Boredom Proneness and Rule-Breaking: A Persistent Relation One Year into the COVID-19 Pandemic
Bibliographic record
Abstract
Research conducted within the first year of the pandemic demonstrated that boredom prone individuals were more likely to break rules (e.g., social distancing) aimed at preventing the spread of COVID-19. It is of interest whether this relation persisted deeper into the pandemic, given that initial results may have reflected the extraordinary nature of the early stages of the pandemic on one hand, or more stable dispositions on the other. Therefore, in the Summer of 2021, we administered an online survey to investigate whether boredom proneness predicted COVID-19 rule-breaking over one year into the pandemic (and approximately one year after the earlier studies). We found that boredom prone individuals remained more likely to engage in COVID-19 rule-breaking. Our results suggest that a trait disposition towards boredom exerts a persistent, long-term influence on behaviour, one that is detrimental to personal well-being during the pandemic. Adherence to public health measures might be improved by encouraging individuals to find adaptive ways of coping with boredom.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".