Attachment Representations and Maternal Sensitivity in Low Socioeconomic Status Mothers
Bibliographic record
Abstract
According to attachment theory, mental representations are defined as dynamic cognitive guides that organize both perceptual and behavioral aspects of the self, attachment figure, and relationships with others. Based on this assumption, several studies had reported a relationship between attachment representations and the quality of care provided by mothers to their infants. This study explored on the relationship between maternal attachment representations, assessed by a narrative script task, and the quality of maternal care observed at home. Participants were 32 mothers between 19 and 44 years of age (M = 29.6, SD = 6.28) and their children between 8 and 10 months (M = 8.91, SD = 0.96). The results did not show a significant relationship between global scores of participants’ observed care (i.e., maternal sensitivity) and their attachment representations. However, a specific association was found between two dimensions of sensitivity (acceptance and active/animated interactions) and the narrative script that refers to a child’s physical injury event. Additionally, mothers who reported early separation experiences with their children showed a significant association between sensitivity and attachment representations on mother-child scripts. Moreover, these mothers showed lower scores on global sensitivity and on specific behavioral care dimensions, such as sensitive response and acceptance to child’s signals, than those of mothers that did not report separations early in their children’ lives.
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".