Authorizing Copyright Infringement and the Control Requirement: A Look at P2P File-Sharing and Distribution of New Technology in the U.K., Australia, Canada, and Singapore
Bibliographic record
Abstract
The doctrine of authorizing copyright infringement has been used to deal with the marketing of new Ttechnology that might be employed by a user to infringe copyright, from the distribution of blank cassette tapes and double-cassette tape recorders to photocopiers. It is being tested yet again with the distribution of peer-to-peer file-sharing software that enables the online exchange of MP3 music and other copyrighted files. This article looks at the different positions adopted in several Commonwealth jurisdictions, and examines the policy considerations behind these positions. It looks at, in particular, the recent Australian case of Universal Music Australia Pty Ltd. v. Sharman License Holdings Ltd. While many copyright infringement issues involve a balancing of the copyright owner’s interests against the alleged infringing user’s interests, the authorization concept is compounded by the further competing interests of promoting technology, as well as the interests of legitimate users who deploy the technology in lawful ways. The court’s challenge is to find an acceptable equilibrium among these interests.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".