Reconciling the self and morality: An empirical model of moral centrality development.
Bibliographic record
Abstract
Self-interest and moral sensibilities generally compete with one another, but for moral exemplars, this tension appears to not be in play. This study advances the reconciliation model, which explains this anomaly within a developmental framework by positing that the relationship between the self's interests and moral concerns ideally transforms from one of mutual competition to one of synergy. The degree to which morality is central to an individual's identity-or moral centrality-was operationalized in terms of values advanced implicitly in self-understanding narratives; a measure was developed and then validated. Participants were 97 university students who responded to a self-understanding interview and to several measures of morally relevant behaviors. Results indicated that communal values (centered on concerns for others) positively predicted and agentic (self-interested) values negatively predicted moral behavior. At the same time, the tendency to coordinate both agentic and communal values within narrative thought segments positively predicted moral behavior, indicating that the 2 motives can be adaptively reconciled. Moral centrality holds considerable promise in explaining moral motivation and its development.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| 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".