Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate gender differences in burnout, style of coping and the availability of peer support among high‐tech engineers Design/methodology/approach A longitudinal study investigated gender differences in burnout, style of coping and the availability of peer support among high‐tech engineers, an interesting occupational group from a gender perspective both because of the masculine culture of the engineering profession and the many prejudices against women engineers. Both the masculine culture and the prejudices help explain the paucity of women engineers and predict high levels of burnout among them. Findings The paper's findings supported this prediction. They revealed a significant gender difference in burnout, with women engineers reporting higher levels of burnout than men. The gender differences in burnout were interpreted as related to other findings: women's greater tendency to utilize emotion‐focused coping, their smaller peer support and greater work–family conflict. Originality/value In addition to their implications for gender theory and research and for burnout theory and research, the paper's findings point to the need to encourage and support the small and unique group of women engineers.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".