Repairing one’s mood for the benefit of others: Agreeableness helps motivate low self-esteem people to feel better
Bibliographic record
Abstract
The chronic experience and expression of negativity is associated with poorer personal and relationship outcomes. Unfortunately, compared to people with high self-esteem, those with low self-esteem (LSEs) are less motivated to repair their negative moods. The current research examined mood repair in a novel way: in a close relationship context, when mood repair centers on benefitting others. We hypothesized that LSEs are more motivated than usual to repair negative moods when doing so benefits close others and when high in agreeableness (a trait involving prosocial motivation). We found support for our hypothesis with self-report (Studies 1 and 2) and behavioral measures (Study 2) of mood repair motivation, through an experimental manipulation of relationship context (Study 1), when participants expected to communicate with their romantic partners (Study 2), and for both sad (Study 1) and angry (Study 2) moods. Agreeable LSEs were more motivated to repair their negative moods than were disagreeable LSEs.
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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 | 0.000 |
| 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) | 0.003 | 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".