Integrating transportation and land use planning at the metropolitan level in North America: multilevel governance in Toronto and Chicago
Bibliographic record
Abstract
This article compares the policies and processes by which transportation and land use planning are integrated in metropolitan Toronto, Canada, and Chicago, in the United States. Using twenty-four semi-structured interviews with key informants, it describes the array of interventions undertaken by governmental and non-governmental actors in their respective domains to shed light on how the challenge of integrating transportation and land use planning is addressed on both sides of the border. Evidence concerning the political dynamics in Toronto and Chicago demonstrates that the capacity of metropolitan institutions to adopt and implement plans that integrate transportation with land use fundamentally depends on the leadership of the province or the state government. Although the federal government of each nation can bypass the sub-national level and intervene in local affairs by funding transportation projects that include land use components, its capacity to promote a coherent metropolitan vision is inherently limited. In the absence of leadership at the provincial or state level, the resence of a policy entrepreneur or a strong civic capacity at the regional levelcan be a key factor in the adoption and implementation of innovative reforms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".