Policy Areas Impinging on Elderly Transportation Mobility: An Explanation with Ontario, Canada as Example
Bibliographic record
Abstract
As countries face the challenges posed by rising numbers of older persons, the need to reassess their respective policies to address transport needs in aging societies is increasingly recognized in relation to health and sustainability goals. This paper proposes the examination of six interrelated policy areas affecting elderly mobility in a country or administrative region. A general survey of policy developments in each of these areas could improve current strategies and existing processes in the planning and implementation of mobility services that will be responsive to both elderly and the general population now and in the future. These include: 1) general transport policy framework; 2) travel mode preference; 3) alternative transport infrastructure stock and investments; 4) housing-land-use-transportation linkage; 5) research and technology applications that improve travel mode and environment; and 6) institutional and legal reforms. These policy areas are discussed and given concrete elucidation in the case of Ontario, Canada. Reflections and recommendations for further research and policy action deemed critical in the case region are highlighted.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".