NYMITY, P2P & ISPS: Lessons from BMG Canada Inc. v. John Doe
Bibliographic record
Abstract
This chapter provides an exploration of the reasons why a Canadian Federal Court refused to compel five Internet service providers to disclose the identities of twenty nine ISP subscribers alleged to have been engaged in P2P file-sharing. The authors argue that there are important lessons to be learned from the decision, particularly in the area of online privacy, including the possibility that the decision may lead to powerful though unintended consequences. At the intersection of digital copyright enforcement and privacy, the Court's decision could have the ironic effect of encouraging more powerful private-sector surveillance of our online activities, which would likely result in a technological backlash by some to ensure that Internet users have even more impenetrable anonymous places to roam. Consequently, the authors encourage the Court to further develop its analysis of how, when and why the compelled disclosure of identity by third party intermediaries should be ordered by including as an element in the analysis a broader-based public interest in privacy.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.046 | 0.020 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 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".