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Record W1933599635 · doi:10.1111/ijau.12008

Audit Fees and Auditor Independence: The Case of <scp>ISO</scp> 14001 Certification

2013· article· en· W1933599635 on OpenAlexaff
Kouakou Dogui, Olivier Boiral, Iñaki Heras Saizarbitoria

Bibliographic record

VenueInternational Journal of Auditing · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAccountingAuditRemunerationAuditor independenceBusinessExternal auditorJoint auditAuditor's reportCertificationImpartialityContext (archaeology)Internal auditFinanceEconomicsLawPolitical scienceManagement

Abstract

fetched live from OpenAlex

This study analyses the effects of audit fees and the clients' financial power on the independence of ISO 14001 auditors on the basis of a qualitative analysis of interviews with 36 professionals involved in the certification process. The results of the study demonstrate that most respondents support the legitimacy of the current remuneration system based on the user‐pays principle, despite its business and financial ramifications, claiming that the independence of auditors is in fact ensured by the imposition of contractual duty, the observance of ethical codes, distancing the auditor from negotiations with the client, and dissociating the fee charged for the audit from the granting of the ISO 14001 certificate. However, the study demonstrates that auditors often adapt their behaviour to the client's economic context and the company size, which may call into question the prevailing opinion on the independence and impartiality of the certification process. This paper, on the one hand, discusses the manner in which auditors legitimize the current remuneration system and, on the other, describes the potential threat that it represents for their independence. The paper also highlights the similarities in this regard between the conflicts of interest in the field of environmental audits and in that of financial audits. Finally, the paper analyses a number of possible solutions to reduce the financial dependence of auditors on the audited companies.

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)0.021
metaresearch head score (Gemma)0.064
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 score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.022
Scholarly communication0.0060.006
Open science0.0010.007
Research integrity0.0020.004
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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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

Citations36
Published2013
Admission routes1
Has abstractyes

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