Selectivity in toddlers’ behavioral and emotional reactions to prosocial and antisocial others.
Bibliographic record
Abstract
Whereas some evidence suggests that toddlers consider targets' deservingness when deciding whom to help, other research demonstrates that toddlers help indiscriminately. The present findings shed light on this discrepancy by demonstrating that although toddlers do exhibit selectivity in giving behaviors, their emotional responses are comparatively indiscriminate. Specifically, in Experiment 1, 20-month-olds (N = 64) were more likely to give preferred toys to prosocial versus antisocial puppets, and more likely to withhold toys from antisocial versus prosocial puppets. Experiment 2 (N = 64) ruled out low-level explanations for the effects observed in Experiment 1, demonstrating that toddlers do not show the same effects when puppets' toy preferences are unclear. Despite providing evidence for selectivity in giving behaviors, across both experiments, toddlers were happier after giving than before giving, regardless of what they gave or whom they gave to. These results reveal the possibility of a divergence in early prosociality: Toddlers' giving behaviors are responsive to recipient deservingness, but their after-the-fact emotional reactions are responsive to giving acts themselves. Results are discussed in terms of their relevance to the debate regarding whether toddlers' early prosocial behaviors are discriminate versus indiscriminate. (PsycINFO Database Record
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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 | 0.002 |
| 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 | 0.000 |
| 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".