Step in the Wrong Direction: The Impact of the Legislative Protection of Technological Protection Measures on Fair Dealing and Freedom of Expression.
Bibliographic record
Abstract
This paper will investigate whether legislation granting protection to TPMs infringes the freedom of expression (s. 2(b)) guarantee as contained in the Canadian Charter of Rights and Freedoms. This paper will proceed in five parts. Part I will discuss Bill C-60 and the legislative protection of TPMs in Canada. Part II will discuss the effect of TPMs on fair dealing. Part III will analyze whether the freedom of expression guarantee can be used to challenge provisions in the Copyright Act. Part IV will evaluate whether amendments to the Copyright Act granting protection to TPMs are consistent with the freedom of expression guarantee (s. 2(b)) in the Charter. Part V will investigate the treaty implications of protecting a right to access works for fair dealing purposes within legislation granting protection to TPMs.\nThis paper concludes that should the Canadian government amend the Copyright Act to provide legislative protection for TPMs, it must create a corresponding right for users to access copyright-protected expression for fair dealing purposes. Otherwise, the provisions may not survive Charter scrutiny. Although this paper will discuss this topic with reference to Canada, materials will be used from other jurisdictions in building this discussion. As well, the general argument in this paper may be helpful in addressing the interplay between copyright, fair dealing, and freedom of expression rights in other jurisdictions.
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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 | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.015 | 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".