Two forms of mother–child reciprocity and their links to children's cooperativeness
Bibliographic record
Abstract
Abstract The present study examined links between mother–child reciprocity and early elementary school children's cooperative behavior, an important marker of adjustment during this age. The study identified two distinct forms of mother–child reciprocity—following the child's lead and sharing the lead—and examined their interplay with maternal perception of the child. Mothers were observed in play interaction with their children (N = 106), and three groups were identified: mothers who followed their child's lead, mothers who shared the lead equally with the child, and mothers who showed neither form of reciprocity. Mothers’ view of their child as relatively non‐compliant or compliant was also assessed, and used in conjunction with reciprocity group to predict children's cooperation (two dependent measures: observed cooperation with the mother and teacher‐reported cooperative behavior at school). Consistent with prediction, children's observed cooperation with maternal requests was greatest when mothers followed the lead of children whom they viewed as relatively non‐compliant, and when mothers shared the lead with children whom they viewed as compliant. Teachers rated children as more cooperative in the classroom when mothers followed their children's lead, regardless of maternal view of child compliance. The results suggest that the two forms of reciprocity, following and sharing, are distinct.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".