Bibliographic record
Abstract
Objectives: Health literacy has become an important issue in the filed of public health. The World Health Organization (WHO) recently established a strong global mandate for public policy action on health literacy by positioning it as one of three key pillars for achieving sustainable development and health equity in the Shanghai Declaration on Health Promotion. A number of countries implemented national health literacy policies, with many others expected to develop them in the immediate future. However, national policies and strategies for health literacy in Korea is still limited and underdeveloped. The aim of this study was to suggest policy directions to improve health literacy in Korean through reviewing international health literacy polices and strategies at the national level. Methods: In terms of the literature in U.S, Canada, Australia, and European countries, government policy reports and research papers were reviewed. For systematic comparison, the criteria for analyzing and extracting data from policy documents suggested by previous study was employed. Results: Based on the literature review, document review on international efforts to improve health literacy, and survey results, we suggest the following policy recommendations: (1) developing an official term of health literacy in the Korean language to help stakeholders and the public better understand the comprehensive, multi-dimensional concept, (2) monitoring of the health literacy level among Koreans, and (3) coordinating with government, healthcare sector, academia, etc. to develop intersectoral strategies aiming at improving health literacy as well as achieving health equity. Conclusions: For the development of effective health literacy policies and strategies at the national level, health literacy needs to be understood as a key determinant of health, and inter-sectoral efforts should be considered to improve health literacy.
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 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".