Climate change impacts on indigenous health promotion: the case study of Dikgale community in Limpopo Province, South Africa
Bibliographic record
Abstract
The most important determinants of indigenous health promotion are availability and accessibility of water, food and traditional medicine. It is for this reason that the 1986 Ottawa Charter for Health Promotion proposed the inclusion of food, water and ecosystems in any health promotion strategies. The present study describes the extent to which climate change in the form of rainfall scarcity and increased temperatures impacts the availability and accessibility of quality water, food and traditional medicine as basic determinants of indigenous health promotion. In-depth interviews were conducted with 240 participants purposely selected from Dikgale community in Limpopo Province, South Africa. The study results show that availability and accessibility of water, food and traditional medicine are negatively impacted by increased temperature and scarcity of rainfall. These resources are scarcely encountered, and where they exist, they are of poor quality. However, community members resorted to modern technological practices such as sourcing water from the municipal water reticulation system, buying foodstuffs from retail outlets and immunization against disease via modern health care facilities. It can be deduced from the study that the prerequisites of indigenous health promotion are climate-sensitive. They become available and accessible under favourable climate conditions, and are scarce under unfavourable climate conditions, a situation that compromises the practice of indigenous health promotion.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".