Bibliographic record
Abstract
Histories of contemporary development control tend to situate its beginning in the first or second decade of the twentieth century, when modern zoning bylaws were adopted. Yet, as some researchers have pointed out, building and land-use regulations took shape in the nineteenth century and even earlier. This paper focuses on controls set by the City of Toronto between 1834, when it was incorporated, and 1904, when it adopted bylaw no. 4408, which is seen by many as the first step taken by the city toward modern zoning. In technical terms, it appears that a coherent, though minimal, apparatus of land-use regulation was already in place by the 1860s. Over the course of the nineteenth century, building codes and nuisance laws display the growing intervention of public authorities in the development of the industrial city. Municipal control over material production and over human activity diversifies and finds expression in increasingly complex ordinances. In political terms, the bylaws reveal a growing concern with socio-spatial differentiation and with the protection of property values rather than with health and safety. The incremental development of land-use regulation suggests that, even though North American cities borrowed from each other and from their European counterparts, they constructed zoning locally, in accordance to local needs, resources, and constraints (economic, political, and legal) and in a piecemeal fashion, one bylaw, one amendment at a time.
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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 | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".