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Record W1849168427 · doi:10.3917/riges.334.0048

Créer une culture de service

2008· article· fr· W1849168427 on OpenAlexvenueno aff
Jocelyn Pinet, André Coupet

Bibliographic record

VenueGestion · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicGlobal and Cross-Cultural Management
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Résumé Pour devenir une entreprise axée sur la qualité du service au client, il ne s’agit plus d’ajouter une énième initiative, mais bien d’opérer un virage culturel piloté par des leaders engagés dans la qualité du service au client. Dans cet article, nous examinons l’influence qu’exercent les cultures organisationnelles sur les comportements des personnes et voyons comment, dans une culture axée sur le service, le personnel ne se contente pas d’offrir un bon service, mais qu’il se préoccupe d’être au service de ses clients. Nous présentons aussi les caractéristiques qui distinguent un leader d’un gestionnaire. Nous proposons un modèle fondé sur trois axes, où le leadership agit en tant que pierre angulaire à l’aide des gestes forts accomplis sur des thèmes précis qui permettent à l’entreprise de conduire une transformation culturelle axée sur le client.

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)0.007
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.016
Scholarly communication0.0130.005
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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