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Record W2088176269 · doi:10.1177/0143831x14546237

Challenging new governance: Evaluating new approaches to employment standards enforcement in common law jurisdictions

2014· article· en· W2088176269 on OpenAlexaff
Leah F. Vosko, John Grundy, Mark P. Thomas

Bibliographic record

VenueEconomic and Industrial Democracy · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsWilfrid Laurier UniversityYork University
Fundersnot available
KeywordsEnforcementCorporate governanceArgument (complex analysis)Law enforcementBusinessLaw and economicsProcess (computing)Public economicsEconomicsLawPolitical scienceFinance

Abstract

fetched live from OpenAlex

A mounting crisis in employment standards (ES) enforcement is prompting the adoption of new instruments and mechanisms among governments in common law jurisdictions aiming to improve workplace regulation. This shift, evident across all stages of the enforcement process, indicates the increasing influence of regulatory new governance. Using reforms in four jurisdictions as illustrative examples, this article raises serious cautions around the emergence of regulatory new governance in employment standards enforcement. The central argument of the article is that new modes of regulation that fail to account adequately for the power dynamics of the employment relationship risk entrenching processes of regulatory degradation. In light of this potential, the article outlines four principles for more effective ES regulation that aim to balance aspects of traditional regulatory models with a selective application of more promising elements of regulatory new governance, in particular participatory arrangements that involve workers in enforcement processes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.146
GPT teacher head0.337
Teacher spread0.191 · 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 teacher head, 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

Citations28
Published2014
Admission routes1
Has abstractyes

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