Adapting to the Impacts of Drought by Smallholder Farmers in Sekhukhune District in Limpopo Province, South Africa
Bibliographic record
Abstract
Smallholder farmers have been affected by drought impacts for several years. Sekhukhune district is characterized by poor and unreliable rainfall, frequent droughts and periodic flooding most of the time. Due to low and unreliable rainfall the smallholder farmers in the Sekhukhune district are finding it difficult to obtain high crop yields. As result of unreliable rainfall the majority of the households in the district are food insecure. The drought impacts in the Sekhukhune district has affected smallholder farmers in different ways including economically, socially and the production. Sekhukhune district has been receiving lower rainfall due to the effects of high extreme climatic events, climate variability and change. The impact of lower rainfall has negative effects on the agricultural sector, resulting in decrease in agricultural activities, loss of livestock, shortage of drinking water, low yields and shortage of seeds for subsequent cultivation in the district. The lowest average annual rainfall recorded was 438 mm in 1992. Limpopo Province including the Sekhukhune district has been characterised by low rainfall and recurrent drought problems especially in 1981/1984, 1988/1989, 1991/92 and in the 2004 and these hinder agricultural production in the province. The majority of farmers in the Sekhukhune district in 1992 lost high volumes of crops and livestock due to shortages of water and because of drought problems during that year. It was highlighted by several experts that the drought impacts in the Sekhukhune district are not only affecting the crop and the livestock smallholders, it is also affecting the vegetation status in the district. The quality and status of vegetation can be severely impacted by drought periods. The combination of these factors, for example low rainfall, poor vegetation condition and a range of other constraints, heightened during droughts, unfortunately produces a range of additional stressors for farmers in the Sekhukhune district. Poor vegetation usually means poor grazing and therefore poor cattle condition. This can further translate into loss of livelihoods as poor cattle often receive poor market prices.
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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 | 0.000 | 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".