Achieving SDGs and addressing health emergencies in Africa: strengthening health promotion
Bibliographic record
Abstract
In 1986, the World Health Organization (WHO) convened the first Global Conference on Health Promotion held in Ottawa, Canada. This conference yielded the Ottawa Charter which defined health promotion as the process of enabling people to increase control over, and to improve, their health. A series of conferences followed and in 2005, WHO convened the Sixth Global Conference in Bangkok, Thailand, which yielded the Bangkok Charter for Health Promotion. This Charter for the first time expanded the role of health promotion to include addressing social determinants of health. Ministers of Health from 47 countries of the WHO Regional Office for Africa in 2012 endorsed the Health Promotion: Strategy for the African Region. This Strategy highlighted eight priority interventions required to address health risk factors and their determinants. In 2011, the Rio Political Declaration on Addressing Social Determinants of Health was adopted by Health Ministers and civil society groups to address inequalities and inequities within and between populations. The main action areas were good governance to tackle the root causes of health inequities; promoting participation and ownership; community leadership for action on social determinants; global action on social determinants to align priorities and stakeholders; and monitoring progress on implementation of policies and strategies. Health promotion has been prominent as part of disease outbreak response, including for Ebola and COVID-19. It has been an integral part of improving maternal and child health mortality and morbidity as well as TB, HIV/AIDS and malaria; and lately reducing the impact of noncommunicable diseases, namely diabetes, high blood pressure and cancer. While challenges continue in strengthening health promotion, there have been concerted efforts to place health promotion on the development agenda in countries through Health in All Policies (HiAP), capacity strengthening, monitoring and evaluation, and innovative financing policy options using dedicated tax from tobacco and alcohol, and road use.
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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 | 0.039 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".