The development of internalizing problems in early childhood: The importance of sibling clustering.
Bibliographic record
Abstract
Within family sibling clustering of internalizing problems is examined during the early childhood period. Sibling clustering, the ongoing sibling similarity in internalizing problems, may be a result of heritability of internalizing problems, as well as shared environmental effects. Clustering may also result from the time-varying influence of sibling socialization, where 1 sibling is teaching or modeling internalizing problems to the other sibling. We compared a traditional cross-lagged panel model with a recently developed multilevel statistical model that differentiates the 2 mechanisms. Sibling clustering was operationalized as the family level, time-invariant variance in internalizing problems, and differentiated from sibling socialization, the cross-lagged (time-varying) association between earlier child behavior and later sibling behavior. A 3-wave longitudinal study tracked 916 children (age M = 3.46, SD = 2.23) in 397 families using a 2-parent composite score of internalizing problems. Results suggest the importance of accounting for sibling clustering in the context of a panel study, as its inclusion in the model eliminated the identified time-varying, sibling socialization effects. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".