Analysis of latent profiles of gratitude, indebtedness, and religiosity among individuals in romantic relationships in the United States, Canada, and South Korea
Bibliographic record
Abstract
Interpersonal gratitude, a positive emotion arising from receiving benefits, often co-occurs with indebtedness, an obligation to repay a favor. While valued across religions, gratitude and indebtedness have been predominantly examined in Western cultures, where gratitude is often a univalent positive experience. In East Asian cultures, the co-occurrence of positive and negative emotions is more common. In this study, we used latent profile analysis to identify subgroups of individuals based on their gratitude, indebtedness, and religiosity. In both samples (United States/Canada N = 543; South Korea N = 530), we identified three distinct profiles, which were similar across samples. In the American/Canadian sample, grateful nonreligious (high gratitude, moderate indebtedness, low religiosity) and in South Korea, highly indebted moderates (high gratitude, high indebtedness, moderate religiosity) experienced lower life satisfaction and self-esteem. These findings underscore cultural similarities in gratitude in romantic relationships, while highlighting how religiosity and indebtedness differentially impact personal well-being across cultures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".