Access Copyright : prise 2 ou Retour au XIXe siècle pour le droit d’auteur canadien ?
Bibliographic record
Abstract
RESUME En 2020, la Cour d’appel federale s’est prononcee sur deux questions importantes de droit d’auteur que soulevent les tarifs deposes par la societe de gestion Access Copyright et homologues par la Commission du droit d’auteur. L’une de ces questions a mene a la conclusion que les utilisateurs ne sont pas lies par ces tarifs, ce qui remet ainsi en cause non seulement le role de la Commission du droit d’auteur, mais aussi les fondements memes de la gestion collective. Cet article porte sur ce dernier point qui interesse toutes les societes de gestion au Canada. Il offre ainsi l’occasion de se pencher sur le Rapport Parker, qui a donne naissance a un tribunal administratif du droit d’auteur, et sur les valeurs qui ont anime son auteur. ABSTRACT In 2020, the Federal Court of Appeal had the opportunity to discuss two important issues that fl ow from the approval by the Copyright Board of tariffs fi led by Access Copyright. One of these issues was answered with the conclusion that users are not bound to abide by approved tariffs and thus challenged not only the role of the Copyright Board, but also the very foundations of collective management. This text deals with this issue – which is relevant to all collective societies in Canada – and provides an opportunity to examine the Parker Report, which led to the creation of a copyright administrative tribunal, and the values that actuated its author.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.002 |
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.
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".