Re-defining Toronto's collective housing: an architectural model for floating communities in the Don River Watershed
Bibliographic record
Abstract
Re-defining Toronto’s Collective Housing: An Architectural Model for Floating Communities in the Don River Watershed is meant to be a critique of the existing typology of floating communities in Toronto, and a proposal for a new model focused around building a sustainable and intentional culture around the water. \nExisting water-based communities in Toronto pose many issues in terms of sustainability, land use, community, stewardship and public access to the waterfront. \nThis thesis will address these issues and serve as a kick starter to the development \nof similar communities in the future. \nToronto is a large waterfront urban centre, however, even given its history \nsurrounding the water, the current city is not very oriented around it. The idea of an \naffordable community focused around the water has the opportunity to elevate this \nconnection between the city, its inhabitants and its watersheds. This thesis will analyze and take into consideration the current typology of floating communities in the \ncity and draw on the inspiration of global precedents to develop a program model \nthat values the importance of community, sustainability, financial accessibility and \nlocal culture. This thesis aims to aid not only in the development of community, but \nalso in the remediation and conservation of Toronto watersheds, providing a place \nfor conservationists and eco-minded patrons to live closely with the ecosystems \nthey strive to protect. The final design will use a sensitive design approach to build a \nprogram and building system that reflects the goals and ideals of this study. \nQuestion: \nHow can a new floating community typology address the lack of balance and \nattention to our watersheds through an affordable and sustainable community focused model?
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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 | 0.006 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".