Is professional exam performance associated with career success for Big 4 auditors? Evidence on gender differences
Bibliographic record
Abstract
Abstract This study examines whether better performance on the Certified Public Accountant (CPA) exam is associated with an auditor's career success and whether any relation differs based on gender. Our study adds to prior studies on the career development of auditors by showing that the auditor's performance on the exam predicts success during the auditor's career. Although there is little difference in the average CPA exam scores of male versus female auditors, we document gender differences in the relation between performance on the CPA exam and career success. Male auditors who pass the exam with superior results receive higher annual compensation than those with weaker results. They are also more likely to become partners in Big 4 accounting firms and have larger client portfolios. For female auditors, we find weaker or no association between CPA exam scores and compensation or other indicators of career success. Our path analysis shows that the mechanisms underlying career success work differently for men and women. CPA exam scores of male auditors have a direct effect on compensation and an indirect (mediating) effect through promotion to partner and client portfolio size. However, for female auditors, exam scores have no effect on promotion to partner or client portfolio size, and exam scores have a much smaller effect on compensation. Our findings suggest that CPA exam scores translate into career success for male auditors but not for female auditors.
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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 | 0.016 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".