A Person-Centered Approach to Moral Judgment
Bibliographic record
Abstract
Both normative theories of ethics in philosophy and contemporary models of moral judgment in psychology have focused almost exclusively on the permissibility of acts, in particular whether acts should be judged on the basis of their material outcomes (consequentialist ethics) or on the basis of rules, duties, and obligations (deontological ethics). However, a longstanding third perspective on morality, virtue ethics, may offer a richer descriptive account of a wide range of lay moral judgments. Building on this ethical tradition, we offer a person-centered account of moral judgment, which focuses on individuals as the unit of analysis for moral evaluations rather than on acts. Because social perceivers are fundamentally motivated to acquire information about the moral character of others, features of an act that seem most informative of character often hold more weight than either the consequences of the act or whether a moral rule has been broken. This approach, we argue, can account for numerous empirical findings that are either not predicted by current theories of moral psychology or are simply categorized as biases or irrational quirks in the way individuals make moral judgments.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".