Impact of Research on the Evolution of Accessibility Standards
Bibliographic record
Abstract
Accessibility in the built environment is crucial for achieving the Sustainable Development Goals (SDGs) to promote equity, inclusion, and sustainable urban development. This study examines how the quantity and content of research on the accessibility of built environments for people with physical, sensory, and cognitive/intellectual disabilities impacted the development of accessibility standards. A systematic review was conducted to investigate the correlation between standard evolution and pertinent research. A representative sample was selected and reviewed to identify connections between research and the development of standards and to highlight gaps and limitations that hinder comprehensive accessibility standards. Canada’s CSA/ASC B651 standard is used as a case study. The study revealed that the evolution of the standard is constrained by the status and type of research. Results indicated that 50% of the research reviewed focuses on individuals with physical disabilities, half of the studies are not data-driven, and most research on people with cognitive or intellectual disabilities follows medical models, with data that are not suitable for standard development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.302 | 0.534 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.021 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".