Climate change mitigation and adaptation through suburban sustainable landscape : a case study of the city of Colwood
Bibliographic record
Abstract
This case study explores sustainable landscape features and solutions to the impacts of climate change in the City of Colwood, a suburban area on Vancouver Island in Canada. It does so by addressing this research question: What landscape features could be incorporated into a suburban landscape to enhance its ability to mitigate and/or adapt to climate change? The main goal of the case study is to define relevant sustainable suburban landscape features that will potentially help the City of Colwood mitigate and/or adapt to climate change. A qualitative approach has been taken to data collection from a variety of primary and secondary resources—reports, government publications, articles, and case studies from other jurisdictions. These documents have been used to identify landscapes that can address climate change mitigation and/or adaptation. The study’s results on sustainable landscapes in suburban areas could contribute to revisions in laws and policies on sustainable urban landscapes and to future plans and developments in this area. Key words: climate change, mitigation, adaptation, sustainability, regenerative thinking, landscape ecology, urban landscapes, suburban landscapes, sustainable landscapes, City of Colwood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".