Personality, Gender, and the Ways People Perceive Moral Dilemmas in Everyday Life
Bibliographic record
Abstract
This study examined the relations among personality, gender, and the ways people perceive moral dilemmas in their everyday lives. Participants were 117 young women and men who responded to Gibbs, Basinger, and Fuller’s (1992) Sociomoral Reflection Measure and to antisocial, prosocial, and social pressure types of real-life moral dilemma. Participants completed measures assessing shame and guilt (Harder, 1987; Tangney, 1990) and identity (Bennion & Adams, 1986). The female participants reported feeling more guilt about the prosocial dilemma and viewed the social pressure dilemma as more care-oriented than males did. Scores on the shame and guilt measures were not related to guilt associated with the real-life dilemmas. Identity-achieved scores were negatively related to feeling guilty about social pressure dilemmas involving parents. Discussion focuses on the relevance of personality, gender, and family influences for a model of real-life moral reasoning, with implications for development and education.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".