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Record W3121732818 · doi:10.1506/j519-5lvu-jtmq-yyj7

Audit Review: Managers' Interpersonal Expectations and Conduct of the Review*

2002· article· en· W3121732818 on OpenAlexaffvenue
Michael Gibbins, Ken T. Trotman

Bibliographic record

VenueContemporary Accounting Research · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAuditDocumentationInterpersonal communicationProcess (computing)PsychologyField (mathematics)Public relationsAccountingBusinessSocial psychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract This paper presents an interpersonal model of audit file review centered on the audit manager. A manager's conduct of the review is affected by four components: the manager's expectations about the client, expectations about the preparer, expectations about the partner, and the manager's own approach and circumstances. The paper then presents a comprehensive field‐based analysis of how a working paper review is conducted. It supplements the mostly experimental research on working paper review by reporting the results of a retrospective field questionnaire that asked audit managers to report on their behavior and their relationships with preparers and partners on actual audit engagements. The extent of review was sensitive to specific features of the client and the file (including risk factors), to features of the preparer, and particularly to the style of the reviewer, which was quite stable across cases. Although the evidence of managers' awareness of preparers' “stylizing” the file to suit the manager was weak, the evidence of managers' stylizing for the partners was pervasive, affecting both work done and documentation. Managers believed that good reviews emphasized key issues and risks rather than detail. Other new descriptive evidence on the nature of the review process is provided, including the purpose of the review process, how frequently surprises are found in the review process, and the qualities of good reviewers compared with poor reviewers. The implications of our model and our results for future research are outlined.

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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
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 head0.071
GPT teacher head0.313
Teacher spread0.242 · 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 designNot applicable
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

Citations140
Published2002
Admission routes2
Has abstractyes

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