Municipal High Modernism and “Negotiation”: Toronto’s Post-War Governance and Expressway Arrangement c. 1943 - 1971
Bibliographic record
Abstract
This essay examines the history of urban planning and governance, urban- suburban infrastructure development, and city-community negotiation in post-war Toronto. A specific emphasis is placed on the downtown community’s push-back against a centrally planned highway grid during the late 1960s. The role of the automobile is a central element to the study, as it was the primary impetus for Toronto planners who sought to deliberately model post-war infrastructure after auto-centric U.S. cities. The history engages with the expansion of an expressway-tethered stretch of urban and suburban space now known as the “Golden Horseshoe”: surveying the location of automobile plants in cities along the rail lines; capital flight from Quebec; and suburban developer’s encroachment upon agricultural space in their search for cheaper land to build middle-class subdivisions. The paper reviews the existing literature on Canadian and North American urban transportation and economic history, whilst also drawing on a primary research base of municipal and provincial master planning documents, policy deliberations, newspaper accounts, activist materials and interpretations from key actors throughout the period of the study. Toronto is placed in a broader transnational theoretical framework through an exploration of two key concepts; “high modernism” and “negotiation”. These two ideas are used to demonstrate how a centralized bureaucratic urban vision was challenged by organized residents of Toronto’s core who were determined to preserve the human scale, architectural distinctiveness and civic involvement in urban life. The thesis’ vital case study is the protest against the proposed Spadina Expressway, the success of which led to the cancellation of not just that highway, but the abandonment of other municipal highway plans across the city. This political shift is an important chapter in Toronto’s urban governance as a formerly top-down, provincially controlled process was democratized into a new municipal authority that valued greater community engagement. The logic animating the city’s greater built environment is discussed to make sense of the sprawling suburban form that was manifest and became dominant in the post-war period.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.024 | 0.022 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".