Everyday dilemmas: New directions on the judgment and resolution of benevolence–integrity dilemmas
Bibliographic record
Abstract
Abstract Many everyday dilemmas reflect a conflict between two moral motivations: the desire to adhere to universal principles (integrity) and the desire to improve the welfare of specific individuals in need (benevolence). In this article, we bridge research on moral judgment and trust to introduce a framework that establishes three central distinctions between benevolence and integrity: (1) the degree to which they rely on impartiality, (2) the degree to which they are tied to emotion versus reason, and (3) the degree to which they can be evaluated in isolation. We use this framework to explain existing findings and generate novel predictions about the resolution and judgment of benevolence–integrity dilemmas. Though ethical dilemmas have long been a focus of moral psychology research, recent research has relied on dramatic dilemmas that involve conflicts of utilitarianism and deontology and has failed to represent the ordinary, yet psychologically taxing dilemmas that we frequently face in everyday life. The present article fills this gap, thereby deepening our understanding of moral judgment and decision making and providing practical insights on how decision makers resolve moral conflict.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".