Bibliographic record
Abstract
This study looks at the persistent issue of gender discrimination in the workplace in China, focusing on the barriers that women encounter because of societal and cultural norms that disadvantage them in both the public and private spheres. The study focuses on the effects of gender prejudice on women's mental health and professional advancement, specifically in the recruiting and promotion procedures. A comprehensive survey disseminated via well-known social media platforms and structured interviews with women who have encountered or observed gender prejudice were both components of the mixed-method technique used. Quantitative and qualitative data were collected through the questionnaire, which examined workplace culture, particular cases of discrimination, and the effects on mental health and job satisfaction. According to research, discriminatory behaviors that are made worse by cultural norms and traditional gender roles not only prevent women from advancing in their careers but also significantly worsen their mental health. The study suggests an integrative approach to solve these problems, which includes strengthening workplace regulations, raising awareness, and setting up support networks to promote gender equality. Such actions are necessary to establish a fair workplace that benefits employers and employees alike, which will ultimately boost organizational results.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".