Sibling relationship quality moderates the associations between parental interventions and siblings’ independent conflict strategies and outcomes.
Bibliographic record
Abstract
This study extends research on sibling conflict strategies and outcomes by examining unique and interactive associations with age, relative birth order, sibling relationship quality, and caregivers' interventions into conflict. Each of 62 sibling dyads (older sibling mean age = 8.39 years; younger sibling mean age = 6.06 years) discussed 1 recurring conflict alone (dyadic negotiation) and a 2nd conflict with their primary parental caregiver (triadic negotiation). Negotiations were coded for children's conflict strategies, outcomes, and caregiver interventions; each family member provided ratings of sibling relationship quality. Results revealed that age was associated with siblings' constructive strategies, particularly in the dyadic negotiation. With age controlled, younger siblings referred more frequently to their own perspective. Caregivers' future orientation in the triadic negotiation was associated with children's future orientation in the dyadic negotiation; however, this association was most evident when sibling relationship quality was high. Similarly, caregivers' past orientation was positively associated with dyadic compromise, especially when relationship quality was high. Results reveal the value of simultaneously considering associations among parental, affective, and developmental correlates of sibling conflict strategies.
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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 | 0.002 | 0.012 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".