Emergence and Uncertainty in Urban Landscapes : A Model for the Toronto Public Landscape
Bibliographic record
Abstract
This thesis was initially predicated on early research carried out on Toronto's Public Open Space - in quite a broad framework. Texts based on the topic of Toronto's formation and its policy on public open space from the earlier days surrounding Lord Simcoe's first plans of the city provided a point of departure for the research. OMA and Bruce Mau in their design entry to the Downsview Park competition offered further insight into the perceptions and policy of Toronto in relation to public parks and lack of investment and maintenance. While other contributors on the topic of Toronto included Robert Fulford (Accidental City), Mark Osbaldeston (Unbuilt Toronto: a History of the City That Might Have Been), Jane Jacobs (Death and LIfe of Great American Cities), Howard Moscoe (Councillor Moscoe and his views of the city), Rob Ford and many others offered unforeseen accounts or facts on the city over the past century. Such people and the views they have published defend the very reason for the selection of Toronto as the subject of this research. Coinciding with the topic of Toronto, the recent emergence of the discipline of Landscape Urbanism and the capabilities of landscape in dealing with Modern and Post-modern failings within the city was deemed very early on to be the platform or medium upon which to offer any solution to the research on Toronto. Charles Waldheim, Professor and Chair of the Landscape Architecture Department at the Graduate School of Design in Harvard University, has on occasion referred to his term Landscape Urbanism as follows: Across a diverse spectrum of cultural positions landscape has emerged as the most relevant medium through which to construct a meaningful and viable public realm in North American cities. (Waldheim, C. 2006. p.41)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".