Two Sides of the Same Coin? Viewing Altruism and Aggression Through the Adaptive Lens of Kinship
Bibliographic record
Abstract
Abstract Are altruism and aggression polar opposites, or are they two sides of the same coin? In this review, the authors examine the evolved biological roots of these behaviors and focus on the psychology of kinship and how it can serve to bridge both behaviors. Drawing on inclusive fitness theory (), the kinship, acceptance, and rejection model of altruism and aggression (KARMAA; ), and a sociofunctional threat‐based approach to prejudice (), the authors propose that altruism and aggression can be viewed as two sides of the same coin depending on context and perspective. For example, a mother bear protecting her cubs by attacking a predator may be simultaneously exhibiting an act of altruism and aggression. After offering some empirical support for their view, the authors discuss the theoretical and practical implications of viewing altruism and aggression as related constructs at the intrapersonal, interpersonal, and intergroup levels.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| 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".