Most Canadian Universities and Colleges Outside of Quebec Rely on Fair Dealing Rather than Access Copyright
Bibliographic record
Abstract
A Review of: Henderson, S., McGreal, R., & Vladimirschi, V. (2018). Access Copyright and fair dealing guidelines in higher educational institutions in Canada: A survey. Partnership: The Canadian Journal of Library and Information Practice and Research, 13(2), 1-37. https://doi.org/10.21083/partnership.v13i2.4147 Abstract Objective – To investigate the interpretations of fair dealing applied across Canadian post-secondary educational institutions outside of Quebec and to determine whether such institutions have a licence with Access Copyright. Design – Descriptive/quantitative study. Setting – Canadian post-secondary education sector, excluding Quebec. Subjects – A total of 159 Canadian post-secondary institutions outside of Quebec, including 75 universities and 84 colleges. Methods – A list of Canadian post-secondary educational institutions outside of Quebec was compiled. Data from participants relating to the research objective—reliance on an Access Copyright licence or use and interpretation of fair dealing—was collected via internet searches or, if unavailable online, via direct telephone communication with participants. Main Results – A majority of Canadian post-secondary educational institutions outside of Quebec, approximately 78% (124 institutions), did not have a licence with Access Copyright. The smaller the institution, the likelier it was to have an Access Copyright licence. This was in part linked to the fact that smaller institutions typically do not have staff specializing in copyright; savings from terminating Access Copyright licences (charged on a per student basis) would not justify the creation of such positions. Regarding fair dealing, 18% of study participants based their approach on the Supreme Court of Canada’s six-factor test (29 institutions), while 53% applied the fair dealing guidelines created by Universities Canada (85 institutions). Conclusion – Most of the institutions studied did not have Access Copyright licences and were relying on fair dealing instead, suggesting a bellwether for the copyright climate in the Canadian higher education sector towards fair dealing. Institutions may benefit from a future national consensus regarding interpretations of fair dealing concepts.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.003 |
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".