White-Collar Workers and Neighbourhood Change: Jarvis Street in Toronto, 1880–1920
Bibliographic record
Abstract
In 1880, Jarvis Street, just east of Toronto’s central business district, was the city’s premier residential district, home to notable Torontonians such as the Masseys and the Gooderhams. By 1920, the street would host a new group of young, unattached, white-collar workers. Changes to the social, demographic, and occupational character of Jarvis Street were accompanied by physical changes to its built form. The family estates of the nineteenth-century elite were converted into boarding and rooming houses, or torn down and replaced by some of the city’s first apartment buildings. These changes were driven by the growth of corporate capitalism in Toronto and the attendant growth of white-collar workers, as well as changes to urban form associated with the growth of the city outwards. This article examines the relationship between neighbourhood change and larger socio-economic changes occurring across the North American urban landscape at the time. It does so by using a variety of historical data, including City of Toronto tax assessments, city directories, as well as contemporary newspaper accounts. This case study of Jarvis Street’s social, gender, occupational, and physical changes shows the way that larger socio-economic processes are written at the scale of the neighbourhood. In doing so, it demonstrates the importance of understanding neighbourhood change as local materialization of larger social, economic, and demographic processes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 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".