“I did not expect that from you!”: Unforgiveness dimensions, attachment insecurities, and relationship under‐commitment following a relational transgression
Bibliographic record
Abstract
Abstract After experiencing a relational transgression, individuals may not forgive their partner. However, unforgiveness may prove detrimental to relationship functioning for both partners, and even more so when combined with individual and relational risk factors. This study examined the associations between unforgiveness dimensions (cognitive‐evaluative, emotional‐ruminative, and offender reconstrual) and relationship under‐commitment in couples who experienced a relational transgression, and the moderating roles of attachment insecurities (attachment anxiety and avoidance) and the sample type (community vs. clinical) in these associations. The sample included 114 couples (42 from the community and 72 seeking relationship therapy); both partners completed online questionnaires. Path analyses revealed associations between the cognitive‐evaluative and offender reconstrual dimensions, and higher under‐commitment in offended partners. The association between offender reconstrual and under‐commitment was only present when offended partners exhibited low to moderate levels of attachment anxiety. The emotional‐ruminative dimension was associated with under‐commitment in both partners, but only when offended partners reported low levels of attachment avoidance. No moderation effect was found for the sample type. This study enhances understanding of post‐transgression unforgiveness and unravels some individual characteristics that are likely to affect how it relates to both partners' under‐commitment.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".