Development and preliminary psychometric evaluation of the Tripartite Attachment Battery
Bibliographic record
Abstract
Mikulincer and Shaver's (2007) model of attachment-system functioning and dynamics in adulthood provided the impetus for developing three self-report measures assessing adult attachment characteristics. These scales are collectively referred to as the Tripartite Attachment Battery (TAB). The Secure Attachment Scale assesses attachment insecurity-security along a single dimension. This is the first self-report measure designed to directly assess attachment security in adults in this manner. The Organized Insecurity Scale includes subscales assessing two specific forms of insecurity: attachment anxiety and attachment avoidance. Unlike other popular measures of adult attachment assessing these constructs, it also includes items that capture secondary attachment strategies related to anxiety (i.e., hyperactivation) and avoidance (i.e., deactivation). The Disorganized Attachment Scale is based on an earlier self-report measure. It captures a more severe form of attachment insecurity characterised by fear, confusion about relationships, and distrust. The process of developing items for these measures is briefly described and an initial psychometric evaluation of each measure is presented. These evaluations were aimed at: (a) assessing the internal consistency of each scale or subscale, and (b) identifying poor items that may need to be removed or modified. A small convenience sample (N = 53) was used. Each measure had a high level of internal consistency, with coefficient alphas ranging from .81 to .93. Recommendations regarding further revising and evaluating the measures included in the TAB are presented.
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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 | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".