Reconsidering the links between sibship size, maternal sensitivity, and child attachment: A multidimensional interactive approach.
Bibliographic record
Abstract
Despite being a well-documented predictor of children's cognitive and social development, sibship has received remarkably little attention in the attachment and maternal sensitivity literature. The only study that has examined both sensitivity and attachment in relation to sibship found greater maternal sensitivity but no more secure attachment among first-born infants. In the current study, we sought to examine the same links while testing two related hypotheses: that sibship size relates only to some specific aspects of sensitivity, and that sibship size relates to sensitivity only among certain mothers, namely those who are at risk for suboptimal parenting because of an insecure attachment state of mind. We assessed three dimensions of maternal sensitivity at 12 months and child attachment at 15 and 25 months among 258 mother-infant dyads living in intact biparental families. Compared with mothers who had fewer children, those with more children were observed to be less accessible/available, less positive, but not less cooperative/attuned, when interacting with their infant. These links were moderated by maternal attachment state of mind, such that significant relations were observed only among mothers presenting a more insecure state of mind. Finally, sibship size was unrelated to attachment. These findings suggest that failure to consider different dimensions of sensitivity or important parental moderators may result in the erroneous conclusion that birth order and sibship size are inconsequential for parent-child relationships. (PsycINFO Database Record
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".