MétaCan
Menu
Back to cohort
Record W2141465446 · doi:10.3917/grhu.082.0033

La responsabilité sociale des entreprises vue par les salariés : phare ou rétroviseur ?

2011· article· fr· W2141465446 on OpenAlexaff
Jacques Igalens, Assâad El Akremi, Jean‐Pascal Gond, Valérie Swaen

Bibliographic record

VenueRevue de gestion des ressources humaines · 2011
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La perception de la responsabilité de l’entreprise par ses salariés est un sujet important car elle semble de nature à influencer certaines attitudes et certains comportements qui sont au centre des relations entre l’employé et l’entreprise (fidélité, engagement, etc.). Or si la littérature scientifique s’est attachée à connaître la perception de nombreuses parties prenantes, y compris les candidats au recrutement, peu de recherches visent spécifiquement les employés. Quelques tentatives de construction d’échelles existent mais ne sont pas convaincantes. Pour ces raisons nous avons étudié, à partir d’entretiens collectifs, la perception de groupes de cadres et de non cadres de quatre entreprises. Deux d’entre elles ont un passé d’appartenance au secteur public. Les résultats mettent en évidence que les non-cadres privilégient la dimension sociale de la responsabilité sociale. Les cadres sont généralement mieux informés sur les principes, les valeurs et les engagements de leur entreprise. Dans de nombreux cas les non-cadres relient fortement comportement au travail et hors travail. Nous avons également montré que dans le cas des entreprises issues du secteur public, la responsabilité sociale prenait la place de la notion de service public.

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)0.004
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.083
GPT teacher head0.272
Teacher spread0.190 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueRevue de gestion des ressources humainesSame topicCorporate Social Responsibility ReportingFrench-language works237,207