Auditors' Communications with Audit Committees: The Influence of the Audit Committee's Oversight Approach
Bibliographic record
Abstract
SUMMARY Policymakers have identified effective communications between the auditor and the audit committee (AC) as an indicator of a quality audit, but little is known about the factors auditors consider when deciding what to communicate about significant accounting issues. We propose auditors use the AC's oversight approach as a cue for the level of detail in their communications that is necessary to satisfy the AC's preferences for auditors' insights on issues that were resolved with management. In our experiment, auditors resolved an inventory obsolescence issue with a hypothetical CFO, and then wrote a communication about it for the AC. We manipulate the AC's preference for getting involved in the issue resolution process and its reputation for asking questions. Our results, supplemented by findings from audit partner interviews, suggest auditors tailor their communications to the AC's oversight approach, the AC's industry and accounting knowledge, and the AC chair's preferred communication style. Data Availability: Contact the authors.
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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 | 0.050 | 0.272 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".