A Home‐based Description of Attachment in Physically Disabled Infants
Bibliographic record
Abstract
Abstract This study investigated attachment security and behavior in 34 physically disabled infants and 26 non‐disabled infants by using convergent, categorical (secure, avoidant and ambivalent) and continuous (Attachment Behavior Q‐Set) measures of the relationship, based on the same set of home observations. Proportions of attachment classifications were not different for disabled and non‐disabled infants, but insecure infants in the disabled group scored consistently lower on the AQS security score than non‐disabled insecure infants. This result suggests that while proportions of attachment classifications may not vary as a function of infant status, insecure disabled infants are more insecure than insecure non‐disabled infants. An analysis of 5 behavioral dimensions of the AQS showed that secure infants emitted the same kinds of attachment behaviors without regard for infant status. Insecure disabled infants, however, showed lower levels of secure base behavior and physical contact with mother than their non‐disabled counterparts, and showed a marginal tendency to fuss more as well. Discussion focuses on the potential benefits of using convergent, categorical and continuous measures of attachment in the study of both typical and atypical groups of infants.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".