Eleven-Month-Old Infants Preferentially Look at Helpers But Do Not Reliably Incorporate Inconsistency Into Their Evaluations
Bibliographic record
Abstract
Adults quickly form character impressions from their observations of others’ behavior and sometimes manage to do so even when an agent’s behaviors are inconsistent. Developmental psychology has provided some evidence that infants, like adults, may form impressions based on prosocial and antisocial acts: They prefer those who behave prosocially versus antisocially toward third parties. That said, previous work suggests that infants find it difficult to evaluate characters’ whose behaviors are inconsistent. The present, preregistered experiments further explored this phenomenon in an older age group (11-month-olds; N = 189) using an online format and presenting infants with giving versus taking, a different type of prosocial versus antisocial action than in previous work. In a preliminary experiment, we successfully replicated the finding that infants prefer looking to helpful givers over unhelpful takers when actors behave consistently and when each actor performed 4 actions. We then used the same online testing methods to examine infants’ evaluations of inconsistent actors. In Experiment 1, infants appeared able to evaluate inconsistent actors, preferring more versus less prosocial actors when their inconsistent act occurred last in a series of 5 acts; however, they did not appear to find the behavioral inconsistency unexpected, suggesting they may have failed to notice it. In Experiment 2, we adjusted the order of inconsistent acts and put the inconsistent act first, and attempted to conceptually replicate the findings of Experiment 1. Here, infants did not prefer more prosocial actors. Together with past work, these findings suggest that while infants prefer agents whose actions are consistently prosocial versus antisocial, they do not reliably incorporate behavioral inconsistency into their social evaluations.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".