Role of state and trait attachment dimensions on involvement in a close relationship
Bibliographic record
Abstract
The aim of the study was to investigate the association between trait and state attachment features and involvement in a couple-relationship. Eighty-four participants of different nationalities completed Childhood Trauma Questionnaire (CTQ), Toronto Alexithymia Scale (TAS-20), Attachment Style Questionnaire (ASQ), Experiences in Close Relationships-Revised (ECR-R), State Adult Attachment Measure (SAAM) and a personal questionnaire focused on involvement and amount of time spent in a couple-relationship. Results of the study showed that trait attachment features predicted involvement in a close relationship and the presence of a couple relationship predicted attachment state dimensions. Correlation analyses showed that the involvement in couple relationship was associated to CTQ Physical Neglect and SAAM Anxiety while participants without a partner had higher scores on CTQ Emotional Abuse, ECR-R Avoidance and SAAM Avoidance. Regression analyses showed that trait attachment features predicted time spent in a close relationship, while time spent in relationship predicted state attachment dimensions. Moreover, regression analysis showed that SAAM Security was predicted by ECR-R scales only in the sample of participants involved in a couple relationship.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".