Distraction Sneakers Decrease the Expected Level of Aggression within Groups: A Game‐Theoretic Model
Bibliographic record
Abstract
Hawk-dove games have been extensively used to predict the conditions under which group-living animals should defend their resources against potential usurpers. Typically, game-theoretic models on aggression consider that resource defense may entail energetic and injury costs. However, intruders may also take advantage of owners who are busy fighting to sneak access to unguarded resources, imposing thereby an additional cost on the use of the escalated hawk strategy. In this article we modify the two-strategy hawk-dove game into a three-strategy hawk-dove-sneaker game that incorporates a distraction-sneaking tactic, allowing us to explore its consequences on the expected level of aggression within groups. Our model predicts a lower proportion of hawks and hence lower frequencies of aggressive interactions within groups than do previous two-strategy hawk-dove games. The extent to which distraction sneakers decrease the frequency of aggression within groups, however, depends on whether they search only for opportunities to join resources uncovered by other group members or for both unchallenged resources and opportunities to usurp.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".