Bibliographic record
Abstract
It is now impossible to understand major North American cities without considering the seemingly never-ending and ever-growing sprawl of their surrounding suburbs. In The Shape of the Suburbs, activist, urban affairs columnist, and former Toronto mayor John Sewell examines the relationship between the development of suburbs, water and sewage systems, highways, and the decision-making of Toronto-area governments to show how the suburbs spread, and how they have in turn shaped the city. Using his wealth of knowledge of the city of Toronto and new information gathered from municipal archives, Sewell describes the major movements and forces that allowed for rapid development of the suburbs, while considering the options that were available to planners at the time. Discussing proposals to curb suburban sprawl from the 1960s to the recently adopted plan for the Greater Toronto area, Sewell combines insightful and accessible commentary with rigorous research on the debate between urban and suburban. Concerned not only with sprawl, The Shape of the Suburbs also demonstrates the ways in which suburban political, economic, and cultural influences have impacted the older, central city, culminating in the forced Megacity amalgamation of 1998. Rich in detail and full of useful visual illustrations, The Shape of the Suburbs is a lively look at the construction of the suburban era
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".