Differing Levels of Gratitude Between Romantic Partners: Concurrent and Longitudinal Links With Satisfaction and Commitment in Six Dyadic Datasets
Bibliographic record
Abstract
Gratitude promotes high quality relationships, but what happens when partners differ in their levels of gratitude? We examined the dyadic nature of gratitude in relationships using six longitudinal datasets (562 couples). Approaching the dyadic effect from the perspective of a “weak-link” hypothesis, we tested if the link between one partner's gratitude and relationship quality is reduced if the other partner is low in gratitude. Our results overall did not support this hypothesis as they indicated that grateful individuals were more satisfied and committed at baseline, and more grateful and committed over time, regardless of their partner's level of gratitude. As an alternative way to conceptualize the dyadic effect of gratitude, we explored a potential similarity effect using Dyadic Response Surface Analysis. Our results revealed no unique effect of having two partners reciprocating the same levels of gratitude above and beyond the effect of each partner's gratitude.
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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 | 0.005 | 0.015 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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 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".