Rich Environments, Dull Experiences: How Environment Can Exacerbate the Effect of Constraint on the Experience of Boredom
Bibliographic record
Abstract
We examined the hypothesis that boredom is likely to occur when opportunity costs are high; that is, when there is a high potential value of engaging in activities other than the researcher-assigned activity. To this end, participants were either placed in a room with many possible affordances (e.g., a laptop, puzzle, etc.; affordances condition; n = 121), or they were ushered into an empty room (control condition; n = 107). In both conditions participants were instructed to entertain themselves with only their thoughts (hence, participants in the affordances condition were to refrain from engaging with the available options). As predicted, participants in the affordances condition reported higher levels of boredom compared with those in the control condition. Results suggest, that under some conditions, environments that afford alternative activities may be more boring than those that are void of such activities.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".