The Development of Prosocial Behaviors in Young Children: A Prospective Population-Based Cohort Study
Bibliographic record
Abstract
Researchers know relatively little about the normative development of children's behaviors aimed at alleviating distress or discomfort in others. In this article, the authors aim to describe the continuity and discontinuity in the degree to which young children in the general population are reported to exhibit specific prosocial behaviors. Data came from the Québec Longitudinal Study of Child Development. Consistent with Hay's model of prosocial development, the results show that there were about as many children who stopped exhibiting prosocial behaviors between 29 and 41 months of age as there were children who started doing so during this period. Further, gender differences (girls > boys) in prosocial behaviors are either emerging or at least increasing in magnitude, with girls being more likely to start and boys being more likely to stop exhibiting these behaviors between 29 and 41 months of age. Consistent with the early-onset hypothesis, children who exhibit prosocial behaviors at 17 months of age are less likely to stop exhibiting the same behaviors between 29 and 41 months of age. Otherwise, if they did not exhibit prosocial behaviors at 29 months of age, they are also more likely to start doing so in the following year.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".