The Determinants of Audit Expectation Gap in Malaysia
Bibliographic record
Abstract
This study intended to identify the determinants of the audit expectation gap in Malaysia. The expectation gap is defined as the different perspectives of what society thinks and what society wants the auditors to do. Previous Malaysian researchers prove the existence of audit expectations. However, only some studies identify determinants of the audit expectation gap in Malaysia. Recent studies show that the Malaysian public misunderstood auditors' duties and audit scope. This quantitative research addresses the relationship between auditors’ skills, auditors’ efforts, knowledge of society, and users' needs toward the audit expectation gap. Online questionnaires are used in this study as measuring tools to measure the variables expected to have a significant relationship with the audit expectation gap. The software used to conduct the analysis is SPSS 20 under the linear regression method. There was a total of 108 Malaysian auditors involved in this research. This study shows that auditors’ efforts and knowledge of society are significantly related to the audit expectation gap. The rest of the factors were tested, and it was found that they did not significantly affect the audit expectation gap. Therefore, auditors should utilize exemplary efforts and increase public awareness of the audit scope.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".