Testing the “Inverted‐U” Phenomenon in Moral Development on Recently Promoted Senior Managers and Partners*
Bibliographic record
Abstract
Abstract This paper examines the change in the average level of moral development over a 7.5‐year period of promotion, attrition, and survival in five Big 6 firms. The study improves upon previous cross‐sectional studies that found decreases in the average level of moral development at the senior manager and partner levels, which has been referred to as the “inverted‐U” phenomenon. Problems with these studies that limit the generalizability of their findings include their cross‐sectional nature and samples that usually come from one or two firms. Over a 7.5‐year period, we found that the participating Big 6 firms retained auditors with higher average levels of moral development (measured using the defining issues test), while those with lower average levels left the firms. The average level of moral development for new partners was at least as high as the group from which they came. This research suggests that the concern about Big 6 firms retaining a higher proportion of auditors with lower moral development may be an artifact of research design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.036 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".