Mothers’ communicative cues and the development of infants’ helping: Linking participation and problem solving in the first year of life
Bibliographic record
Abstract
Abstract There is an ongoing debate on the role of socialization in the development of infants’ helping. Although opportunities for the socialization of early helping are rare in problem solving (bystander intervention), there are many opportunities for socialization in participation (working alongside others), and infants’ experiences of participation could socialize problem solving indirectly. The present study links participation and problem solving conceptually by drawing on a Hebbian concept of indirect learning and through a study examining mothers’ communicative cues in both forms of helping. Forty mother‐infant dyads engaged in two semi‐structured helping tasks, a participation task and a problem‐solving task at five, eight, and ten months of age. Mothers’ communicative cues and infants’ return of the object were examined using coding schemes adapted from prior research. Mothers used similar communicative cues (reaches, give‐me gestures, and verbal requests) in both tasks, and more maternal scaffolding contributed to greater object handover. Infants showed higher object handover in participation tasks. The findings, framed in Tomasello's neo‐Vygotskian account of prosocial development, offer a synthesis of the debate on the role of socialization where prosocial behavior emerges first between people, and then becomes individualized.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".