The Likelihood of Fraudulent Financial Reporting: The New Implementation of Malaysian Code of Corporate Governance (MCCG) 2017
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
On 26 April 2017 Securities Commission Malaysia has released new Malaysian Code of Corporate Governance (MCCG 2017) replacing MCCG 2012 with several changes and recommendations to enhance corporate’s accountability, transparency and sustainability. Therefore, the objective of this study is to compare the degree of compliance of this new MCCG 2017 among healthy companies and likelihood of fraudulent financial reporting companies using PN17 companies as a proxy. This study used content analysis of MCCG 2017 and disclosures provided in the annual report of the companies and analyzed it using descriptive statistics. We find that the degree of compliance even among healthy companies in Malaysia in terms of board diversity and board remuneration is still insufficient, and some of the companies are still reluctant to comply. This study provides initial evidence on the effect of new amendment of MCCG 2017 on the likelihood of fraudulent financial reporting in Malaysia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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