Assessing attachment for family court decision making
Bibliographic record
Abstract
Purpose – Attachment has long been considered relevant to child care proceedings. However, compared to other forms of evidence, it has been limited by the lack of consistent methods of assessment, training of experts, and empirical evidence. To reduce these limitations, The International Association for the Study of Attachment (IASA) has developed a Family Attachment Court Protocol for assessment and formulation of attachment issues. The purpose of the Protocol is to act as a guide to good practice and to begin a process of improving the application of attachment to family court proceedings. Design/methodology/approach – The Dynamic-Maturational Model of Attachment and Adaptation (DMM) and its associated assessments were adapted for forensic use. The resulting Family Attachment Court Protocol was trialed in cases before 15 judges in five countries and modified based on feedback. Findings – The judges and most of the professionals working for the court expressed approval of the new Protocol. Research limitations/implications – Implementation of the Protocol will require additional authorised experts. Practical implications – The primary practical implication is that the courts will receive verifiable evidence on attachment can be tested and, thus, validated or disproven. Social implications – If accepted, the IASA Protocol will reduce the idiosyncratic nature of child care proceedings and increase the rigour of professional qualification to address attachment. Originality/value – The IASA Protocol is new and valuable because its theoretical underpinnings in the DMM are based on both clinical and also neurological evidence about protection from danger, and it can replace untestable expert opinion about attachment with evidence-based assessment and transparent formulation of recommendations.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".