Daily moral identity: Linkages with integrity and compassion
Bibliographic record
Abstract
OBJECTIVE: The present study investigated how much variability in moral identity scores is attributable to individual differences that are stable over time and how much variability reflects daily fluctuations. METHOD: Participants (N = 138, M age = 25.11 years, SD = 10.77; 82% female) were asked to report the self-importance of three moral attributes (being honest, fair, and caring) once a day for 50 consecutive days. Ratings were decomposed into between- and within-person variability and analyzed in relation to individuals' self-reported feelings of integrity and compassion using hierarchical linear modelling. RESULTS: Daily measures of moral identity exhibited more between- than within-person variability (64% vs. 36%). Furthermore, feelings of integrity and compassion were more strongly positively correlated with moral identity on the inter-individual level than the intra-individual level. CONCLUSION: Overall, findings suggest that moral identity has both trait- and state-like characteristics and might be best conceptualized as a characteristic adaptation evidencing both stability and change.
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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 | 0.010 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".