An International Comparison of Women's Health Issues in the Philippines, Thailand, Malaysia, Canada, Hong Kong, and Singapore: The CIDA-SEAGEP Study
Bibliographic record
Abstract
This was an international study of women's health issues, based on an Official Study Tour in Southeast Asia (the Philippines, Thailand, Malaysia, Hong Kong, and Singapore) and Canada. The objectives of the study were to identify and compare current gaps in surveillance, research, and programs and policies, and to predict trends of women's health issues in developing countries based on the experience of developed countries. Key informant interviews (senior government officials, university researchers, and local experts), self-administered questionnaires, courtesy calls, and literature searches were used to collect data. The participating countries identified women's health as an important issue, especially for reproductive health (developing countries) and senior's health (developed countries). Cancer, lack of physical activity, high blood pressure, diabetes, poverty, social support, caring role for family, and informing, educating, and empowering people about women's health issues were the main concerns. Based on this study, 17 recommendations were made on surveillance, research, and programs and policies. A number of forthcoming changes in women''s health patterns in developing countries were also predicted.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".