Audit partner achievement drive and audit quality
Bibliographic record
Abstract
Abstract In this study, we examine how achievement‐related tendencies are expressed in the professional auditing context, particularly through the interplay between the CEO and the audit partner. We use the facial width‐to‐height ratio (fWHR), a stable morphological trait widely applied in prior research, as a proxy for achievement drive. Using a sample of US audit partners from 2016 to 2019, we find that higher achievement drive is associated with enhanced audit quality, evidenced by fewer restatements and lower abnormal accruals. Auditors with higher achievement drive are also more likely to become industry experts, attain leadership positions, and achieve partnership status more quickly. Importantly, we find that high‐achievement‐drive audit partners are more inclined to assert dominance in negotiations, particularly when working with equally driven CEOs, leading to improved audit quality. Overall, our findings suggest that, when activated in auditing contexts, achievement‐oriented tendencies, as proxied by fWHR, are linked to higher audit quality.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".