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Record W1939395699 · doi:10.3233/wor-2012-0805-5172

The influence of flexible management practices on the sharing of experiential knowledge in the workplace: a case study of food service helpers

2012· article· en· W1939395699 on OpenAlexaff
Élise Ledoux, Esther Cloutier, Pierre‐Sébastien Fournier

Bibliographic record

VenueWork · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsUniversité LavalInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsExperiential knowledgeKnowledge sharingExperiential learningKnowledge managementBusinessService (business)Process (computing)Work (physics)Knowledge value chainOrganizational learningMarketingPsychologyEngineeringComputer science

Abstract

fetched live from OpenAlex

Previous studies have shown that the job knowledge and prudent knowledge of experienced workers constitute a wealth that needs to be shared in workplaces to promote worker integration, job retention and occupational health and safety. It appears, however, that certain management practices undermine this knowledge sharing process. This case study of food service helpers in institutional food service departments is part of a research project aimed at comparing the impact of different work organization methods on knowledge sharing in the workplace on the basis of case studies carried out in several organizations. The results of this case study reveal that by destabilizing and weakening the work teams, flexible management practices create an environment that is not conducive to experiential knowledge sharing.

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0130.007
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.292
Teacher spread0.231 · 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 designQualitative
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
Published2012
Admission routes1
Has abstractyes

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