Smart Growth and Urban Economic Development: Connecting Economic Development and Land-Use Planning Using the Example of High-Tech Firms
Bibliographic record
Abstract
This paper explores the connections between economic development and sustainable land-use planning. It brings forward the idea that for cities to adapt their development patterns from low-density urban sprawl, they must plan and develop with efforts coordinated between economic development and land-use planning. It uses the example of the high-tech sector to determine what aspects are needed to create areas that are both attractive to high-tech firms while also matching the principles of smart growth, a popular method of sustainable urban development. It analyzes two case-study areas in Metro Vancouver: Yaletown, a dense neighbourhood in downtown Vancouver; and Crestwood Corporate Centre, a traditional office park in Richmond. Through these case studies the important factors needed to attract high-tech firms are determined, and connections with aspects of smart growth are articulated. It is argued that economic development and forms of sustainable urban development such as smart growth have positive connections and mutually beneficial results when coordinated.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".