Climate Change Impacts, Vulnerability, and Adaptation Options among the Lozi Speaking People in the Barotsefloodplain of Zambia
Bibliographic record
Abstract
The aims of this study were: -to find out how communities in the Barotse floodplain of Mongu district in Zambia are affected by climate change, establish adaptation opportunities practiced by the Lozi people and to raise awareness and stimulate interest in matters of climate change.Using primary and secondary data sources, it was observed that the negative impacts of climate change among the Lozi people include; increase in atmospheric pressure and excessive heat and flooding, prolonged spells of unexpected changes in seasons, reduction in food production and security, as well as inadequate clean water supply and extinction of some plant and animal species.The study also revealed vast local ecological knowledge that, if utilised, may help in the adaptation of climate change.The study further showed that climate change awareness and education are key in mitigating and adapting to climate change effects, though it was not found in the area.The study strongly recommend regular climate change awareness activities in order to promote mitigation and adaptation, need to pay greater and particular attention to the vast local ecological knowledge exhibited by the Lozi people that would help in adaptation to climate change in the area.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".