The ability to regulate emotion is associated with greater well-being, income, and socioeconomic status.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Are people who are best able to implement strategies to regulate their emotional expressive behavior happier and more successful than their counterparts? Although past research has examined individual variation in knowledge of the most effective emotion regulation strategies, little is known about how individual differences in the ability to actually implement these strategies, as assessed objectively in the laboratory, are associated with external criteria. In two studies, we examined how individual variation in the ability to modify emotional expressive behavior in response to evocative stimuli is related to well-being and financial success. Study 1 showed that individuals who can best suppress their emotional reaction to an acoustic startle are happiest with their lives. Study 2 showed that individuals who can best amplify their emotional reaction to a disgust-eliciting movie are happiest with their lives and have the highest disposable income and socioeconomic status. Thus, being able to implement emotion regulation strategies in the laboratory is closely linked to well-being and financial success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it