Analysis of Fraudulent Financial Reporting With the Role of KAP Big Four as a Moderation Variable: Crowe's Fraud's Pentagon Theory
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this study is to provide empirical evidence of pentagon fraud risk factors sush as financial targets, financial stability, number of audit committee members, nature of industry, change in auditors, auditor opinion, change in director, proportion of the independent commissary, frequent number of CEO pictures, and CEO duality on fraudulent financial reporting with KAP big four as a moderating variable. The samples in this study were all state-owned companies listed on the Indonesia Stock Exchange in 2014-2018. The purposive sampling technique was used in sampling so that 55 companies were obtained. This study uses logistic regression analysis techniques with SPSS version 26. The results of the study indicate that financial stability and the auditor's opinion influence the fraudulent financial reporting. However, financial targets, number of audit committee members, nature of industry, change in auditors, change in director, proportion of the independent commissary, frequent number of CEO pictures, and CEO duality not effect on fraudulent financial reporting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it