Bibliographic record
Abstract
The Vancouver Region is widely recognised as one North American jurisdiction where strong growth management plans and policies have been put in place in order to control urban sprawl. While many authors have lauded the region for its good planning intentions, there has been little in the way of assessment of actual performance. This paper attempts to identify some quantitative growth management goals that have been (officially and unofficially) espoused by planning authorities in the region, and to measure these against actual trends. The results are mixed: on the one hand, some key growth management goals adopted by the region are not ambitious compared with existing trends and even these goals are not being met. For instance, the supposedly compact scenario adopted by the region deviates hardly at all from existing growth trends, which regional planners had clearly identified as untenable and requiring drastic change. On the other hand, the region's goal of preserving extensive green areas has been achieved without being watered down during goal formulation or implementation. Whereas these findings may appear contradictory, they are not: conservation in the region has not compromised the potential for growth in the region—at least for the time being. The real test of regional growth management efforts will come in the near future when further expansion meets the 'green wall' on the periphery and NIMBY resistance against densification within existing urban areas. The study suggests that the current structure of regional planning, relying on a partnership between municipal and regional governments, has served the region fairly well in building support for the need for growth management and in elaborating growth management vision. However, there is serious doubt about the ability of this system to set ambitious growth management objectives and to see through the implementation of those objectives in the face of social forces attempting to preserve business-as-usual trends in the region.
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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 | 0.000 | 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 | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".