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Record W4386195823 · doi:10.1093/indlaw/dwad022

Does Labour Law Trust Workers? Questioning Underlying Assumptions Behind Managerial Prerogatives

2023· article· en· W4386195823 on OpenAlexaff
Valerio De Stefano, Ilda Durri, Charalampos Stylogiannis, Mathias Wouters

Bibliographic record

VenueIndustrial Law Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsYork University
FundersVlaamse regeringFonds Wetenschappelijk Onderzoek
KeywordsHierarchyAutonomyLabour lawWorkforceLaw and economicsOrder (exchange)Control (management)Public relationsSocial dialogueBusinessSociologyEconomicsLawPolitical scienceManagement

Abstract

fetched live from OpenAlex

Abstract This article explores the relationship between modern labour law, trust-based management, and collective labour relations. It begins by examining the historical origins of labour law, which was established to give employers the means to govern their workforce, based on the assumption that workers were untrustworthy. We argue that this notion still persists, albeit in a refined form, and that advancements in technology can exacerbate the negative consequences of managerial prerogatives. The article highlights the need to re-examine the extent of managerial prerogatives and provides several examples of businesses that have adopted trust-based models of organization, leading to positive outcomes. However, the study cautions that trust-based models can be used as a guise for employers to retain greater control over their employees and emphasizes the critical role of collective labour relations in ensuring true trust. The article concludes by arguing that policymakers must challenge the hierarchy-centred model of the employment contract and promote practices that reinforce social dialogue and collective voice in order to reap the benefits of trust-based business practices. This study sheds light on the need to re-evaluate the current employment landscape and consider alternative models that prioritize trust, autonomy, and social dialogue in the workplace.

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)0.043
metaresearch head score (Gemma)0.086
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.086
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.073
Scholarly communication0.0130.018
Open science0.0030.006
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.083
GPT teacher head0.327
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations4
Published2023
Admission routes1
Has abstractyes

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