What is needed for health promotion in Africa: band-aid, live aid or real change?
Bibliographic record
Abstract
Health Promotion in sub-Saharan Africa (SSA) is currently facing many difficult challenges. Health status is worse than in any other region, with the midpoint data indicating that that SSA is not on track to achieve any of the Millenium Development Goals. This paper explores the history of health promotion in Africa, from before Alma Ata, through the 1970s, 1980s and 1990s, and up to the present. Using examples from Mozambique, Zimbabwe and South Africa during their transitional periods, and health promotion approaches adopted to tackle HIV/AIDS, diarrhoea and non-communicable diseases, the paper shows how the focus has shifted away from the ideals of the Ottawa Charter to an individualistic behaviour change approach. The reasons for the shift reflect political choices of governments that have favoured technocratic approaches over harnessing the popular mobilisations that have accompanied national struggles. The experiences of global movements, such as the Global Equity Gauge Alliance are considered as a way of enhancing local health promotion initiatives which, as presently conceived, are limited in their ability to address equity and the broader determinants of ill 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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".