Children's utilization of emotion expectancies in moral decision‐making
Bibliographic record
Abstract
This study investigated the relevance of emotion expectancies for children's moral decision-making. The sample included 131 participants from three different grade levels (M = 8.39 years, SD = 2.45, range 4.58-12.42). Participants were presented a set of scenarios that described various emotional outcomes of (im)moral actions and asked to decide what they would do if they were in the protagonists' shoes. Overall, it was found that the anticipation of moral emotions predicted an increased likelihood of moral choices in antisocial and prosocial contexts. In younger children, anticipated moral emotions predicted moral choice for prosocial actions, but not for antisocial actions. Older children showed evidence for the utilization of anticipated emotions in both prosocial and antisocial behaviours. Moreover, for older children, the decision to act prosocially was less likely in the presence of non-moral emotions. Findings suggest that the impact of emotion expectancies on children's moral decision-making increases with age. Contrary to happy victimizer research, the study does not support the notion that young children use moral emotion expectancies for moral decision-making in the context of antisocial actions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".