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Record W2124653412 · doi:10.1506/8yp9-p27g-5nw5-djkk

An Empirical Investigation of Audit Fees, Nonaudit Fees, and Audit Committees*

2003· article· en· W2124653412 on OpenAlex
Lawrence J. Abbott, Susan W. Parker, Gary F. Peters, K. Raghunandan

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

VenueContemporary Accounting Research · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingBusinessAuditAudit committeeAuditor independenceCommissionIncentiveJoint auditAudit evidenceSample (material)Actuarial scienceFinanceInternal auditEconomics

Abstract

fetched live from OpenAlex

Abstract This study examines the association between audit committee characteristics and the ratio of nonaudit service (NAS) fees to audit fees, using data gathered under the Securities and Exchange Commission's (SEC's) fee disclosure rules. Issues related to NAS fees have been of concern to practitioners, regulators, and academics for a number of years. Prior research suggests that audit committees possessing certain characteristics are important participants in the process of managing the client‐auditor relationship. We hypothesize that audit committees that are independent and active financial monitors have incentives to limit NAS fees (relative to audit fees) paid to incumbent auditors, in an effort to enhance auditor independence in either appearance or fact. Our analysis using a sample of 538 firms indicates that audit committees comprised solely of independent directors meeting at least four times annually are significantly and negatively associated with the NAS fee ratio. This evidence is consistent with audit committee members perceiving a high level of NAS fees in a negative light and taking actions to decrease the NAS fee ratio.

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)0.006
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.001
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 head0.053
GPT teacher head0.312
Teacher spread0.259 · 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