Interoception and Boredom Proneness: A Novel Finding and a Call for Research
Bibliographic record
Abstract
Boredom proneness has been previously shown to be associated with higher levels of alexithymia, the inability to accurately label and represent one’s affective states. One prominent model of affective regulation suggests that we make use of interoceptive signals to predict the affective outcomes of intended actions. Given recent neuroimaging work implicating the anterior insular cortex in boredom, a region known to be critical for interoceptive processing, we explored the relations between alexithymia, interoception, and boredom proneness. Results showed strong relations with boredom proneness and attention to interoceptive signals. There were hints that the highly boredom prone also struggle to make sense of those interoceptive signals, however these were not prominent predictors of boredom proneness in regressions. We discuss the results and potential future experiments to explore the relation between boredom proneness and interoceptive processing.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".