Bibliographic record
Abstract
Audit risk and business risk have been shown to affect audit fees and hours which are used to represent auditors' efforts in previous studies. However, most previous studies consider only one of these types of risk, or focus on audit risk rather than business risk to estimate auditor efforts. This study investigates the simultaneous effects of audit risk and business risk on auditor efforts. The data of Korean listed firm is used and business risk is measured by the degree of market competition. This study verifies that when audit risk and business risk are considered simultaneously, the effect of audit risk on audit fees and hours diminishes with lower business risk. Auditors are less concerned about audit risk in less competitive markets than in highly competitive markets because auditor is less exposed to litigation risk due to the nature of less competition. In addition, this study investigates the unilateral effect of fluctuations in business risk on auditor efforts. As a result, the study provides evidence that market competition is significantly associated with auditor efforts in terms of audit fees and hours.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".