Aereo Dynamics: “User Rights” and the Future of Internet Retransmission in Canada
Bibliographic record
Abstract
2014’s U.S. Supreme Court decision Aereo made waves in the entertainment and technology industry when it ruled in favour of a coterie of cable companies against an upstart start-up, Aereo Inc., retransmitting broadcast television over the internet. Little attention, however, has been paid to its ramifications to the Canadian broadcasting regime, with its vastly different regulatory scheme and an underlying objective to promote the dissemination of Canadian content. Complicating matters further is the 2012 Canadian Supreme Court decision Cogeco, where the retransmission of broadcast signals had been re-articulated as a ’user right’. This paper uses the Aereo decision as a heuristic tool to examine the Canadian retransmission regime with respect to the internet streaming of broadcast television, in which I argue that a firm employing ’Aereo’-like technology can help fulfill the CRTC’s mandate to advance the objectives of the Broadcasting Act that underpins Canadian communication law, and indeed, can and should be legal under Canada’s current copyright and telecommunications regime. I further contend that the retransmission of broadcast television is a ’user right’ in Canada and consequently does not constitute a copyright violation. The paper ends by examining the contours of the new ’user right’ to retransmission and how it relates to the existing ’user rights’ discourse introduced by the Supreme Court in CCH Canadian Ltd. v. Law Society of Upper Canada.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".