Coalition formation: a game-theoretic analysis
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
There are many examples of individuals forming coalitions to obtain or protect a valuable resource. We present an analytical model of coalition formation in which individuals seek alliances if they judge themselves too weak to secure the resource alone. We allow coalition seeking to carry an investment cost (θ) and let contest outcomes depend probabilistically on the relative fighting strengths of contesting parties, with effective coalition strength directly proportional to combined partner strength. We identify the evolutionarily stable strength thresholds, below which individuals within triads should seek a coalition. We show that if θ exceeds a critical value, then unilateral fighting over resources is an evolutionarily stable strategy (ESS). Universal (3-way) coalitions are also an ESS outcome if θ is less than a second critical value. Both of these extreme solutions are less likely to arise, the greater the variance in fighting strengths and the greater the benefit from dominating opponents. Our analysis also identifies intermediate solutions in which only the weaker individuals seek coalitions: only then can a true coalition (2 vs. 1) form. We characterize these ESSs and show that true coalitions are more likely to arise when the effective strength of a coalition is less than the sum of its individual strengths (antergy). Alliances in primates are characterized by antergy, high reliability of strength as a predictor of contest outcome, and high variability in strengths. These are precisely the conditions in which in our model most favors true coalition formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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