Constraints and Challenges Facing the Small Scale Farmers in Limpopo Province, South Africa
Bibliographic record
Abstract
Macro- and micro-structural constraints, including those linked to and exacerbated by historical, natural and financial factors are some of the many stressors facing small-scale farmers in Limpopo Province. The challenge is to co-design ways to effectively manage these constraints with development actions. Small scale farmers in South Africa are still facing major challenges in the agricultural sector. In this paper some of the challenges faced by small-scale farmers in the Limpopo Province have been identified. Some of the challenges found during the formal surveys and focus group meetings in the Tshakhuma, Rabali and Tshiombo areas were those linked to financial, assets, land ownership and biophysical factors. Specific constraints included: (a) Market information and market access; (b) Price of inputs, for example fertilizer and herbicides; (c) Availability of inputs; (d) Irrigation; (e) Cost of transport, and Natural constraint.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".