How Do the Accounting Profession and Higher Education Currently Approach Ethics Training?
Bibliographic record
Abstract
ABSTRACT Given the recurrence of ethical scandals in the accounting profession, the importance of ethics training continues to grow. We hand-collected data and performed a survey to investigate what measures are being taken by the profession and academia to ensure that accountants receive ethics training throughout their careers and before entering the workforce. We find variation across the CPA jurisdictions, such that the majority require candidates to pass an ethics exam for CPA licensure and mandate several hours of ethics CPE for renewal, whereas relatively few require individuals to pass a college-level ethics course. In response, accounting programs adopt numerous approaches to teaching ethics with half of our sample of schools offering either a standalone accounting or business ethics course, about a third offering both accounting and business ethics courses, and the remaining schools integrating ethics into coursework. Furthermore, approaches vary based on undergraduate versus graduate programs and state CPA requirements. Data Availability: Data are available upon request.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".