Associations between Caregivers' Global and Specific Attachment Representations and the Infant-Caregiver Attachment Relationship
Bibliographic record
Abstract
The primary objectives of the current study were: (1)to determine the extent to which caregivers’ conceptualizations of their own attachment history (global attachment representations are congruent with the way in which they conceptualize their relationships with a specific child (relationship-specific attachment representations); and (2)to evaluate whether these relationship-specific representations play a mediating role in the intergenerational transmission of attachment. Prenatal assessments of caregivers’ global attachment representations, as measured by the Adult Attachment Interview (AAI), and relationship-specific attachment representations, as measured by the Working Model of the Child Interview (WMCI), were obtained in a sample of 196 mother-infant dyads. Infant-caregiver attachment status was assessed using the Strange Situation Procedure (SSP) when infants were 12 months of age. Considerable correspondence was found between caregivers’ global and relationship-specific attachment representations; however, there was no evidence for the mediational hypothesis. The current study makes a significant contribution to the literature as it represents the first attempt to directly evaluate the links between caregivers’ global and relationship-specific attachment representations within the domain of caregiver-child relationships.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".