More ‘altruistic’ punishment in larger societies
Bibliographic record
Abstract
If individuals will cooperate with cooperators, and punish non-cooperators even at a cost to themselves, then this strong reciprocity could minimize the cheating that undermines cooperation. Based upon numerous economic experiments, some have proposed that human cooperation is explained by strong reciprocity and norm enforcement. Second-party punishment is when you punish someone who defected on you; third-party punishment is when you punish someone who defected on someone else. Third-party punishment is an effective way to enforce the norms of strong reciprocity and promote cooperation. Here we present new results that expand on a previous report from a large cross-cultural project. This project has already shown that there is considerable cross-cultural variation in punishment and cooperation. Here we test the hypothesis that population size (and complexity) predicts the level of third-party punishment. Our results show that people in larger, more complex societies engage in significantly more third-party punishment than people in small-scale societies.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".