Workaholism among Norwegian journalists: gender differences
Bibliographic record
Abstract
Purpose Although workaholism in organizations has received considerable popular attention, our understanding of it based on research evidence is limited. This results from the absence of both suitable definitions and measures of the concept. The purpose of this paper is to examine gender differences in three workaholism components, workaholic job behaviors and work and well‐being outcomes among Norwegian journalists. Design/methodology/approach Data are collected from 211 journalists (138 males and 68 females) using anonymously completed questionnaires, with a 43 percent response rate. Findings Females and males are found to differ on some personal and situational demographic characteristics, and on one of three workaholism components (feeling driven to work, females scoring higher). Females however report higher levels of particular outcomes (e.g. negative affect, exhaustion) and less professional efficacy, likely to be associated with lower levels of satisfaction and well‐being. Females and males score similarly on the experience of flow at work and absenteeism. Research limitations All data are collected using self report questionnaires. It is not clear the extent to which these findings would generalize to men and women in other occupations. Originality/value This study adds to the small but growing literature on flow and optimal experience in organizations.
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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 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".