The feasibility of adaptive reuse of vacant industrial buildings in Southwestern Ontario
Bibliographic record
Abstract
This research investigated the feasibility of adaptive reuse of vacant industrial buildings in Southwestern Ontario. Adaptive reuse is a conversion strategy that has recently been utilized in cities faced with a decline in industry. The cities experiencing a labour shift away from manufacturing now have dilapidated vacant or underutilized industrial buildings cross their urban landscape. Adaptive reuse is the process of reusing an existing building, with or without changes to the structure, for a new purpose. Southwestern, Ontario is a region that has struggled to rebound from the economic shift, and the 2008/2009 recession. The region is located southwest of Toronto, bordering Lake Erie and Lake St. Clair. This study, through case study analysis, explored the characteristics that are important in hindering or facilitating the feasibility of adaptive reuse of existing vacant industrial buildings. The case studies demonstrate that location, market characteristics, legislation, council support, and financial implications are the most important factors in assessing the feasibility of adaptive reuse. This research, and the recommendations provided, may aid municipalities and counties in encouraging and working with developers to revitalise their vacant industrial buildings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".