The 7th WHO Global Conference on Health Promotion - Towards Integration of Oral Health, Nairobi, Kenya, 26-30 October 2009.
Bibliographic record
Abstract
Since the first World Health Organization (WHO) Global Conference on Health Promotion (GCHP) that produced the Ottawa Charter for Health Promotion, subsequent GCHPs were held in different continents. It was Africa's turn to host the 7 th GCHP in Nairobi in October 2009, organised by WHO and Kenya Ministry of Health. The theme of the meeting was Promoting Health and Development: Closing the Implementation gap. It was the first time in the GCHP history that oral health received such a high profile and featured in one of the 12 special sub-plenary sessions. This report summarises the proceedings of the sub-plenary session on social determinants of oral health. Strategies for tackling social determinants of oral health and closing the implementation gap were considered, together with specific examples from developed and developing countries from different WHO regions. Oral health promotion implications were discussed based on public health experience and operational research. At the end of the session, input on oral health related issues was prepared for the Nairobi Call to Action adopted by the conference. In follow-up, the WHO Global Oral Health Programme contributes to the newly established WHO initiative Mainstreaming Health Promotion, which particularly seeks to build capacity in health promotion in low- and middle income countries. This work is carried out in support of the World Health Assembly Resolution (WHA60.17) on oral health.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.095 | 0.027 |
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".