The Practitioners’ Guide to Using the Copyright Act of Canada to Make Accessible Content for People with Print Disabilities
Bibliographic record
Abstract
This article documents the process and guidelines developed to respond to a library practitioner’s question as to what constitutes a reasonable search, in the context of section 32 of the Canadian Copyright Act. In answering the question, the authors decided that a Canadian guide would be helpful to all practitioners facing the same question, and they undertook a project to create “Accessible Content: A Guide to the Canadian Copyright Act on Searching for Accessible Formats and Producing and Distributing Alternate Formats” (----, 2025). The authors formed a multi-stakeholder coalition, and developed a set of guidelines aimed at aiding practitioners to understand and apply the exceptions in the Copyright Act that enable the reproduction of works for persons with perceptual disabilities.
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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 | 0.017 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.020 | 0.009 |
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".