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Record W1482984644 · doi:10.1108/02689230210450972

Labour‐management forums and workplace performance

2002· article· en· W1482984644 on OpenAlexaffabout
Terry H. Wagar, Kent V. Rondeau

Bibliographic record

VenueJournal of Management in Medicine · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsInstitute of Health EconomicsAlberta HealthUniversity of AlbertaSaint Mary's UniversitySt. Mary's University
Fundersnot available
KeywordsBusinessIndustrial relationsHealth careTrade unionLabour economicsSample (material)Job satisfactionPublic relationsEconomicsPolitical scienceEconomic growthManagement

Abstract

fetched live from OpenAlex

Many health care workplaces are adopting more cooperative labour-management relations, spurred in part by sweeping changes in the economic environment that have occurred over the last decade. Labour-management cooperation is seen as essential if health care organizations are to achieve their valued performance objectives. Joint labour-management committees (LMCs) have been adopted in many health care workplaces as a means of achieving better industrial relations. Using data from a sample of Canadian union leaders in the health care sector, this paper examines the impact of labour-management forums and labour climate on employee and organizational outcomes. Research results suggest that labour climate is less important in predicting workplace performance (and change in workplace performance) than is the number of LMCs in operation. However, labour climate is found to be at least as important in predicting union member satisfaction (and change in member satisfaction) as is the wide adoption of LMCs in operation. These findings are consistent with the notion that the greater use of LMCs is associated with augmented workplace performance (and a positive change in workplace performance), notwithstanding the contribution of the labour climate 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 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 score0.764
Threshold uncertainty score0.806

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)0.0010.000

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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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

Citations5
Published2002
Admission routes2
Has abstractyes

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