The ICFR process: Perspectives of accounting executives at large public companies
Bibliographic record
Abstract
Abstract The Sarbanes‐Oxley Act charges management with the primary responsibility for internal control over financial reporting (ICFR). However, prior research tells us little about the ICFR process from management's perspective. We develop a theoretical model of the ICFR process from management's perspective and examine that model by surveying 145 and interviewing 35 accounting executives at large US public companies. Our primary finding is that executives feel constrained in their ability to direct ICFR and hold perspectives that reflect these constraints. Specifically, most executives feel compelled by auditors to follow the PCAOB's preferences even though executives believe these preferences often tend to distract management and auditors from riskier areas. Executives also believe that audit committees' involvement in ICFR is too passive and that auditors' assessments are sometimes too severe, prompting executives to push back on auditors. Overall, executives strive to make decisions that are optimal for their ICFR, but limited resources and other business conditions, such as restructuring events and lack of qualified personnel, limit the effectiveness of their ICFR efforts. We discuss the implications of our results for practitioners, regulators, and researchers.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".