Attachment insecurities and under‐commitment in distressed couples: The role of positive and negative partner behaviors
Bibliographic record
Abstract
Research has rarely considered intermediate variables in the association between attachment insecurities and relationship commitment. Based on attachment theory and Rusbult's Investment Model, we tested whether positive and negative partner behaviors explain this association in 91 distressed couples undergoing therapy. Path analyses based on the Actor-Partner Interdependence Model revealed that individuals with attachment avoidance reported perceiving fewer positive behaviors from their partner, which was associated with their own higher under-commitment. Partners of individuals with avoidance also reported perceiving fewer positive partner behaviors, which was in turn associated with their own higher under-commitment. Partners of individuals with attachment anxiety perceived more positive behaviors from their partner, which was associated to their own lower under-commitment. Perceived negative partner behaviors were only directly associated with higher under-commitment. These findings imply that perceived positive partner behaviors may be a key aspect to target in relationship therapy in couples who present with high attachment insecurities.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".