Deconstructing maternal sensitivity: Predictive relations to mother‐child attachment in home and laboratory settings
Bibliographic record
Abstract
Abstract Despite the well‐documented importance of parental sensitivity for child development, there is a lack of consensus regarding how best to assess it. We investigated the factor structure of maternal caregiving behavior as assessed at 12 months by the Maternal Behavior Q‐Sort (Pederson & Moran) with 274 mother‐infant dyads. Subsequently, we examined associations between these empirically‐derived dimensions and child attachment, assessed in the home and laboratory (final N = 157). Three dimensions of maternal behavior were identified, corresponding fairly closely to Ainsworth's original scales. They were labeled Cooperation/Attunement, Positivity, and Accessibility/Availability. Only Cooperation/Attunement consistently predicted home‐based attachment at 15 months and 2 years, and at comparable strength to the overall sensitivity score, suggesting that this construct may be central to sensitivity. At 18 months, compared to their primarily secure counterparts, different types of laboratory‐assessed insecure attachment were associated with different patterns of maternal behavior. Mothers in avoidant relationships (n = 18) were low on Cooperation/Attunement and Accessibility/Availability, but fairly high on Positivity. Mothers of disorganized infants (n = 11) were Cooperative/Attuned but somewhat less Positive toward, and less Accessible/Available to, their infants. A multidimensional approach to parental behavior may facilitate the identification of parenting precursors of insecure parent‐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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".