Gender Differences in Work Experiences and Work and Learning Outcomes among Employees in the Manufacturing Sector in Turkey: An Exploratory Study
Bibliographic record
Abstract
This study examined gender differences in work experiences and work outcomes among 215 male and 46 female employees working in the textile and furniture sectors in Turkey. Data were collected from 261 employees, a 65 percent response rate, using anonymously completed questionnaires. Respondents were mostly male, worked full-time, had relatively short job and firm tenures, generally held jobs involving some supervisory responsibilities, and worked 41 to 50 hours per week in fairly large firms. All measures used here had been used and validated previously by other researchers. Work experiences included perceptions of supervisor empowering behaviors; outcomes included job satisfaction, affective commitment, work engagement, engaging in voice behaviors, and intent to quit. Learning related outcomes included learning opportunities and self-rated employability. There were small differences in departments in which men and women worked with a slightly higher percentage of men in production and a slightly lower percentage of men in accounting, human resource management and marketing. Consistent with earlier work, significant gender differences were found on several personal demographic and work situation characteristics. Women were younger, less likely to be married, were more highly educated, were at lower organizational levels, had less job and organizational tenure. Males and females had similar perceptions of their supervisor’s empowering behaviors, their own levels of psychological empowerment, similar learning opportunities and levels of self-rated employability and on most work outcomes (e.g, job satisfaction, organizational commitment, intent to quit).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".