Understanding the transmission of attachment using variable- and relationship-centered approaches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The interrelations of maternal attachment representations, mother–infant interaction in the home, and attachment relationships were studied in 99 adolescent mothers and their 12-month-old infants. A q-factor analysis was used to identify emergent profiles of mother and infant interaction. Traditional multivariate statistical analyses were complemented by a relationship-based approach utilizing latent class analysis. The results confirmed many theoretical predictions linking interaction with autonomous maternal representations and secure attachment, but failed to support a mediating role for maternal sensitivity. Strong associations were found between mothers displaying nonsensitive and disengaged interaction profiles, infants who did not interact harmoniously with the mother and preferred interaction with the visitor, unresolved maternal representations, and disorganized attachment relationships. Moreover, maternal nonsensitive and disengaged interaction in the home mediated the association between unresolved representations and disorganization. The results of the latent class analysis were consistent with these findings and revealed additional, empirically derived associations between attachment classifications and patterns of interactive behavior, some of which prompt a reconsideration of our current understanding of attachment transmission in at-risk populations.This research was supported by a predoctoral fellowship to the first author from the Social Sciences and Humanities Research Council and by research grants to the second and third authors from the Social Sciences and Humanities Research Council, the Ontario Mental Health Foundation, and Health Canada.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it