Evolutionary Game of Group Cooperation Institutions for Chaoshan Businessmen in Ming and Qing Dynasties
Bibliographic record
Abstract
Chaoshan businessmen were widely involved in internal group cooperation. Based on historical and comparative institutional analysis, it is found that the cooperative behavior of Chaoshan businessmen in the Ming and Qing Dynasties is not simply an economic behavior. It reflects the historical evolution of the interaction between the regional cultures concerning the sea, clan and Confucianism, the governance of merchant groups with blood and geographical characteristics, and the beliefs of merchants in Mazu and Guan Yu. The evolutionary game theory is used to investigate the evolutionary process and the evolutionary stable strategy of the internal cooperative behavior of Chaoshan businessmen. It shows that due to the joint influence of regional culture, governance of merchant groups and beliefs of merchants, a multilateral collective punishment mechanism for untrustworthy merchants and a loss compensation mechanism for trustworthy merchants are established through channels such as chambers of commerce and ancestral temples. Thus, it reinforces the group cooperation institutions of integrity within Chaoshan merchant groups in the Ming and Qing Dynasties.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".