Examining Ecological Constraints on the Intergenerational Transmission of Attachment Via Individual Participant Data Meta-analysis
Bibliographic record
Abstract
Abstract Parents’ attachment representations and child–parent attachment have been shown to be associated, but these associations vary across populations (Verhage et al., 2016). The current study examined whether ecological factors may explain variability in the strength of intergenerational transmission of attachment, using individual participant data (IPD) meta-analysis. Analyses on 4,396 parent–child dyads (58 studies, child age 11–96 months) revealed a combined effect size of r = .29. IPD meta-analyses revealed that effect sizes for the transmission of autonomous-secure representations to secure attachments were weaker under risk conditions and weaker in adolescent parent–child dyads, whereas transmission was stronger for older children. Findings support the ecological constraints hypothesis on attachment transmission. Implications for attachment theory and the use of IPD meta-analysis are discussed. The title for this Special Section is Meta-analysis and Individual Participant Data Synthesis in Child Development, edited by Glenn I. Roisman and Marinus H. van IJzendoorn
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.029 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.024 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".