Governance models for rural accessible transportation: insights from Atlantic Canada
Bibliographic record
Abstract
Insufficient or lack of accessible transportation options pose significant challenges for persons with disabilities living in small rural communities who need to travel within communities for day-to-day needs and between communities to access educational, employment, medical, and recreational services in urban areas. It is more than gaining the right to accessible transportation but one of how transportation services are to be provided. This article examines governance options for rural accessible transportation in Canada’s Atlantic provinces: New Brunswick, Nova Scotia, Prince Edward Island and Newfoundland and Labrador. Alternative governance options for accessible transit are identified including the direct provision of services, contracting out, co-operatives, not-for-profits, community boards and taxis. Insights gleaned from interviews with service providers tease out the advantages and disadvantages of the various options and reveal a struggle to balance accountability provisions with transaction costs. Points of interestAccessible public transit is enabling and necessary for people with disabilities to live full and independent lives.Many small towns and rural communities, like those found in Atlantic Canada, lack accessible public transit due to struggling economies and aging populations.Variability exists in how other small towns provide accessible public transit including direct provision, contracting out, co-operatives, not-for-profits, community boards to accessible taxis.Local officials struggle to balance oversight provisions while minimizing the expense of negotiations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".