Peopling the North American city: Montreal, 1840-1900
Bibliographic record
Abstract
Many North American cities trace their population booms to the nineteenth century when immigrants and migrants flooded emerging industrializing urban centres in search of better lives. Peopling the North American City examines this phenomenon in Montreal through the eyes of a thousand couples to construct both an intimate portrait and a compelling overview of life in a nineteenth-century metropolis. Benefiting from Montreal's remarkable archival records, Sherry Olson and Patricia Thornton use an ingenious sampling of twelve surnames to track the comings and goings, births, deaths, and marriages of the city's inhabitants. The book demonstrates the importance of individual decisions by outlining the circumstances in which people decided where to move, when to marry, and what work to do. Integrating social and spatial analysis, the authors provide insights into the relationships among the city's three cultural communities, show how inequalities of voice, purchasing power, and access to real property were maintained, and provide first-hand evidence of the impact of city living and poverty on families, health, and futures. The findings challenge presumptions about the cultural assimilation of migrants as well as our understanding of urban life in nineteenth-century North America. The culmination of twenty-five years of work, Peopling the North American City is an illuminating look at the humanity of cities and the elements that determine whether their citizens will thrive or merely survive.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".