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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".