Impulsiveness does not prevent cooperation from emerging but reduces its occurrence: an experiment with zebra finches
Bibliographic record
Abstract
Reciprocal altruism, the most probable mechanism for cooperation among unrelated individuals, can be modelled as a Prisoner's Dilemma. This game predicts that cooperation should evolve whenever the players, who expect to interact repeatedly, make choices contingent to their partner's behaviour. Experimental evidence, however, indicates that reciprocity is rare among animals. One reason for this would be that animals are very impulsive compared to humans. Several studies have reported that temporal discounting (that is, strong preferences for immediate benefits) has indeed a negative impact on the occurrence of cooperation. Yet, the role of impulsive action, another facet of impulsiveness, remains unexplored. Here, we conducted a laboratory experiment in which male and female zebra finches (Taenyopigia guttata) were paired assortatively with respect to their level of impulsive action and then played an alternating Prisoner's Dilemma. As anticipated, we found that self-controlled pairs achieved high levels of cooperation by using a Generous Tit-for-Tat strategy, while impulsive birds that cooperated at a lower level, chose to cooperate with a fixed probability. If the inability of impulsive individuals to use reactive strategies are due to their reduced working memory capacity, thus our findings might contribute to explaining interspecific differences in cooperative behaviour.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".