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Record W3136200054

Back to the Future of Canadian Labour Law

2020· article· en· W3136200054 on OpenAlexaffabout
David J. Doorey

Bibliographic record

VenueSSRN Electronic Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsYork University
Fundersnot available
KeywordsCharterLabour lawCollective bargainingSupreme courtJurisprudenceLawLegislaturePolitical scienceCommon lawSubject (documents)Law and economicsSociology
DOInot available

Abstract

fetched live from OpenAlex

The invitation to present the H.D. Woods Lecture came with a proposed subject: the future of labor law. That future won't come by means of a sudden legislative tsunami that sweeps in broad-based sect-oral collective bargaining or some other dramatic new system to replace the Wagner Model which has governed since the 1940s. Instead, change will come first in the form of smaller fore-shocks. In this paper, which is the text of the 2019 H.D. Woods lecture, I argue that clues as to what those fore-shocks may be found can be found in important debates that took place during the 1980s. One of those debates examined comparative labor law and proposals to improve the Wagner Model of collective bargaining by merging features of the Canadian and U.S. versions of that model to create a hybrid model that would better facilitate access to collective voice. A second debate related to the potential impact of the Charter of Rights and Freedoms on the future of Canadian Labor law. David Beatty argued that the Charter would eventually lead to the dismantling of the Wagner Model and its replacement with a new model that extended the reach of collective bargaining to workers long excluded by the Wagner Model. In early Charter litigation, the Supreme Court of Canada wholly rejected Beatty's normative vision for a post-Charter labor law. However, in important ways, Charter jurisprudence since 2001 has slowly shifted the labor law agenda towards a landscape that shares much in common with that which Beatty envisioned long ago. The paper concludes with some predictions about the changes that will come to Canadian labor law drawn from these debates of some 40 years ago.

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)0.003
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 score0.224
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0230.020
Scholarly communication0.0150.006
Open science0.0020.004
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0240.002

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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
Published2020
Admission routes2
Has abstractyes

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