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Record W2100975349 · doi:10.7202/050956ar

Décentralisation des services de ressources humaines : impacts sur la satisfaction des clients

2005· article· fr· W2100975349 on OpenAlexvenueno aff
Thierry Wils, Marcel Saint-Onge, Christiane Labelle

Bibliographic record

VenueRelations industrielles · 2005
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsCentralisationPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Le but de cette étude est d'évaluer dans quelle mesure la décentralisation d'un service de ressources humaines a un impact sur la satisfaction de ses clients. Une enquête par questionnaire a été réalisée dans deux organisations du secteur public fédéral (l'une possédant un service centralisé et l'autre ayant opté pour une structure décentralisée). À partir d'un échantillon de 496 répondants, l'analyse statistique révèle que la satisfaction des clients envers leur service de ressources humaines est influencée positivement par la décentralisation, mais que cette relation est modérée par l'endroit de travail des clients (impact positif sur la satisfaction des clients en région). L'analyse montre également que la consultation et la flexibilité constituent deux facteurs explicatifs qui entrent enjeu seulement dans une structure décentralisée pour expliquer la satisfaction des clients.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2005
Admission routes1
Has abstractyes

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