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Record W2979605615 · doi:10.7202/1063708ar

Does It Pay to Disclose CSR Information? Evidence from French Companies

2019· article· en· W2979605615 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement international · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsExecutive compensationIncentiveCorporate governanceCorporate social responsibilityBusinessAccountingCompensation (psychology)Sample (material)Empirical evidenceFinancePublic relationsEconomicsPsychologyMicroeconomicsPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

This article looks at how company disclosure of corporate social responsibility (CSR) information affects executive compensation through an empirical study of a sample of French companies listed on the SBF 120 index from 2007 to 2011. The focus is on short-term incentive compensation and total incentive compensation. These two components are not correlated with the total CSR disclosure score (comprising environmental, social, and governance factors). The study reveals that only the environmental disclosure score is correlated with (short term and total) executive incentive compensation. Social and governance disclosure do not have any effect on executive incentive compensation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.006

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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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