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Record W7124439835 · doi:10.52975/llt.2025v96.004

Drinking on the Job

2025· article· en· W7124439835 on OpenAlexaffvenueabout
Allan Greer

Bibliographic record

VenueLabour / Le Travail · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsPaymentValue (mathematics)BarterSign (mathematics)Labour supplyElement (criminal law)Work (physics)

Abstract

fetched live from OpenAlex

This article examines the role of alcohol, specifically rum, in labour relations in the early staples trades. In the 18th-century colonies that would later form Canada, labour was generally scarce and therefore expensive. Employers had to offer high wages as they struggled to recruit and retain workers, but because their enterprises were typically undercapitalized and vulnerable to market fluctuations, they could not afford to pay the salaries in full at the end of the contracted period. Focusing on the fishing servants of Newfoundland and the voyageurs of the North West Company, the article shows how wages were systematically clawed back through the workings of a version of “truck.” Payment was deferred to the end of the season, and in the interim, employers would supply their men with goods at inflated prices, ensuring that many ended up indebted beyond the value of their nominal wages and had to sign on for a further term to pay off their debts. Rum was a crucial element in this system, its addictive qualities making it the ideal instrument for absorbing earnings. Many fishing masters and fur traders actively encouraged consumption; drinking on the job, then, was not only allowed but, in some cases, practically mandatory.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.203
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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 designQualitative
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

Citations0
Published2025
Admission routes3
Has abstractyes

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