The Unintended Consequences of Material Weakness Reporting on Auditors' Acceptance of Aggressive Client Reporting
Bibliographic record
Abstract
ABSTRACT Regulators are concerned that auditors do not sufficiently identify and report material weaknesses in internal control over financial reporting (ICFR). However, psychological licensing theory suggests reporting material weaknesses could have unintended consequences for acceptance of aggressive client financial reporting. In an experiment, we predict and find auditors accept more aggressive client reporting after they report a material weakness in ICFR than after they report no material weakness. We provide evidence licensing underlies this effect. In a second experiment, we investigate the efficacy of an intervention to reduce the identified licensing effects by prompting an audit quality goal. We find this prompt mitigates the unintended consequence when auditors report a material weakness. While regulators are concerned companies are undeservedly receiving clean ICFR audit opinions, our findings indicate adverse ICFR opinions may lead auditors to give companies undeservedly clean financial statement opinions. We provide a potential remedy to this unintended consequence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.097 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".