THE COEVOLUTION OF GROUP SIZE AND LEADERSHIP: AN AGENT-BASED PUBLIC GOODS MODEL FOR PREHISPANIC PUEBLO SOCIETIES
Bibliographic record
Abstract
We present an agent-based model for voluntaristic processes allowing the emergence of leadership in small-scale societies, parameterized to apply to Pueblo societies of the northern US Southwest between AD 600 and 1300. We embed an evolutionary public-goods game in a spatial simulation of household activities in which agents, representing households, decide where to farm, hunt, and locate their residences. Leaders, through their work in monitoring group members and punishing defectors, can increase the likelihood that group members will cooperate to achieve a favorable outcome in the public-goods game. We show that under certain conditions households prefer to work in a group with a leader who receives a share of the group's productivity, rather than to work in a group with no leader. Simulation produces outcomes that match reasonably well those known for a portion of Southwest Colorado between AD 600 and 900. We suggest that for later periods a model incorporating coercion, or inter-group competition, or both, and one in which tiered hierarchies of leadership can emerge, would increase the goodness-of-fit.
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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 | 0.000 | 0.002 |
| 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) | 0.004 | 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".