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Record W647334371 · doi:10.5860/choice.49-3462

Peopling the North American city: Montreal, 1840-1900

2012· article· en· W647334371 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.808
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.325
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2012
Admission routes1
Has abstractyes

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Same venueChoice Reviews OnlineSame topicCanadian Identity and HistoryFrench-language works237,207