Preschoolers’ responses to prosocial opportunities during naturalistic interactions with peers: A cross‐cultural comparison
Bibliographic record
Abstract
Abstract The goal of this study was to better understand similarities and differences in preschool children's expression of needs and prosocial responsiveness to peers’ needs across two culturally distinct contexts. Preschoolers were observed in a semi‐naturalistic design across rural Mexico and urban Canada, wherein they were instructed to build a tower with blocks. Three‐ to 6‐year‐olds (N = 306; 48% female) were divided into 64 peer groups. We coded for children's expression of needs (instrumental, material, or emotional), responses to prosocial opportunities (prosociality, denial, or no response), prosociality without an apparent need (spontaneous prosociality), and types of prosocial behavior (helping, sharing, or comforting). While instrumental and material needs were expressed similarly across both samples, Tzotzil Maya children expressed fewer emotional needs than Canadian children. Failing to respond to others’ needs, followed by denial, were the most frequent need‐provoked response in both countries; surprisingly, only 9% of needs received a prosocial response. Though need‐provoked prosociality was rare in both cultural contexts, children engaged in considerable spontaneous prosociality which varied as a function of age, gender, and cultural context. Lastly, Canadian more than Tzotzil Maya children denied emotional and instrumental needs (but not material needs). The findings inform how cultural practices may shape the presentation of needs and prosocial responsiveness in peer interactions.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".