Consequences, norms, and generalized inaction in moral dilemmas: The CNI model of moral decision-making.
Bibliographic record
Abstract
Research on moral dilemma judgments has been fundamentally shaped by the distinction between utilitarianism and deontology. According to the principle of utilitarianism, the moral status of behavioral options depends on their consequences; the principle of deontology states that the moral status of behavioral options depends on their consistency with moral norms. To identify the processes underlying utilitarian and deontological judgments, researchers have investigated responses to moral dilemmas that pit one principle against the other (e.g., trolley problem). However, the conceptual meaning of responses in this paradigm is ambiguous, because the central aspects of utilitarianism and deontology-consequences and norms-are not manipulated. We illustrate how this shortcoming undermines theoretical interpretations of empirical findings and describe an alternative approach that resolves the ambiguities of the traditional paradigm. Expanding on this approach, we present a multinomial model that allows researchers to quantify sensitivity to consequences (C), sensitivity to moral norms (N), and general preference for inaction versus action irrespective of consequences and norms (I) in responses to moral dilemmas. We present 8 studies that used this model to investigate the effects of gender, cognitive load, question framing, and psychopathy on moral dilemma judgments. The findings obtained with the proposed CNI model offer more nuanced insights into the determinants of moral dilemma judgments, calling for a reassessment of dominant theoretical assumptions. (PsycINFO Database Record
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".