Healing Fair Dealing?: A Comparative Copyright Analysis of Canadian Fair Dealing to UK Fair Dealing and US Fair Use
Bibliographic record
Abstract
As a result of the March 4, 2004 Supreme Court of Canada decision in CCH Canadian Ltd v Law Society of Upper Canada for the first time in Canadian copyright history, the court determined that Canadian law must recognize a user right to carry on exceptions generally and fair dealing in particular. This paper compares the Canadian fair dealing legislation and jurisprudence to that of the UK and the US. It is observed that because of CCH, the Canadian common law fair dealing factors are more flexible than those entrenched in the US. For the UK, certain criteria have emerged from the caselaw consonant to Canada's pre-CCH framework and in many ways there is now a hierarchy of factors with market considerations at the fore. The real differences, however, ultimately lie in the policy preoccupations held by the respective courts, with Canada's top court alone concerned in championing user rights above all other rights. The paper concludes that Canadian fair dealing does not require too much healing but would benefit from some remedies outside (and complementary to) the law and the courts. While doing nothing does not seem to be the appropriate response, legal intervention as many advocate may not be warranted either. Rather than, or at the very least together with, reforming the law, establishing fair dealing best practices is most promising. The parties directly affected in a specific industry can together develop these guidelines to ultimately aid in clearer and ongoing fairer fair dealing decision-making in the courts. It is here that US initiatives can serve as most fruitful to emulate.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.026 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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.
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".