Does Audit Quality Matters in Malaysian Public Sector Auditing?
Bibliographic record
Abstract
Auditors play a key role in contributing to the credibility of the financial statements on which they are reporting. High-quality audits support financial stability. The responsibility for performing quality audits of financial statements rests with the auditors. However, audit quality is best achieved in an environment where there is support from and appropriate interactions among participants in the financial reporting supply chain. Most prior studies look into audit quality from the perspective of private sector however this study focus on the quality of public sector auditing in Malaysia. There are three independent variables being investigated in this study that are the auditor’s independence, auditor’s competency and auditor’s workload. Data were collected through the distribution of questionnaires to 114 samples of auditors involved in public sector audit in Malaysia. The data were analysed using correlation test and regression test. The findings of this study show that there are positively significant relationship between auditor’s independence and auditor’s competency on audit quality. The results revealed that auditor’s competency is the most significant factor affecting the audit quality in public sector audit. However, results show that auditor’s workload has a negative and insignificant impact on audit quality. Hence, this study recommends that the audit departments to strengthen the audit quality and could improve the quality of the financial reporting in the public sector. In addition, auditor’s competency should be enhanced among the auditors in public sector to ensure high quality of audit work performed. Future studies should explore other variables such as client satisfaction, auditor switching and auditor’s turnover in public sector auditing.
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How this classification was reachedexpand
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".