Auditor communication on critical audit matters: Timing, inspection likelihood, and the audit committee
Bibliographic record
Abstract
Abstract In response to the extended audit report regulations implemented in the United States and internationally, both audit firms and regulators have increased scrutiny over critical audit matters/key audit matters (collectively referred to as CAMs) through internal and external inspections. At the same time, auditors and audit committees (ACs) have altered the content and timing of CAM‐related discussions by communicating specific planned audit procedures earlier in the audit process. This study explores the effect of early communication of CAM‐related audit procedures to the AC and increased scrutiny from inspections on auditors' propensity to adjust planned audit procedures in the presence of newly identified audit risks. Based on self‐justification theory, we predict and find that early communication of planned audit procedures to the AC causes auditors to be less likely to adjust planned audit procedures even when additional risks arise that necessitate change, especially when inspection is likely. This has the potential for diminished audit quality. Interviews with audit partners provide context for how these findings relate to the current auditing environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.403 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".