Bibliographic record
Abstract
In Robertson v. Thomson Corp., the Supreme Court of Canada (‘‘ the Court ’’) considered ‘‘ whether newspaper publishers are entitled as a matter of law to republish in electronic databases freelance articles they have acquired for publication in their newspapers — without compensation to the authors and without their consent’’. Curiously, while deciding that publishers are not entitled to reproduce the individual articles without the consent of the freelancers, it also held that the publishers do have a right to reproduce the articles in a CD- ROM database ‘‘as a part of those collective works — their newspapers . . .’’ independently of whether the scope of authorization of the freelancers extends to reproduction in electronic databases. The Court observed that, at its core, the case concerned competing layered rights of publishers in their newspaper, and free- lancers in their articles contained in the newspaper. In this comment, however, the author argues that by grounding the right of publishers to reproduce news- paper articles in their right to reproduce their newspapers — independently of the scope of the authorization to reproduce the articles — the Court wrongly abandons layered rights as they are ordinarily understood in the Copyright Act.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".