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Record W2159003570 · doi:10.2308/aud.2010.29.1.173

Audit Committee Member Investigation of Significant Accounting Decisions

2010· article· en· W2159003570 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAuditing A Journal of Practice & Theory · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAccountingNegotiationAuditScrutinyBusinessAccounting information systemAudit committeeCorporate governancePublic relationsPolitical scienceFinance

Abstract

fetched live from OpenAlex

SUMMARY: In the post-Enron environment, audit committee (AC) members are under increased scrutiny to demonstrate effectiveness in resolving significant accounting issues. However, prior research suggests that AC members are not involved in material auditor-client negotiations and that they are often not adequately informed of the issue resolution process. Therefore, AC members may not be effective in their oversight of the financial reporting process unless an accounting decision is clearly aggressive or adequate information about the decision is provided. In this study, I examine AC members’ investigation of accounting decisions when they are (or not) adequately informed of the negotiation process that led to the decision and when the decision results in an aggressive (versus conservative) financial reporting outcome. The hypotheses are developed from social psychology and research on corporate governance practice suggesting that AC members investigate accounting decisions to reduce discomfort in the financial reporting process by asking probing questions of the auditors and management. The results indicate that negotiation knowledge increases AC discomfort but has no effect on AC investigation, perhaps because potential questions were adequately addressed by the available information. I also find that AC members investigate more extensively as accounting decisions become increasingly aggressive and AC members with accounting experience are particularly thorough in their investigations when accounting decisions are aggressive. The results of this research have important implications to practice and future research.

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)0.010
metaresearch head score (Gemma)0.184
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.184
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.254
Teacher spread0.237 · 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