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Record W3110376987 · doi:10.7202/1072625ar

La GRH socialement responsable d’une multinationale dans ses filiales malgache, camerounaise et tunisienne : une réponse aux tensions stratégiques et managériales ?

2020· article· fr· W3110376987 on OpenAlexvenueno aff
Suzanne Marie Apitsa, Lovanirina Ramboarison‐Lalao, Kais Gannouni

Bibliographic record

VenueManagement international · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicGlobal and Cross-Cultural Management
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Cette recherche qualitative explore le déploiement du volet social-RH des politiques RSE d’une banque multinationale dans ses filiales malgache, camerounaise et tunisienne. Au-delà des contingences africaines communes aux filiales étudiées, les résultats montrent que l’adoption d’une démarche « client-fournisseur » peut permettre de répondre efficacement aux aspirations sociales des employés et à celles des parties prenantes externes. L’analyse des résultats suggère d’actionner durablement en Afrique une approche hybride des pratiques à travers l’opérationnalisation d’une GRH socialement responsable, comprise et acceptée par les parties prenantes, comme un levier de bien-être, et in fine de performance sociale et économique.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.061
GPT teacher head0.353
Teacher spread0.292 · 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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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