Smart growth and sustainable development: Challenges, solutions and policy directions
Bibliographic record
Abstract
In this paper, we focus on the issues related to development densities that emerged from our study of sprawl and development issues in three regions of British Columbia, Canada. We chose to focus on this aspect of the smart growth agenda because, while many of its other elements enjoy wide support across social interests, the goal of achieving a higher density urban fabric is highly controversial. We proceeded by collecting data on development densities and 13 indicators of potential benefits in 26 municipalities. The results suggest that the density of communities is associated with efficiencies in infrastructure and with reduced automobile dependence, with the ecological and economic implications which flow from that. However, it does not necessarily correlate with greater affordability of housing or more access to green space. In fact, if anything, we discovered a negative relationship between housing affordability and green space per capita and higher land use densities. In a second stage of the research, we conducted a qualitative analysis of a subset of six municipalities and identified key policy issues for moving ahead with the smart growth agenda. The paper concludes with a discussion of the policy issues that emerged from these case studies.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.022 | 0.019 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".