A World of Blame to Go Around: Cross-Cultural Determinants of Responsibility and Punishment Judgments
Bibliographic record
Abstract
Research finds collectivists make external attributions for others' behavior, whereas individualists make internal attributions. By focusing on external causes, collectivists should be less punitive toward those who harm others. Yet, many collectivistic cultures are known for strict retributive justice systems. How can collectivists simultaneously make external attributions and punish so harshly? We hypothesized that unlike individualists whose analytic tendencies engender a focus on mental states where judgments of accountability stem from perceptions of a harm-doer's agency, collectivists' holistic cognitive tendencies engender a focus on social harmony where judgments of accountability stem from perceived social consequences of the harmful act. Thus, what leads collectivists to make external attributions for behavior also leads to harsh punishment of those harming the collective welfare. Four cross-cultural studies found evidence that perceptions of a target's agency more strongly predicted responsibility and punishment judgments for individualists, whereas perceived severity of the harm was stronger for collectivists.
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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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".