A POPULATION MODEL OF THE STABILITY–FLEXIBILITY TRADEOFF
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Bibliographic record
Abstract
We present a population model illustrating the concept of virtual stability, i.e. the idea that complex adaptive systems with the capacity for self-monitoring and adaptive control are able to maintain themselves in states that would otherwise be unstable. The advantage gained from this is increased behavioral flexibility in the face of random environmental perturbations. In the model presented, transition probabilities between three population types are used to emulate stability: stable types have low probabilities of making transitions to other types, and unstable types have high transition probabilities. The model itself consists of two stable types and one unstable type, and conditions are explored that lead to dominance by the unstable type. Under certain conditions the unstable type can defeat a stable type, even in an environment that always favors the stable type.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it