MATERNAL REPRESENTATIONS AND INFANT ATTACHMENT: AN EXAMINATION OF THE PROTOTYPE HYPOTHESIS
Bibliographic record
Abstract
The prototype hypothesis suggests that attachment representations derived in infancy continue to influence subsequent relationships over the life span, including those formed with one's own children. In the current study, we test the prototype hypothesis by exploring (a) whether child-specific representations following actual experience in interaction with a specific child impacts caregiver-child attachment over and above the prenatal forecast of that representation and (b) whether maternal attachment representations exert their influence on infant attachment via the more child-specific representation of that relationship. In a longitudinal study of 84 mother-infant dyads, mothers' representations of their attachment history were obtained prenatally with the Adult Attachment Interview (AAI; M. Main, R. Goldwyn, & E. Hesse, 2002), representations of relationship with a specific child were assessed with the Working Model of the Child Interview (WMCI; C.H. Zeanah, D. Benoit, & L. Barton, 1986), collected both prenatally and again at infant age 11 months, and infant attachment was assessed in the Strange Situation Procedure (M.D.S. Ainsworth, M.C. Blehar, E. Walters, & S. Wall, 1978) when infants were 11 months of age. Consistent with the prototype hypothesis, considerable correspondence was found between mothers' AAI and WMCI classifications. A mediation analysis showed that WMCI fully accounted for the association between AAI and infant attachment. Postnatal WMCI measured at 11 months' postpartum did not add to the prediction of infant attachment, over and above that explained by the prenatal WMCI. Implications for these findings are discussed.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".