From inter-group conflict to inter-group cooperation: insights from social insects
Bibliographic record
Abstract
The conflict between social groups is widespread, often imposing significant costs across multiple groups. The social insects make an ideal system for investigating inter-group relationships, because their interaction types span the full harming-helping continuum, from aggressive conflict, to mutual tolerance, to cooperation between spatially separate groups. Here we review inter-group conflict in the social insects and the various means by which they reduce the costs of conflict, including individual or colony-level avoidance, ritualistic behaviours and even group fusion. At the opposite extreme of the harming-helping continuum, social insect groups may peacefully exchange resources and thus cooperate between groups in a manner rare outside human societies. We discuss the role of population viscosity in favouring inter-group cooperation. We present a model encompassing intra- and inter-group interactions, and local and long-distance dispersal. We show that in this multi-level population structure, the increased likelihood of cooperative partners being kin is balanced by increased kin competition, such that neither cooperation (helping) nor conflict (harming) is favoured. This model provides a baseline context in which other intra- and inter-group processes act, tipping the balance toward or away from conflict. We discuss future directions for research into the ecological factors shaping the evolution of inter-group interactions. This article is part of the theme issue 'Intergroup conflict across taxa'.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".