A look into accessible public transportation for people in Toronto who have acquired brain injuries
Bibliographic record
Abstract
Purpose This paper aims to explore the transportation needs of adults in Toronto who have acquired brain injuries (ABIs). Design/methodology/approach A survey was completed by staff working with clients in a community brain injury organization. Findings The survey showed that that some people with ABIs who do not use mobility devices and/or do not have obvious physical disabilities, could benefit from the city's door‐to‐door accessible public transit service (Wheel‐Trans). They are currently excluded from Wheel‐Trans based on the eligibility criteria for this service. Research limitations/implications This survey only looks at people with ABIs who are accessing services from an ABI community agency, thus it overlooks those who are not and may not be doing so due to lack of transportation. Also the survey is completed by staff rather than ABI clients, which may lead to different answers/perspectives. Practical implications A change to the eligibility criteria of Wheel‐Trans could increase the independence of some people with ABIs and could also increase their participation in society. Originality/value Based on a literature review by the author, there is no existing research that examines transportation and ABIs in Canada.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".