An Investigation into Cyberloafing and Its Associations with Work and Non-Work Factors
Bibliographic record
Abstract
Cyberloafing, engaging in non-work-related online activities during work hours, has attracted increasing attention due to its potential to disrupt productivity and organizational functioning. Drawing upon contemporary research, we delve into the underlying mechanisms of cyberloafing. This study examines how cyberloafing behavior is related to work-related factors, including the position in the organization, boredom at work, pay satisfaction, and the non-work factors, such as loneliness and social network addiction. Furthermore, we investigate the role of two demographic variables: marital status and gender. We collected data from 174 white-collar employees working in various private-sector institutions in Sakarya (Türkiye). The findings showed that only two work-related variables, boredom at work and salary satisfaction, are significantly associated with cyberloafing. Gender and marital status were weakly related to cyberloafing. The paper also discusses possible solutions and practical implications for organizations seeking to mitigate the adverse effects of cyberloafing. The paper concluded with suggestions for future research and acknowledged the limitations of this study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".