Spatial policies for growth management in metropolitan regions. A comparison of U.S. American, Canadian and German approaches
Bibliographic record
Abstract
Many metropolitan regions face concerns over sprawling development, increased costs of maintaining infrastructure, and loss of green space and farmland. Some metropolitan regions have intentionally created spatial policies to govern development patterns and manage growth within their region. This paper compares the spatial policies applied in three case studies: the Puget Sound region (Washington State, USA), Metro Vancouver region (British Columbia, Canada) and Stuttgart region (Baden-Württemberg, Germany). While all three regions share a vision that can broadly be summarised as transit-connected communities, each metropolitan planning organisation leverages a variety of spatial policies. Based on the unique planning cultures, various governmental actors take on different roles at the local, county, regional and state levels. This paper categorises and compares the multi-level responsibilities for defining, mapping, and implementing spatial policies. With this focus, the paper provides an international comparative perspective on approaches, context, and contents of multi-level growth management.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".