Canadian Study for R&D Needs and Priorities in Accessible Transportation
Bibliographic record
Abstract
This study was undertaken in 2008 by the Transport Canada’s Transportation Development Centre. The research consisted of a literature review of North American and international accessible transportation for the past 10 years, with emphasis on Canadian work; consultations with various Canadian organizations; an analysis of social, economic, and support needs; the establishment of research priorities; and a final report with recommendations. Three different questionnaires were developed to survey seven selected Canadian organizations representing persons with disabilities and two government agencies responsible for accessible transportation. Survey results were analysed in terms of priority and time frame, and further classified into three R&D categories: technology/innovation, policy, and training. Consultations with consumer groups showed that access to travel information, fare affordability, and information for boarding and alighting ranked as the top three high-priority issues. Problems with communication was a recurring theme for travellers with disabilities. The top R&D recommendations from government respondents included updating travel data, developing guidelines for accommodating passengers with disabilities, and improving communication and information technologies. The majority of recommended research projects fell under the technology/innovation category. Of the 51 R&D project recommendations, 25 were suggested to be implemented in a 5 year time frame and 10 were rated as top priority. The list is meant to be used to develop a comprehensive research program, and presented to stakeholders for consideration. The literature review and the survey helped to identify respondents’ key concerns in order to arrive at an array of recommendations in R&D, training, and implementation. The present study revealed the general R&D needs of disabled travellers and two federal government entities regarding accessible transportation. The proposed research projects were presented at a meeting of Transport Canada’s Advisory Committee on Accessible Transportation held on March 19, 2009, and at the Canadian Transportation Agency’s Accessibility Advisory Committee meetings held March 30-31, 2009, to obtain feedback and agreement, especially from the industry and service providers who had not been explicitly consulted in this study. Overall, both committees agreed with the research proposals. Industry representatives expressed a need to undertake R&D that would address the tendency for larger and heavier wheelchairs, the balance of accessibility needs with safety and security concerns, and the lack of transportation-focused data on persons with disabilities. The recent CTA ruling for a one-person-one-fare policy in Canadian domestic air travel (e.g. airlines may not charge more than one fare to obese persons with disabilities who require additional seating for themselves) was expressed as a matter of concern for the industry [Canadian Transportation Agency Decision No. 6 AT A 2008]. The implications for large and obese passengers in public transport vehicles and ambulances operations (e.g. boarding/alighting procedures and equipment, seating, fare policy, access to washroom, safety and emergency evacuation etc.) require solutions. This issue has been added onto the R&D priority list originally developed as the eleventh project.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.010 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".