Workaholism among Australian psychologists: gender differences
Bibliographic record
Abstract
Purpose − This study aims to examine gender differences in three workaholism and workaholism‐related variables. Design/methodology/approach − Uses measures developed by Spence and Robbins and examines gender differences in three workaholism components, workaholic job behaviors and work and well‐being outcomes among Australian psychologists. Findings − Females and males were found to differ on many personal and situational demographic characters, two of three workaholism components (work involvement, and feeling driven to work) males scoring higher. Females, however, reported higher levels of particular workaholic job behaviors (e.g. perfectionism, job stress) likely to be associated with lower levels of satisfaction and well‐being. Females and males scored similarly on work outcomes, family satisfaction, physical health and emotional health. Females indicated more psychosomatic symptoms and less community satisfaction but more friends satisfaction. Originality/value − Aids in the understanding of workaholism 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 | 0.002 |
| 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 | 0.000 |
| 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".