Positive event diversity: Relationship with personality and well‐being
Bibliographic record
Abstract
OBJECTIVE: Examining the personality and well-being correlates of positive event diversity. BACKGROUND: Past research has highlighted that personality traits are linked to the frequency of daily positive events. This study is the first to examine positive event diversity, the extent to which positive events are spread across multiple types of positive life domains, as well as its personality and well-being correlates. METHOD: We conducted parallel analyses of three daily diary datasets (Ns = 1919, 744, and 1392) that included evening assessment of daily positive events and affective well-being. The Big Five personality traits were assessed in baseline surveys. RESULTS: Positive Event Diversity was related to higher person-mean daily positive affect but not negative affect. Higher Extraversion, Agreeableness, Openness, and lower Neuroticism were correlated with more positive event diversity. These associations became nonsignificant when controlling for positive event frequency. Positive event frequency moderated the link between positive event diversity and person-mean affect, such that higher positive event diversity was associated with higher negative and lower positive affect for people who experienced more frequent positive events. CONCLUSIONS: No consistent evidence was found for personality as a moderator of the positive event diversity-well-being link across the three studies. Further, the well-being implications of positive event diversity may be better understood when interpreting them alongside indexes of positive event frequency.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".