The Accessibility for Manitobans Act: Ambitions and Achievements in Antidiscrimination and Citizen Participation
Bibliographic record
Abstract
The Accessibility for Manitobans Act (AMA) was enacted in December, 2013. Manitoba is the second Canadian province to enact accessibility standards legislation. The first province was Ontario, which enacted the Ontarians with Disabilities Act in 2001, and, later, a more fortified and enforceable Accessibility for Ontarians with Disabilities Act, 2005. The AMA presents a strong set of philosophical and social goals. Its philosophical goals mark accessibility as a human right, and aim to improve the health, independence and well-being of persons with disabilities. The AMA’s social goals have the potential to make a positive impact on the development of equality law norms within the context of disability discrimination. Nevertheless, the AMA would be strengthened with a more robust and explicit appreciation of how disability discrimination issues are experienced. The Act should show a greater recognition of the relevance of embodied impairment to individuals with disabilities, and there should be more significant scope for the statute to address intersectionality within disability discrimination. These two challenges replicate the two principal critiques of the social model of disability –the model of disability on which the AMA is based. Finally, for the legislation to be successful, issues of compliance and enforcement that require positive uses of discretion on the part of the civil service should be addressed early on. The findings of this article may be useful for the implementation of the AMA and for the design of future accessibility legislation in Canada and elsewhere.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.020 | 0.016 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".