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Record W2011561476 · doi:10.1353/his.0.0085

Plutôt « s'endetter sur l'honneur ». Le débat sur la loi Lacombe (1900–1903) et les origines de la société de consommation au Québec

2009· article· en· W2011561476 on OpenAlexvenueaboutno aff
Sylvie Taschereau

Bibliographic record

VenueHistoire sociale · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

At the beginning of the twentieth century, Dr. Georges-Albini Lacombe, representing a working-class riding in Montreal, proposed legislation to protect the earnings of indebted workers from being garnisheed and to limit the "system of credit" that Lacombe judged to be the source of their debt. Although it carried his name, the law adopted after the ensuing debate contributed, to the contrary, through the twentieth century, to legitimizing the use of consumer credit. This article analyses this debate in light of the framework given by legal texts to different forms of credit and the strategies and practices regarding credit used by commercial institutions and urban households. Viewed from these perspectives and in relation to the social, cultural, and political dimensions of the history of credit, the debate reveals the interests at stake and the reasoning that finally prevailed to leave intact the system denounced by Lacombe, despite the general hostility voiced during this period toward consumer credit.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.001

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 head0.012
GPT teacher head0.254
Teacher spread0.243 · 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

Citations4
Published2009
Admission routes2
Has abstractyes

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