Piercing the peer–to–peer myths: An examination of the Canadian experience
Bibliographic record
Abstract
Canada is in the midst of a contentious copyright reform with advocates for stronger copyright protection maintaining that the Internet has led to widespread infringement that has harmed the economic interests of Canadian artists. The Canadian Recording Industry Association (CRIA) has emerged as the leading proponent of copyright reform, claiming that peer–to–peer file sharing has led to billions in lost sales in Canada. This article examines CRIA’s claims by conducting an analysis of industry figures. It concludes that loss claims have been greatly exaggerated and challenges the contention that recent sales declines are primarily attributable to file–sharing activities. Moreover, the article assesses the financial impact of declining sales on Canadian artists, concluding that revenue collected through a private copying levy system already adequately compensates Canadian artists for the private copying that occurs on peer–to–peer networks.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.102 | 0.038 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 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".