Gender differences in job experiences and satisfaction in the forest sector
Bibliographic record
Abstract
The forest sector faces complex societal demands that require a workforce with the desired composition of competence. It is also a primary, rural, and male-dominated industry based on gendered norms and culture. There are knowledge gaps in how gender influences work-related satisfaction and experiences in the forest sector and how women manage to work in male-dominated workplaces. We fill part of these voids by studying job satisfaction and women's strategies using the Norwegian forest sector as a case study. By combining surveys and group interviews, we unveil statistical gender differences and individual experiences. We found that while most men and women are satisfied with the social aspects of the workplace, men are more satisfied than women. Women report considerably less gender equality and more use of suppression techniques than men. Thirty-two percent of the women report being sexually harassed during their most important job position. Being exposed to harassment, most women choose not to report it to management, but instead handle the situation themselves. Forestry is a gendered sector, and to change attitudes for improving the work environment and opportunities for all employees, gender-related issues must be raised and handled in a suitable manner by managers and organizations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".