entre le droit de la concurrence et celui de la propriété intellectuelle mérite mieux.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0160.002

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.

Opus teacher head0.036
GPT teacher head0.243
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2014
Admission routes2
Has abstractyes

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