The Impact of Workplace Mentors on the Moral Disengagement of Business Student Protégés
Bibliographic record
Abstract
Educators and practitioners often raise the question of whether business schools sufficiently prepare students to stay morally engaged when faced with ethical dilemmas in the workforce. Specifically, they criticize the theoretical nature of traditional in-class exercises for inhibiting students’ moral development. We investigate the impact working business mentors have on business student moral disengagement. We collected three waves of data from an 8-month formal mentoring program that matched business students with working mentors from the business community. We found that student protégé moral disengagement decreased during the mentoring program as a function of mentor ethical leadership skills, moral identity internalization, and moral awareness. Consequently, we recommend that mentoring programs pay close attention to these mentor characteristics to elevate business student moral reasoning and avoid unintended negative consequences. To guide mentoring programs in this endeavor, we provide specific recommendations for structuring a training program that focuses on improving mentor critical thinking, moral awareness, and ethical leadership.
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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 | 0.016 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".