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Record W3083181415 · doi:10.22495/cgsrv4i2p6

Determinants of sustainability assurance levels: The case of French firms

2020· article· en· W3083181415 on OpenAlexaff
Emna Klibi, Salma Damak–Ayadi, Sinda Dridi, Bouchra M’Zali

Bibliographic record

VenueCorporate Governance and Sustainability Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPromulgationSustainabilityAccountingLeverage (statistics)Sustainability reportingBusinessSample (material)Political scienceLawComputer science

Abstract

fetched live from OpenAlex

The aim of this work is to analyse the determinants of the level of sustainability assurance for the CAC 40 French firms from the time period preceding and following the implementation of the Grenelle 2 law that made sustainability assurance compulsory. The objective of the paper is twofold: 1) provide a better understanding of the factors influencing the professional judgement provided by assurance providers, 2) verify whether the content of the disclosed sustainability reports has evolved as a result of the introduction of the Grenelle 2 law or not. A sample of 257 firm-year observations is collected for the period 2008-2017 and an ordinal regression model is used in this study. The findings highlight a change in the content of assurance reports after the promulgation of the Grenelle 2 law. The sector’s sensitivity, the type of assurance provider, and the leverage level have an impact on the level of assurance for the period 2013-2017 which was not the case for the period 2008-2012. Based on the institutional theory, these correlations may be explained by the promulgation of the Grenelle 2 law in 2012.

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)0.003
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.047
GPT teacher head0.292
Teacher spread0.246 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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