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Record W7064517716

Class Crimes: Master and Servant Laws and Factories Acts in Industrializing Britain and (Ontario) Canada

2020· article· en· W7064517716 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsServantLegislationFactory (object-oriented programming)MisconductLimitingLegislatureWork (physics)Criminal law
DOInot available

Abstract

fetched live from OpenAlex

This chapter compares the historical development and use of criminal law at work in the United Kingdom and in Ontario, Canada. Specifically, it considers the use of the criminal law both in the master and servant regime as an instrument for disciplining the workforce and in factory legislation for protecting workers from unhealthy and unsafe working conditions, including exceedingly long hours work. Master and servant legislation that criminalized servant breaches of contract originated in the United Kingdom where it was widely used in the nineteenth century to discipline industrial workers. These laws were partially replicated in Ontario, where it had shallower roots and was used less aggressively. At the same time as the use of criminal law to enforce master and servant law was contested, legislatures in the United Kingdom and Ontario enacted protective factory acts limiting the length of the working day. However, these factory acts did not treat employer violations crimes; instead, they were treated as lesser ‘regulatory’ offences for which employers were rarely prosecuted.

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)0.005
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: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.009
Science and technology studies0.0140.006
Scholarly communication0.0060.001
Open science0.0020.002
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 head0.030
GPT teacher head0.237
Teacher spread0.207 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueeYLS (Yale Law School)→Same topicMagnetic confinement fusion research→French-language works237,207→