An emerging intellectual property paradigm : perspectives from Canada
Bibliographic record
Abstract
Contents:PART I: INDUSTRIAL PROPERTY1. The Challenge of Trademarks Law in Canada's Federal and Bijural SystemTeresa Scassa2. A Watershed Year for Well Known or Famous MarksRobert G. Howell3. Canada's Treatment of Geographical Indications: Compliant or Defiant? - An International PerspectiveDianne Daley4. From Pasteur to Monsanto: Approaches to Patenting Life in CanadaMark Perry5. Canadian Pharmaceutical Patent Policy: International Constraints and Domestic PrioritiesMelanie Bourassa Forcier and Jean-Frederic MorinPART II: COPYRIGHT6. Canadian Colonial Copyright: The Colony Strikes BackPierre-Emmanuel Moyse7. Canadian Originality: Remarks on a Judgment in Search of an AuthorAbraham Drassinower8. Moral Rights in Canada: An Historical and Comparative ViewElizabeth Adeney9. A Uniquely Canadian Institution: The Copyright Board of Canada Daniel J. GervaisPART III: OVERLAPPING ISSUES10. Battleground Between New and Old Orders: Control Conflicts Between Copyright and Personal Data ProtectionMargaret Ann Wilkinson11. When Intellectual Property Rights Converge - Tracing the Contours and Mapping the Fault Lines 'Case by Case' and 'Law by Law' Myra J. Tawfik12. Surfacing: The Canadian Intellectual Property IdentityYsolde Gendreau
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.029 | 0.032 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".