Trust, variability in relationship evaluations, and relationship processes.
Bibliographic record
Abstract
Little is known about why some people experience greater temporal fluctuations of relationship perceptions over short periods of time, or how these fluctuations within individuals are associated with relational processes that can destabilize relationships. Two studies were conducted to address these questions. In Study 1, long-term dating partners completed a 14-day diary study that assessed each partner's daily partner and relationship perceptions. Following the diary phase, each couple was videotaped trying to resolve the most important unresolved problem from the diary period. As predicted, (a) individuals who trusted their partners less reported greater variability in perceptions of relationship quality across the diary period; (b) they also perceived daily relationship-based conflict as a relatively more negative experience; and (c) greater variability in relationship perceptions predicted greater self-reported distress, more negative behavior, and less positive behavior during a postdiary conflict resolution task (rated by observers). The diary results were conceptually replicated in Study 2a, in which older cohabiting couples completed a 21-day diary. These same participants also took part in a reaction-time decision-making study (Study 2b), which revealed that individuals tend to compartmentalize positive and negative features of their partners if they (individuals) experienced greater variability in relationship quality during the 21-day diary period and were involved in higher quality relationships. These findings advance researchers' understanding of trust in intimate relationships and provide some insight into how temporal fluctuations in relationship quality may undermine relationships.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".