New Era’ of Mass Transit: Governance, Suburbanization, and Regionalism in Toronto and Montréal
Bibliographic record
Abstract
This paper examines the ways in which two mass transit projects, the Eglinton Crosstown in Toronto, and the Réseau express métropolitain in Montréal, are responding to changes and challenges in terms of governance, suburbanization, and regionalism. It uses experiences from the two projects, and the lessons learned from them, in order to identify a series of best practices for transit planning in Canada. Methods used included a document and content analysis, as well as walk-through components of station areas on both lines. The results of the research indicated that the lines were designed and built with goals of ameliorating some of the challenges related to suburbanization and regionalism in mind. However, one of the two projects was more successful in countering the challenges related to governance, whereas the other may be more successful in curtailing suburban sprawl. Overall, the paper concludes that the Eglinton Crosstown and the Réseau express métropolitain have provided a framework of how to develop mass transit projects in Canada, and has found that a focus on public involvement, transparency, and accountability are important for success in transit projects, and that developing a local industry from the experiences of projects built will be highly beneficial in the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".