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Record W3153486021 · doi:10.3917/resg.138.0213

Corporate social responsibility and the readability of listed firms’ compensation discussion and analysis

2020· article· fr· W3153486021 on OpenAlexaffabout
Walid Ben‐Amar, Eustache Ebondo Wa Mandzila, Philip McIlkenny

Bibliographic record

VenueRecherches en Sciences de Gestion · 2020
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPolitical scienceCorporate social responsibilityPhilosophyLaw

Abstract

fetched live from OpenAlex

Cette recherche examine la relation entre la responsabilité sociale des entreprises (RSE) et la complexité des informations qu’elles fournissent relativement la rémunération de leurs dirigeants. En nous basant sur les prédictions de la théorie des parties prenantes, nous nous attendons à ce que les entreprises soucieuses de la RSE adhèrent à des normes éthiques élevées et communiquent des informations plus transparentes et faciles à lire sur la rémunération des dirigeants. Basés sur un échantillon de 196 sociétés inscrites à la Bourse de Toronto, nos résultats montrent une association positive entre la mise en œuvre de pratiques de RSE et la lisibilité des informations textuelles présentées dans le rapport d’analyse et discussion de la rémunération. Parmi les trois composantes du score total de la RSE, le score de gouvernance présente une relation négative avec la complexité linguistique des rapports de rémunération, ce qui suggère que les entreprises mieux gouvernées communiquent des informations plus lisibles sur leurs pratiques en matière de rémunération des dirigeants.

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)0.027
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.226
GPT teacher head0.367
Teacher spread0.141 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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Same venueRecherches en Sciences de GestionSame topicCorporate Social Responsibility ReportingFrench-language works237,207