Infants expect some degree of positive and negative reciprocity between strangers
Bibliographic record
Abstract
Social scientists from different disciplines have long argued that direct reciprocity plays an important role in regulating social interactions between unrelated individuals. Here, we examine whether 15-month-old infants (N = 160) already expect direct positive and negative reciprocity between strangers. In violation-of-expectation experiments, infants watch successive interactions between two strangers we refer to as agent1 and agent2. After agent1 acts positively toward agent2, infants are surprised if agent2 acts negatively toward agent1 in a new context. Similarly, after agent1 acts negatively toward agent2, infants are surprised if agent2 acts positively toward agent1 in a new context. Both responses are eliminated when agent2's actions are not knowingly directed at agent1. Additional results indicate that infants view it as acceptable for agent2 either to respond in kind to agent1 or to not engage with agent1 further. By 15 months of age, infants thus already expect a modicum of reciprocity between strangers: Initial positive or negative actions are expected to set broad limits on reciprocal actions. This research adds weight to long-standing claims that direct reciprocity helps regulate interactions between unrelated individuals and, as such, is likely to depend on psychological systems that have evolved to support reciprocal reasoning and behavior.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".