Is Trait Boredom Redundant?
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 present study explored trait boredom's usefulness as an individual difference measure for the prediction of psychosocial problems. The most striking findings were trait boredom's unique prediction of depression (an internalizing problem) and anger (an externalizing problem), over and above several other well-established trait variables, including neuroticism, impulsivity, emotional awareness, inattention, behavioral inhibition, and behavioral activation. The findings also confirmed predictions regarding differences between two main measures of trait boredom. Specifically, whereas the Boredom Proneness Scale was more closely linked to internalizing problems, the Boredom Susceptibility Scale was more closely linked to externalizing problems. This discrepancy is consistent with the growing body of literature suggesting that these two scales measure different types of trait boredom, and, more generally, that trait boredom is best conceptualized as a multidimensional construct. Implications of these findings, including our understanding of trait boredom and directions for future research, are discussed.
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 | 0.000 | 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