Concessions, lifetime fitness consequences, and the evolution of coalitionary behavior
Bibliographic record
Abstract
The relationship between the costs of coalitionary behavior and the evolution of such behavior has not been closely examined by theoretical studies. Here, we create a set of life-history models for species whose coalitionary behavior is genetically determined to investigate how different types of costs afflicted upon members of failed coalitions, in terms of survival, fecundity, and social rank, may influence the nature of coalitionary behavior that emerges at evolutionary equilibrium. We also extend previous theory by examining the coevolution between coalitionary behavior and concessions granted by dominant individuals to prevent dominants from being targeted by coalitions. We show that species that form coalitions to contest social rank evolve to regularly form bridging coalitions under a vast majority of social and ecological settings, whereas species that contest fecundity form all-up coalitions under most conditions. Further, dominant individuals concede resources to subordinates to prevent coalitionary attacks only in very few circumstances, and these concessions occur only to ensure another individual is a more attractive coalition target. We compare and contrast results to empirical data to provide an evolutionary context for commonly observed coalitionary behaviors in the animal kingdom.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".