Accessibility and the Limits of the Equality Act 2010: Time for a UK Accessibility Act?
Bibliographic record
Abstract
Abstract This article makes a case for the introduction of a new UK Accessibility Act to supplement existing equality law and outlines key ingredients to be included in such legislation. Such a reform would fulfil commitments under international human rights law, align with purported cross-government prioritization of accessibility, establish a more joined-up and effective regulatory structure and, most importantly, hasten progress toward a barrier-free society in which disabled people and others are enabled to learn, work, move and live as equals. The article has three main sections. The first elaborates on the accessibility obligations set out in the UN Convention on the Rights of Persons with Disabilities. It also discusses recent legislative responses to these international human rights requirements in the European Union (the European Accessibility Act) and Canada (the Accessible Canada Act). The second section maps out the various accessibility interventions of the Equality Act 2010 and exposes the limits of the current approach, which is patchy, splintered and heavily dependent on expensive and high-risk litigation by individuals. The third section draws on the examples of Canadian and EU legislation to consider what should be included in a new UK Accessibility Act.
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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 | 0.022 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".