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Record W7064767149

Competition and Labour Law in Canada: The Contestable Margins of Legal Toleration

2022· article· en· W7064767149 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsnot available
Fundersnot available
KeywordsCommodificationPrinciple of legalityCollective actionTolerationNorm (philosophy)Competition (biology)Labour lawAction (physics)
DOInot available

Abstract

fetched live from OpenAlex

In Canada, as elsewhere, the norms of capitalist legality include an aversion to permitting collective action by sellers of commodities to increase their price. Labour law, however, is built on the norm of freedom of association and the right of commodified workers to combine for the purpose of improving the terms of their labour contracts. This gives rise to a recurring regulatory dilemma. In Canada, this conflict has been resolved by granting workers a legal immunity from liability under competition law for engaging in approved collective action to improve or defend their terms and conditions of work. However, the zone of toleration is contestable at three margins, explored in this chapter. First, is the margin between those workers who are covered by the exemption and those who are not; second between the sale of labour power and the sale of the commodities it produces; and the third is between the means that covered workers can lawfully use to make their combinations effective and those that take them out of the zone of toleration. The chapter explores the history of the construction of the zone of toleration and the conflicts over its margins, which are currently stable.

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)0.004
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.206
Threshold uncertainty score0.921

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0310.042
Scholarly communication0.0170.004
Open science0.0030.006
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.197
Teacher spread0.189 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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