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Record W2127893126

L'engagement organisationnel et les comportements discrétionnaires: L'influence des pratiques de gestion des ressources humaines

2000· preprint· fr· W2127893126 on OpenAlexaboutno aff
Philippe Guay, Gilles Simard, Michel Tremblay

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2000
Typepreprint
Languagefr
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsSocial psychologyHumanitiesOrganizational commitmentAutonomyOrganizational justicePolitical sciencePsychologySociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Dans cette étude, réalisée auprès de 536 salariés et cadres québécois, nous examinons l'influence perçue de quatre processus de GRH (le partage d'information, l'empowerment, les compétences et la reconnaissance) sur l'engagement organisationnel et la mobilisation de comportements discrétionnaires au travail, d'une part, de même que le rôle de l'engagement organisationnel (affectif et continu) dans la motivation à mobiliser certains comportements discrétionnaires au travail. Les résultats de l'analyse multivariée révèlent que les comportements discrétionnaires sont plus fortement mobilisés lorsque les employés possèdent un fort niveau d'engagement affectif à l'égard de l'organisation. Nos résultats montrent par ailleurs qu'un fort sentiment d'autonomie et d'influence et la possibilité de pouvoir utiliser ses compétences au travail exercent une forte influence positive indépendante sur la mobilisation de comportements discrétionnaires. Enfin, cette recherche met en lumière le rôle important de la reconnaissance non-monétaire et de la justice procédurale dans la constitution d'un lien affectif avec l'organisation et la motivation des employés à se mobiliser pour le succès de l'organisation.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.003
Open science0.0010.001
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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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.

Study designObservational
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

Citations14
Published2000
Admission routes1
Has abstractyes

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