Regional Planning for Active and Sustainable School Travel: Challenges and Opportunities
Bibliographic record
Abstract
Significant efforts have been made worldwide to enable active and sustainable school travel, however there has been a lack of sustainable program success within the Greater Toronto and Hamilton Area (GTHA). This research begins to untangle the intricacies of integrating school travel programs into professional practice. A qualitative investigation was conducted in five municipalities that have implemented active and sustainable school travel initiatives within the GTHA. Participants from various sectors, including land-use planning, public health, and school boards, were selected for interviews. Thematic analysis revealed seven challenges that stakeholders confront, including Parent Acceptance, Regional Governance, School Boards, Program Ownership, Data Collection, Elected Officials, and Multidisciplinary Stakeholders. This research identified the ways in which stakeholders have attempted to overcome challenges – offering insights into where additional resources, capacity-building, and improved planning procedures could be introduced. Identifying and resolving these challenges are pivotal to the success of future collaborative transportation planning in the GTHA.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".