Generating Change : Sustainable Adaptive Reuse of Urban Power Plants In-Depth Case Studies and Planning Implications for the Hearn, Toronto
Bibliographic record
Abstract
Cities across the western world are making the transition away from coal energy, and towards greener methods of power generation; as a result, abandoned power plants, including Toronto’s Richard L. Hearn Power Generation Station, are now features of many post-industrial urban landscapes. Largely out of use since 1983, the Hearn has seen a variety of redevelopment concepts over the last 30 years, but recent initiatives to revitalize Toronto’s Waterfront and industrial Port Lands have spurred renewed interest in the site. In order to provide direction for the Hearn’s impending redevelopment, indepth case studies of two adaptively-reused urban power plants, London’s Battersea Station and Austin’s Seaholm Plant, were performed via document analysis and key informant interviews. Salient themes, issues, and commonalities shared by all three cases were identified and explored, and used to formulate a series of seven development recommendations for the Hearn.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".