Disorganized attachment in infancy: a review of the phenomenon and its implications for clinicians and policy-makers
Bibliographic record
Abstract
Disorganized/Disoriented (D) attachment has seen widespread interest from policy makers, practitioners, and clinicians in recent years. However, some of this interest seems to have been based on some false assumptions that (1) attachment measures can be used as definitive assessments of the individual in forensic/child protection settings and that disorganized attachment (2) reliably indicates child maltreatment, (3) is a strong predictor of pathology, and (4) represents a fixed or static "trait" of the child, impervious to development or help. This paper summarizes the evidence showing that these four assumptions are false and misleading. The paper reviews what is known about disorganized infant attachment and clarifies the implications of the classification for clinical and welfare practice with children. In particular, the difference between disorganized attachment and attachment disorder is examined, and a strong case is made for the value of attachment theory for supportive work with families and for the development and evaluation of evidence-based caregiving interventions.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".