Analyzing Status of Female workforce in the Railway Industry: A Case Study
Bibliographic record
Abstract
Analysis of the working situation for women in the railway industry needs in-depth study of the viewpoints expressed by both men and women which is understudied in the literature especially in developing countries. Employment of women in the railway industry of Iran has nearly doubled since 2006 and it provided an interesting case study for this aim. The authors developed a questionnaire to explore various aspects of employment including general features like salary and prestige as well as evaluating different perspectives for women employment. Data was derived from 289 filled out questionnaires which were distributed in a public and a private railway company. We conducted independent sample T-tests to see whether there is statistically significant difference in the judgements of men and women for each item as well as the impact of place of employment, age, marital status and studying railway engineering. The obtained results could help the policymakers to improve further the working situation of women in this industry which is claimed to be heavily masculine.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".