Sustainability in Toronto : a Personal Rapid Transit System and a Community Development Plan for Cherry Beach
Bibliographic record
Abstract
Between October 2007 and January 2008 we got the chance to live in Toronto, the most diverse city in the world. Our choice of study has been to explore how sustainabile city planning can be dealt with in a new community of the Central Waterfront of Toronto. The themes presented by us are a new transportation system to decrease our oil-dependency and how to weave environmental and social sustainability together. Focus has been on a new transit system in the form of a Personal Rapid Transit System, which is simplified a system of loops of guideways with small pods that takes you from A to B without stops on the way. Ideas of PRT was introduced in the 60s, and is by its forespokers quick, environmentally friendly, reliable, convenient and cheap. It takes on the challenge to attract people who rather take the car in everyday life. A PRT system between Toronto Downtown and Port Land area as a way to decrease barriers and connecting new and existing built environment. Further, the Swedish model of Hammarby Sjostad, has attracted city planners from all over the world, among them Canadians working with the transformation of the Central Waterfront into becoming new mixed communities. The Hammarby sjostad model is a great example of new urbanism with focus on the environmental part of the sustainability concept. But what can be seen as missing is diversity. Diversity is a key word in Toronto with a couple of well visited neighbourhoods, Kensington Market and the Islands that can be seen as everyday urbanism areas. Still newly built areas at the Central Waterfront were missing these qualities. This led to a focus of what benefits and problems that can occur in weaving environmental and social sustainability together, using ideas of both new urbanism and everyday urbanism in building a new community. This thesis is the result of our ideas of sustainable city planning and presents a planning proposal for Cherry beach at the Waterfront of Toronto.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".