Favorable and unfavorable health conditions within OECD countries: An exploratory study
Bibliographic record
Abstract
OBJECTIVES: This study compared the physical, mental, and social health levels among Organization for Economic Co-operation and Development countries. METHODS: We sampled from 34 Organization for Economic Co-operation and Development member countries and divided physical, mental, and social health into three domains based on World Health Organization health definitions. RESULTS: A multivariate hierarchical cluster analysis was conducted to group countries that were similar in terms of health. Regarding physical health, Japan, South Korea, Sweden, Switzerland, and ten more countries reported favorable health conditions. For mental health, Australia, Canada and eight more countries revealed favorable conditions. Finally, in terms of social health, Austria, Finland, Iceland, and seven more countries reported favorable conditions. Sweden and Switzerland reported the best health conditions aggregated across all three domains. Conversely, Estonia, Hungary, and Turkey reported comparatively poorer health across all three domains when compared with other Organization for Economic Co-operation and Development countries. CONCLUSIONS: We suggested that mental health policy should be further strengthened in cases of Korea and Japan. In case of the Eastern Bloc countries, health policies should be established focusing on health equity for effective improvement of indicators.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".