Changes in Discretionary Financial Reporting Behavior following the Sarbanes-Oxley Act
Bibliographic record
Abstract
We examine the effect of the Sarbanes-Oxley Act (SOX) on the extent of aggressive versus conservative reporting behavior of public companies. SOX imposes considerably greater potential penalties on chief executive officers (CEOs) and chief financial officers (CFOs) who engage in financial wrongdoing. Therefore, risk-averse managers are likely to report lower earnings by reducing discretionary accruals following SOX. Our results, based on a matched sample of dual-listed Canadian firms and their domestically listed counterparts, indicate that (1) firms subject to SOX are more conservative in financial reporting in the post-SOX period as evidenced by lower signed discretionary accruals, the Ball and Shivakumar (2005) conditional conservatism measure, and the Penman and Zhang (2002) unconditional conservatism measure; and (2) the impact of SOX on firms' conservative reporting through discretionary accruals in the post-SOX period is not homogeneous—that is, it is more pronounced for firms that were aggressive in the pre-SOX period.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".