Explanatory limitations of cognitive-developmental approaches to morality.
Bibliographic record
Abstract
In response to Gibbs' defense of neo-Kohlbergian models of morality, the authors question whether revisions in Kohlberg's model constitute a coherent refinement of the cognitive-developmental approach. The authors argue that neo-Kohlbergian measures of moral development assess an aspect of morality (the most sophisticated forms of moral reasoning available to people) that plays a relatively minor role in determining the moral judgments and behavioral decisions people make in their everyday lives. Attempts to conceptualize stages as schema and to redefine moral decision-making in terms of automaticity will not solve these problems. Flexibility is an important aspect of moral maturity. Observed relations between stages of moral development and various forms of social conduct do not establish that the structures of moral reasoning that define stages of moral development exert a significant causal impact on moral behavior. Although cognitive-developmental approaches are equipped to account for some aspects of morality, a more general framework that organizes the insights from other theoretical approaches is needed.
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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 | 0.025 | 0.072 |
| 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 | 0.012 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".