MétaCan
Menu
Back to cohort
Record W3004515024 · doi:10.1111/1748-8583.12285

Employer silencing in a context of voice regulations: Case studies of non‐compliance

2020· article· en· W3004515024 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Resource Management Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsWorkplace Health, Safety and Compensation Commission
FundersEconomic and Social Research CouncilIrish Research Council
KeywordsDirectiveSilenceCompliance (psychology)Context (archaeology)NeglectPublic relationsPrincipal (computer security)BusinessEmployee voiceEuropean unionPolitical sciencePsychologySocial psychologyComputer scienceInternational tradeComputer security

Abstract

fetched live from OpenAlex

Abstract This article, drawing on the latest insights into organisational silence, considers how employers seek to withhold information and circumvent meaningful workplace voice when confronted with regulatory requirements. It offers novel theoretical insights by redefining employer silencing as characterised by the withholding of information and the restriction of workplace dialogue. In outlining three principal routes of non‐compliance—avoidance, suppression, and neglect—we empirically illustrate the path to silence in the regulatory context of the European Union Directive establishing a general framework for informing and consulting employees. Rather than considering how employers utilised the regulations, as existing research considers, we look at how employers circumvented the regulatory space in three case studies in the United Kingdom and Ireland and the significant role of employer silencing as a tool for explaining this dynamic.

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.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.350

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 studies0.0000.000
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 head0.110
GPT teacher head0.371
Teacher spread0.262 · 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