The quality of the mother–child relationship in high-risk dyads: Application of the Emotional Availability Scales in an intergenerational, longitudinal study
Bibliographic record
Abstract
The present research examined how family psychosocial risk may be associated with emotional availability (EA) across age and time in two longitudinal, intergenerational studies with high-risk, disadvantaged mother-child dyads. Study 1 examined dyads during preschool and middle childhood. Study 2 examined a different sample of dyads, tested intensively at five time points (6, 12, and 18 months; preschool; and school age). Across studies, maternal childhood histories of aggression and social withdrawal predicted negative EA (higher levels of maternal hostility) during mother-child interactions at preschool age. In Study 1, mothers with higher levels of social withdrawal during childhood had preschoolers who were less appropriately responsive to and involving of their mothers during interactions. In Study 2, higher levels of observed appropriate maternal structuring predicted child responsiveness while observed maternal sensitivity (and structuring) predicted observed child involvement. More maternal social support and better home environment combined with lower stress predicted better mother-child relationship quality. Findings contribute to the burgeoning literature on EA by focusing on a high-risk community sample across time and generations. Results are interpreted in light of the developmental psychopathology framework, and have implications for a broader understanding of how EA is related to parental history and personal characteristics, as well as ongoing family and environmental context.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".