Gender Imbalance in Science: Analytical Overview and Best Global Practices
Bibliographic record
Abstract
The research aims to conduct an analytical overview of advanced international practices in identifying gender imbalances in scientific research activities to develop recommendations for Kazakhstan. In the article, the authors examine advanced foreign strategies and approaches, including the establishment of a goal-setting system, policies, and monitoring support programs (i.e., preferential hiring policies, professional development, and incentives for gender equality research). The study analyzes the strategic directions and advanced practices of foreign countries based on the use of the STEM and Gender Advancement indicator matrix, as well as conducting a bibliographic analysis using the VosViewer soſtware. The bibliographic analysis identified the following cluster networks: “Science and Research,” “Gender Inequality,” and “Employment and Gender Segregation.” The research work investigates advanced practices from Sweden, Denmark, Norway, Iceland, Germany, Canada, Australia, Kuwait, Egypt, and Algeria in addressing gender imbalances in the scientific environment. Among the identified practices are mentoring programs, quota allocations, improved research funding, and legislative changes. During the analysis, advanced practices were identified for potential adaptation to Kazakhstan’s conditions in the future.
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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 | 0.003 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".