The quality of audit recommendation: The effect of role conflict, role ambiguity and work stress
Bibliographic record
Abstract
This research examines the effects of role conflict and role ambiguity on internal auditor's work stress and the quality of audit recommendations. These relationships were tested based on the survey taken from 96 internal auditors who served at several state universities in Indonesia. The hypothesis testing technique used SmartPLS analysis. The results showed that role conflict has a positive effect on the quality of audit recommendations while role ambiguity has a negative effect. Role conflict and role ambiguity have a positive and significant effect on work stress. Other test results show that internal auditor work stress does not show an effect on the quality of audit recommendations. The practical implication of this research is that to reduce ambiguity in carrying out audit tasks and to improve the quality of audit recommendations, it is necessary to consider an adequate work environment, especially the availability and adequacy of information needed by internal auditors in completing monitoring tasks. The role of conflict due to the presence of more than one task can cause work stress, although it does not interfere with the quality of audit recommendations. Therefore, it is necessary to pay attention to the allocation of work time that is not carried out at the same time so that the workload causes work stress.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".