Transformative Metropolitan Development Models in Large Canadian Urban Areas: The Predominance of Nodes
Bibliographic record
Abstract
The paper centres on the content of metropolitan-scale plans of the six largest Canadian urban regions. Plans in all these regions promote intensification and alternatives to automobile use, and thus adhere to smart growth and sustainability principles. In all cases save one, reliance on nodal development is the preferred manner of achieving intensification and ensuring its co-ordination with public transit services. Meanwhile, however, results point to differences in the stage of development of metropolitan planning strategies. The paper concludes by reflecting on the wide adoption of the nodal model in metropolitan plans. It interprets this popularity as the outcome of the ability of nodes to achieve intensification and reduced car reliance objectives, while conforming to prevailing planning and institutional capacity. The effectiveness of the nodal approach and other broad metropolitan planning concepts rests in their capacity to procure a metropolitan structure for the other scales at which urban planning is practised.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".