Sustainability and local economic development in Canada and the United States
Bibliographic record
Abstract
This article provides a description, summary, and analysis of representative efforts to deal with the challenges to sustainability that result from the predominant patterns of land use in the metropolitan areas of North America. Two broad categories of public policies are considered: management and control of peripheral growth and revitalization efforts to improve the competitiveness of older urban areas. Metropolitan efforts to achieve more sustainable development through management of new development tend to rely more on voluntary agreements that preserve local government autonomy than on regional collaborations. The regional approaches that have been implemented to date have had only limited effectiveness. Efforts to make older communities more competitive with greenfield development have focused on downtown revitalization, industrial location incentives, business incubators, and neighborhood revitalization. While most of these efforts are carried out by state and local governments, faith-based organizations have come to play an increasingly important role. Downtown and industrial revitalization initiatives frequently provide only limited benefits despite their high public cost. Business incubators and neighborhood improvement efforts appear to be more cost effective strategies. On balance, the lack of political will and the preferences of households and businesses for new, low-density developments are likely to continue to foster unsustainable forms of urban development in most North American urban areas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".