TRANSIT AND SCHOOL TRANSPORTATION: EXPERIENCE AND ALTERNATIVE APPROACHES FROM THE LITERATURE
Bibliographic record
Abstract
This research project determines the extent that students are being served by municipal transit systems versus the yellow school bus of the School Boards and synthesizes the various approaches that have been implemented to accommodate school transportation demands and increase student ridership on the transit systems. The project reviewed student ridership statistics and concluded that of the 23 municipal transit systems that have had ridership increase in Canada over the past decade, 19 have been working closely with their school boards to accommodate students for school transportation purposes. In many cases, students were the main reason for the ridership increase. To determine what the transit systems have been doing to increase their student ridership and how students and their school transportation needs are being accommodated when most municipal transit systems are operating under budget constraints, the project surveyed a cross-section of municipal transit systems to synthesize the approaches and administrative arrangements that are being applied. Three transit/school transportation approaches were identified: fare-related approaches; service-related approaches; and operations-related approaches. Two administrative arrangements were identified as informal partnerships and formal partnerships with the school boards.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".