Out-Group Threat Responses, In-Group Bias, and Nonapeptide Involvement Are Conserved across Vertebrates: (A Comment on Bruintjes et al., “Out-Group Threat Promotes Within-Group Affiliation in a Cooperative Fish”)
Bibliographic record
Abstract
The challenges and threats posed by out-groups have major effects on human social behavior and how individuals interact with one another. We briefly review evidence here that out-group threat similarly affects nonhuman animal behavior. Actual and potential threats posed by out-group individuals (unfamiliar and genetically nonrelated individuals of the same species) affect social behavior promoting "out-group" avoidance and "in-group" bias and enhancing in-group (familiar and/or genetically related individuals) affiliation and interactions. Individuals from out-groups present risks of pathogen exposure as well as being threats to resources, territory, and offspring. All of these threats function to promote in-group bias in humans and nonhumans. There are also striking similarities in the underlying neurobiological mechanisms mediating the responses to out-group threat and the expression of in-group bias. In particular, the evolutionarily conserved, hormone-regulated nonapeptide systems (oxytocin, arginine-vasopressin, and homologous neuropeptides and their receptors) are involved in the mediation of the detection and avoidance of out-groups and response to in-groups and facilitation of in-group responses across multiple vertebrate species. Consequently, comparative investigations of both the behavioral expression of and the mechanism underlying out-group avoidance and in-group bias are necessary for a full understanding of the evolution of social behavior and responses to in- and out-groups.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".