Moral parochialism and contextual contingency across seven societies
Bibliographic record
Abstract
Human moral judgement may have evolved to maximize the individual's welfare given parochial culturally constructed moral systems. If so, then moral condemnation should be more severe when transgressions are recent and local, and should be sensitive to the pronouncements of authority figures (who are often arbiters of moral norms), as the fitness pay-offs of moral disapproval will primarily derive from the ramifications of condemning actions that occur within the immediate social arena. Correspondingly, moral transgressions should be viewed as less objectionable if they occur in other places or times, or if local authorities deem them acceptable. These predictions contrast markedly with those derived from prevailing non-evolutionary perspectives on moral judgement. Both classes of theories predict purportedly species-typical patterns, yet to our knowledge, no study to date has investigated moral judgement across a diverse set of societies, including a range of small-scale communities that differ substantially from large highly urbanized nations. We tested these predictions in five small-scale societies and two large-scale societies, finding substantial evidence of moral parochialism and contextual contingency in adults' moral judgements. Results reveal an overarching pattern in which moral condemnation reflects a concern with immediate local considerations, a pattern consistent with a variety of evolutionary accounts of moral judgement.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".