"The Good, the Bad or Just Plain Bored? Boredom Predicting Citizenship and Counterproductive Behavior"
Bibliographic record
Abstract
Boredom is often treated as a “dark” construct with the potential to harm organizations. Recently, however, researchers have proposed a “light” side of boredom wherein it could benefit organizations. In the present paper, we juxtapose the “dark” and “light” sides of boredom by investigating the extent to which feeling bored at work causes individuals to perform counterproductive work behavior (CWB) and organizational citizenship behavior (OCB). To test these hypotheses, we surveyed 136 full-time employees using experience sampling methodology. Our results indicated that whereas bored individuals engage in CWB, they are unlikely to perform OCB. In addition, we found evidence suggesting that need for achievement and proactive personality moderate the relations between feeling bored and CWB and OCB, respectively. Our results support the idea that individual differences may shape bored employees’ behavior, such as by enabling them to perform prosocial acts in addition to harmful ones.
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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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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 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".