Reciprocity creates a stake in one's partner, or why you should cooperate even when anonymous
Bibliographic record
Abstract
Why do we care so much for friends, even making sacrifices for them they cannot repay or never know about? When organisms engage in reciprocity, they have a stake in their partner's survival and wellbeing so the reciprocal relationship can persist. This stake (aka fitness interdependence) makes organisms willing to help beyond the existing reciprocal arrangement (e.g. anonymously). I demonstrate this with two mathematical models in which organisms play a prisoner's dilemma, and where helping keeps their partner alive and well. Both models shows that reciprocity creates a stake in partners' welfare: those who help a cooperative partner--even when anonymous--do better than those who do not, because they keep that cooperative partner in good enough condition to continue the reciprocal relationship. 'Machiavellian' cooperators, who defect when anonymous, do worse because their partners become incapacitated. This work highlights the fact that reciprocity and stake are not separate evolutionary processes, but are inherently linked.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".