Nature, Predictors, and Outcomes of Workers’ Longitudinal Workaholism Profiles
Bibliographic record
Abstract
This research relies on a combination of variable- and person-centered approaches to help improve our understanding of the dimensionality of the workaholism construct. Our results showed that employees’ workaholism ratings simultaneously reflected a global overarching construct co-existing with four specific dimensions (behavioral, motivational, emotional, and cognitive workaholism) among a sample of 432 workers who completed a questionnaire twice over a three-month period. We also examined the profiles taken by workaholism dimensions, and documented their stability over time as well as the associations between these profiles and theoretically-relevant predictors and outcomes. Furthermore, we examined whether these associations differ as a function of working remotely or onsite. Four profiles were identified and found to be highly stable over time: Unplugged , Plugged In , Moderately Unplugged with Externalized Workaholism , and Moderately Unplugged with Cognitive Workaholism . Personal life orientation, telepressure, and interpersonal norms regarding work-related messages were related to the likelihood of profile membership. Remote working also reinforced the positive effects of personal life orientation and the negative effects of interpersonal norms regarding work-related messages. Finally, employees’ work-to-family guilt, job satisfaction, family satisfaction, and life satisfaction also differed as a function of their profile.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".