The silver lining of a mind in the clouds: interesting musings are associated with positive mood while mind-wandering
Bibliographic record
Abstract
The negative effects of mind-wandering on performance and mood have been widely documented. In a recent well-cited study, Killingsworth and Gilbert (2010) conducted a large experience sampling study revealing that all off-task episodes, regardless of content, have equal to or lower happiness ratings, than on-task episodes. We present data from a similarly implemented experience sampling study with additional mind-wandering content categories. Our results largely conform to those of the Killingsworth and Gilbert (2010) study, with mind-wandering generally being associated with a more negative mood. However, subsequent analyses reveal situations in which a more positive mood is reported after being off-task. Specifically when off-task episodes are rated for interest, the high interest episodes are associated with an increase in positive mood compared to all on-task episodes. These findings both identify a situation in which mind-wandering may have positive effects on mood, and suggest the possible benefits of encouraging individuals to shift their off-task musings to the topics they find most engaging.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".