Bibliographic record
Abstract
Paris is famous for romance. Chicago, the blues. Buenos Aires, the tango. And Toronto? Well, Canada's largest urban centre is known for being a "city that works" -- a remarkably livable metropolis for its size. In this lavishly illustrated book, Richard White reveals how urban planning contributed to Toronto becoming a functional, world-class city. Focusing on the period from 1940 to 1980, he examines how planners shaped the city and its development amid a maelstrom of local and international obstacles and influences. Based on meticulous research of Toronto's postwar plans and supplemented by dozens of interviews, Planning Toronto provides a comprehensive and lively explanation of how Toronto's postwar plans -- city, metropolitan, and regional -- came to be, who devised them, and what impact they had. When it comes to the history of urban planning, the question may not be whether a particular plan was good or bad but whether in the end it made a difference. As White demonstrates, in Toronto's case planning did matter -- just not always as expected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".