The association between voluntary disclosure in audit committee reports and banks’ earnings management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to examine the relation between voluntary disclosure (VD) in audit committee reports and banks’ earnings management. It investigates whether such disclosure reflects an attempt by audit committees to engage in impression management. Design/methodology/approach The study considers top US bank holding companies from 2006 to 2015. The authors develop a scoring grid to measure VD in audit committee reports. The scoring grid is based on recommendations from 10 industry and governance organizations’ reports that analyzed audit committee disclosures. Multivariate regression analyzes are used in this paper. Findings Descriptive statistics reveal that the level of VD in audit committee reports did not increase significantly from 2006 to 2015. Multivariate analyzes indicate that whenever banks’ level of earnings management is high, audit committees increase the extent of their VDs in their reports. The authors infer from this finding that audit committees are using VDs as a vehicle for impression management. Originality/value This paper sheds light onto the motives behind audit committees’ VDs. The evidence, which is consistent with impression management by audit committees in their report, also provides further background to the Securities and Exchange Commission’s recent initiative to enhance VDs in the audit committee report.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it