Canada’s Copyright Act Review: Implications for Fair Dealing and Higher Education
Bibliographic record
Abstract
Beginning in late 2017, the Standing Committee on Industry, Science and Technology (INDU Committee) undertook a statutory review of Canada’s Copyright Act. This article examines the recommendations made by higher education and academic library stakeholders in order to determine their copyright priorities. More specifically, the analysis highlights recommendations relating to fair dealing and addresses the tension between higher education and the Canadian publishing community. The article also explores the three fair dealing recommendations made in the INDU Committee’s final report, raises questions about the INDU Committee’s support for use of fair dealing in higher education, and proposes increased advocacy by the higher education community, including a cohesive strategy that engages directly with the public interest aspect of education’s role and the representation of its user groups. Ultimately, educational institutions are as much a part of the Canadian cultural landscape as any other copyright stakeholder. Improved advocacy is vital as Canada heads towards the next statutory review, expected to be launched in 2022.
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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 | 0.136 | 0.328 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.037 | 0.040 |
| Scholarly communication | 0.041 | 0.013 |
| Open science | 0.010 | 0.009 |
| Research integrity | 0.029 | 0.024 |
| 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".