Sustainable placemaking in Suburbia
Bibliographic record
Abstract
There has been a significant increase in housing development in the Greater Toronto \nArea over the past fifty years, and all signs indicate that this will continue in the near \nfuture. The unsustainable practices of suburban developments must be addressed. \nThis thesis will look at the history of suburban developments from post-war times \nto current practices, with a focus on the lack of identity of a place, the loss of \necosystems, and hyper-individualism. It will also look at ways to improve tomorrow’s \nsuburban developments through placemaking, energy-efficient design and \nimplementation of green technologies like Net Zero and district energy to manage \nand reduce the energy consumed by these developments. The thesis will consider \nthese elements and practices to create a plan to lay the groundwork for the future \ncommunity development. The main design proposal of this thesis will be for phase \none of the plan, which focuses on creating a place and providing identity to the site.
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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 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".