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Record W2806475706 · doi:10.1111/1911-3846.12454

PCAOB Inspections: Public Accounting Firms on “Trial”

2018· article· en· W2806475706 on OpenAlexvenueno aff
Kimberly D. Westermann, Jeffrey P. Cohen, Greg Trompeter

Bibliographic record

VenueContemporary Accounting Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingBusinessListed companyAuditPublic accounting

Abstract

fetched live from OpenAlex

ABSTRACT The objective of our article is to obtain a better understanding of how auditors anticipate the potential for PCAOB inspection, experience the inspection, cope with the consequences of the inspection, and understand the PCAOB's influence within the context of professionalism. We use a qualitative approach that uses both surveys (55) and interviews (20) of auditors (of varying rank and firm) across a five‐year period (2012–2017). Respondents suggest that PCAOB inspectors are powerful, representing the “prosecution,” “judge,” and “jury” of the auditing profession. We therefore use a structural metaphor of the PCAOB inspection as a judicial “trial.” By controlling the criteria used to evaluate performance, inspectors have the power to repeatedly “subpoena,” “interrogate,” and return a “verdict” on the firm (auditor); those judged as “guilty” require supervised “probation.” This process is perceived as having improved audit quality but at a cost. Passing an inspection is so important that auditors (firms) have resorted to impression management strategies and “functionally stupid” work practices (e.g., excessive documentation, a decrease in critical thinking as a result of a “box ticking” approach to auditing). Furthermore, some respondents believe that being a good auditor has come at the expense of being a good accountant; the emphasis on audit process and concurrent de‐emphasis on technical accounting could ultimately lead to audits themselves falling short. In addition, it is evident that inspectors and auditors differ in their perceptions of risk, likely manifesting because inspectors are standards‐focused while auditors (firms) are methodology‐focused. Finally, the inspection process has created excessive stress and tension, beyond budget and fee pressures, which some auditors perceive as affecting the pool of talented auditors that firms may be able to attract and retain in the future.

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)0.008
metaresearch head score (Gemma)0.059
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.085
GPT teacher head0.322
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

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

Citations232
Published2018
Admission routes1
Has abstractyes

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