Evolutionary Dynamics of Mixed Rings of Coordinators and Anticoordinators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Decision-making based on peers’ actions often results in one of the following two groups: coordinators who tend to blend in with the population and make trending decisions, and anticoordinators who act against the majority. Only mixed networks of both coordinators and anticoordinators are capable of not reaching an equilibrium state, where every individual is satisfied with her choice. However, the conditions for nonequilibration, and more challengingly, the characterization of the non-equilibrium limit set remain concealed. We answer these problems for ring networks. We show that a mixed ring of coordinators and anticoordinators equilibrates if and only if it does not contain a particular arrangement of consecutive agents, and never equilibrates if and only if it contains a particular arrangement of consecutive agents with particular actions. As a result, a ring may admit both equilibrium and non-equilibrium limit sets. We further investigate the stability of the equilibrium states of the resulting network dynamics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 it