Links between children's attachment behavior at early school-age, their attachment-related representations, and behavior problems in middle childhood
Bibliographic record
Abstract
The objective of the present study was to examine associations between children's attachment behavior at early school-age, dimensions of narrative performance, and behavior problems as assessed in middle childhood. Children's attachment patterns with mother were assessed at age 6 ( N = 127) using the Main and Cassidy (1988) separation—reunion classification system. Two years later, these children ( N = 109) completed the Narrative Story Stem Battery (Bretherton, Oppenheim, Buchsbaum, Emde, & The MacArthur Narrative Group, 1990), and teachers rated their level of behavior problems using the Social Behavior Questionnaire (Tremblay, Vitaro, Gagnon, Piché, & Royer, 1992). Results indicated that secure children depicted fewer conflict themes in their narratives than did disorganized/controlling children, produced more discipline themes than avoidant children, and had higher coherence scores than ambivalent children. Avoidant children also depicted fewer conflict themes than disorganized/controlling children. Finally, children's narrative conflict themes significantly predicted both level of externalizing and total behavior problems, even after controlling for variance explained by gender and disorganized/controlling attachment behavior. Girls' narratives were more likely to evoke discipline and affection/affiliation themes, and to be more coherent than boys' narratives.
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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 | 0.003 |
| 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 | 0.000 |
| 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".