History, Expectations, and Leadership in the Evolution of Social Norms
Bibliographic record
Abstract
We study the evolution of the social norm of "cooperation" in a dynamic environment. Each agent lives for two periods and interacts with agents from the previous and next generations via a coordination game. Social norms emerge as patterns of behavior that are stable in part due to agents' interpretations of private information about the past, which are influenced by occasional past behaviors that are commonly observed. We first characterize the (extreme) cases under which history completely drives equilibrium play, leading to a social norm of high or low cooperation. In intermediate cases, the impact of history is potentially countered by occasional "prominent" agents, whose actions are visible by all future agents, and who can leverage their greater visibility to influence expectations of future agents and overturn social norms of low cooperation. We also show that in equilibria not completely driven by history, there is a pattern of "reversion" whereby play starting with high (low) cooperation reverts toward lower (higher) cooperation.
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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 | 0.006 | 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".