Mutual cooperation gives you a stake in your partner’s welfare, especially if they are irreplaceable.
Bibliographic record
Abstract
Why do we care so much for friends-much more than one might predict from reciprocity alone? According to a recent theory, organisms who cooperate with each other come to have a stake in each other's well-being: A good cooperator is worth protecting-even anonymously if necessary-so they can be available to cooperate in the future. Here, we present three experiments showing that reciprocity creates a stake in a partner's well-being, such that people are willing to secretly pay to protect good cooperative partners, if doing so keeps those partners available for future interaction. Participants played five rounds of a cooperative game (Prisoner's Dilemma) and then received an opportunity to help their partner, without the partner ever knowing. In Experiments 1 and 2, participants were more willing to help a cooperative partner if doing so kept that partner available for future rounds, compared to when the help simply raised the partner's earnings. This effect was specific to cooperative partners: The type of help mattered less for uncooperative partners or for recipients that participants did not directly interact with. In other words, an ongoing history of reciprocity gave people a stake in their partner's good condition but not their partner's payoff. Experiment 3 showed that participants had less stake in their partners if those partners could be easily replaced by another cooperator. These findings show that reciprocity and stake are not separate processes. Instead, even shallow reciprocity creates a deeper stake in a partner's well-being, including a willingness to help with zero expectation of recognition. Future work should examine how one's stake in partners is affected by ecological factors that affect the gains of cooperation and the ease of finding new partners. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".