Access to post-secondary Education in Canada for students with disabilities
Bibliographic record
Abstract
In Canada, access to post-secondary education is guaranteed by a number of domestic instruments. These instruments are: statutory human rights legislation, constitutional law, and accessibility legislation. These guarantees are further bolstered by Article 24 of the United Nations Convention on the Rights of Persons with Disabilities (CRPD). Statutory human rights legislation (or anti-discrimination law) plays the most extensive role in controlling the discretionary power that colleges and universities exercise with respect to the admission of prospective students and the reasonable accommodation of matriculated students with disabilities. This article presents the findings of a review of decisions by human rights tribunals in Canada over the 7-year period of 2014–2021. With respect to both admissions cases and in-program reasonable accommodations cases, it identifies the main types of barriers experienced by persons with disabilities. It also examines the ways in which accessibility legislation, a proactive standard-setting form of legislation in Canada, has sought to improve access to post-secondary students with disabilities, focusing on Ontario’s post-secondary education accessibility standards as an example. Finally, it argues that changes to policies and practices on the ground that draw more inspiration from Article 24 of the CRPD will help to ensure that the equality right to post-secondary education for students with disabilities is fulfilled in letter and spirit.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".