AGE DIFFERENCES EMOTION GLOBALIZING: AN EXAMINATION OF BOUNDARY CONDITIONS
Bibliographic record
Abstract
Abstract Emotion globalizing is an individual difference variable referring to the extent to which daily variations in an individual’s current emotions spillover into their evaluations of life satisfaction. The present research sought to: 1) extend the conception of emotion globalizing to stressor-related emotions, 2) examine age differences in these processes, and 3) differentiate associations with evaluations of life satisfaction and day satisfaction. To do so, we used daily diary data from two adult lifespan community samples [Study 1: N = 133 females, age range = 23-78; Study 2: N = 137, age range = 18-95]. Multilevel models revealed older (compared to younger) adults exhibited less negative (but not positive) emotion globalizing and stressor-related emotion globalizing. No age differences were revealed in the association between stressor-related emotions and day satisfaction. These findings support and extend assumptions underlying the mechanisms of emotion globalizing and inform theories of emotional aging.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".