Rescuing the Balance?: An Assessment of Canada's Proposal to Limit ISP Liability for Online Copyright Infringement
Bibliographic record
Abstract
This paper attempts both to explain the technological and legal imperatives pressing Canada to address the issue of ISP liability in reforms to the Copyright Act and to raise some concerns about the impact of the government’s proposed amendments in this area. The basic elements of copyright law, the impact of digital technology on copyright and the policy arguments surrounding ISP liability are briefly discussed to set the context for judicial treatment of and legislative action on this issue. Next, the paper focuses on the development of American jurisprudence with respect to limitation of ISP liability for third party copyright infringement, 14 including examination of the pre-existing legal uncertainty in this area as well as the clarification offered in the DMCA. The position in Canadian law is then assessed, highlighting in particular how proposed amendments to the Copyright Act help resolve the legal questions surrounding ISP liability that remain unanswered after the Copyright Board’s Tariff 22 decision and its subsequent judicial review by the Federal Court of Appeal.15 Theoretical justifications of copyright law are considered as a measure against which to assess whether the effects of the proposed new enforcement regime accord with the fundamental purposes of copyright law. The paper concludes that, although the proposed amendments limiting ISP liability are an adequate first step in helping copyright confront new technologies, they must be fine-tuned in order to better protect the public interest before any legislation is passed.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.012 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".