ATTACHMENT AND CAREGIVER–INFANT INTERACTION: A REVIEW OF OBSERVATIONAL‐ASSESSMENT TOOLS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The relationship between maternal-infant interaction and attachment quality to infant developmental outcomes has long been established. As children mature, problems stemming from troubled caregiver-infant relations may result in referral to mental health or child protection services. The accurate and appropriate assessment of attachment is critical for early recognition of problematic relations and for informing suitable treatment modalities. Evaluating the quality of attachment poses a challenge for researchers and clinicians seeking to explore the association between infant development and the quality of early caregiving experiences. Although providing a definitive answer to the question of which of these assessment procedures is the single universal standard for measuring attachment quantity is beyond the scope of this article, readers will be provided with a description and comparison of strengths and limitations of the most commonly used measures of attachment, including the Strange Situation Procedure (M.D.S. Ainsworth, M.C. Blehar, E. Waters, & S. Wall, 1978), Attachment Q-Sort (E. Waters & K.E. Deane, 1985), Toddler Attachment Sort (TAS-45; J. Kirkland, D. Bimler, A. Drawneek, M. McKim, & A. Scholmerich, 2004), CARE-Index (P. Crittenden, 1985), Atypical Maternal Behavior Instrument for Assessment and Classification (AMBIANCE; E. Bronfman, E. Parsons, & K. Lyons-Ruth, 1999), Massie-Campbell Scale of Mother-Infant Attachment Indicators During Stress Scale (Attachment During Stress Scale; H.N. Massie & B.K. Campbell, 1983), and the Risky Situation Procedure (D. Paquette & M. Bigras, 2010).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it