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Record W4377006871 · doi:10.7202/1095929ar

Stratégies pour servir avec le sourire : effet des orientations clients et impacts sur la performance de service

2023· article· fr· W4377006871 on OpenAlex
Michel Cossette, Mélanie Bergeron

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHumain et Organisation · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePsychologyPhilosophy

Abstract

fetched live from OpenAlex

Dans les entreprises de service, on demande aux employés de servir les clients avec le sourire afin de les fidéliser. Les objectifs de la présente étude sont d’évaluer l’effet sur la performance des employés de trois stratégies pour servir avec le sourire et de déterminer si certaines prédispositions des employés (orientations vers la résolution des problèmes des clients et vers le développement de bonnes relations avec les clients) influencent les meilleures stratégies. L’article développe et valide les principales hypothèses d’un modèle auprès de 210 employés et de leur supérieur immédiat. Les résultats démontrent l’importance des orientations clients pour servir authentiquement les clients avec le sourire et démontrent l’importance de l’authenticité des employés dans la performance au travail.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.002
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 head0.045
GPT teacher head0.352
Teacher spread0.307 · 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