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
The ability to regulate emotions is central to well-being, but healthy emotion regulation may not merely be about using the "right" strategies. According to the strategy-situation-fit hypothesis, emotion-regulation strategies are conducive to well-being only when used in appropriate contexts. This study is the first to test the strategy-situation-fit hypothesis using ecological momentary assessment of cognitive reappraisal-a putatively adaptive strategy. We expected people who used reappraisal more in uncontrollable situations and less in controllable situations to have greater well-being than people with the opposite pattern of reappraisal use. Healthy participants ( n = 74) completed measures of well-being in the lab and used a smartphone app to report their use of reappraisal and perceived controllability of their environment 10 times a day for 1 week. Results supported the strategy-situation-fit hypothesis. Participants with relatively high well-being used reappraisal more in situations they perceived as lower in controllability and less in situations they perceived as higher in controllability. In contrast, we found little evidence for an association between greater well-being and greater mean use of reappraisal across situations.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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