Attachment working models as unconscious structures: An experimental test
Bibliographic record
Abstract
Internal working models of attachment (IWMs) are presumed to be largely unconscious representations of childhood attachment experiences. Several instruments have been developed to assess IWMs; some of them are based on self-report and others on narrative interview techniques. This study investigated the capacity of a self-report measure, the Inventory of Parent and Peer Attachment (IPPA; Armsden & Greenberg, 1987), and of a narrative interview method, the Adult Attachment Interview (AAI; George, Kaplan, & Main, 1985), to measure unconscious attachment models. We compared scores on the two attachment instruments to response latencies in an attachment priming task. It was shown that attachment organisation assessed by the AAI correlates with priming effects, whereas the IPPA scales were inversely or not related to priming. The results are interpreted as support for the assumption that the AAI assesses, to a certain degree, unconscious working models of attachment.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".