Spillover Effects of Internal Control Weakness Disclosures: The Role of Audit Committees and Board Connections
Bibliographic record
Abstract
ABSTRACT We find that firms are less likely to report an internal control material weakness (as mandated by the Sarbanes‐Oxley Act) in a given year if one of their audit committee members is concurrently on the board of a firm that disclosed a material weakness within the prior three years. We find a similar spillover effect for financial restatement disclosures. The spillover from material weakness disclosures is evident only if a shared director has more experience with the disclosing firm or can channel more information about the disclosed material weakness. Our findings suggest that prior director experiences outside the firm influence the work of audit committees inside the firm. One rationale is that a director's prior experience with an adverse disclosure helps diffuse important insights and serves as a catalyst for improvements in a firm's internal control and financial reporting practices. An alternative explanation, which we cannot dismiss, holds that a director's prior experience helps a firm to underreport material weaknesses and financial restatements without any attendant improvements in the underlying practices.
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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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".