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Record W49310351

Regulating Public Space in Early-Nineteenth-Century Montreal: Vagrancy Laws and Gender in a Colonial Context

2002· article· en· W49310351 on OpenAlexvenueaboutno aff
Mary Anne Poutanen

Bibliographic record

VenueHistoire sociale · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsVagrancyPrisonBeggingBourgeoisieLawColonialismCriminologyState (computer science)Context (archaeology)IdeologySociologyPublic spacePolitical sciencePoliticsHistoryEngineering
DOInot available

Abstract

fetched live from OpenAlex

In the late eighteenth and early nineteenth century, Montreal’s justices of the peace designed police regulations regarding vagrancy to include licensed begging as a form of social welfare for the respectable poor. Vagrant men and women deemed unworthy of state-sanctioned begging were apprehended and punished in the House of Correction or Common Gaol. City magistrates provided an opportunity for proper objects of charity to solicit alms while permitting some homeless vagrants, often women, to solicit shelter in prison. Women were economically dependent on male earnings, and single women were thus vulnerable to destitution. Gender was crucial to vagrancy laws, which acted as a form of moral regulation and had a concomitant impact on the lives of female vagrants. Men posed at least two threats: a moral one by their refusal to work and their perceived rejection of bourgeois notions of industry, sobriety, and discipline, and a physical threat exemplified by their potential for violence. In the wake of the Rebellions, harsh new laws thus reflected not only the British colonial views of dangerous Canadiens, but also the new bourgeois ideology that envisioned an orderly public space.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.661

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0210.027
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.035
GPT teacher head0.201
Teacher spread0.165 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2002
Admission routes2
Has abstractyes

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