Caprine milk as a source of income for women instead of a taboo: a comparative analysis of the implication of women in the caprine and bovine value chains in Fatick, Senegal
Bibliographic record
Abstract
Abstract Domestic animals, especially small ruminants, are an important source of income for millions of smallholder farmers, particularly women, in Senegal. The aim of this study was to understand the place of the bovine and caprine milk value chains and to identify the role and challenges for women in the Fatick livestock production sector. A survey was conducted among a sample of 50 female producers, including 30 and 20 from the bovine and caprine milk value chains, respectively. Descriptive statistics were performed to compare the caprine and bovine milk value chains in terms of activities, products, and implications for household incomes while showing the place of women at different links of these value chains. The result of the study showed that the bovine milk value chain provided higher income compared to the caprine’s, but the latter was found to be more diverse in terms of milk-derived products with increased income opportunities’ potential. Remoteness, lack of equipment, and cultural biases were reported to be the main constraints in the caprine value chain, while milk price fluctuations were reported to be the biggest challenge for producers in the bovine milk value chain. Access to land and government subsidy programs and domestic time management were the main and specific challenges affecting women in the bovine and caprine value chains. Therefore, there is a need for the establishment of policies and interventions that consider the needs, opportunities, and complementarity offered by both the caprine and bovine milk value chains across smallholder women settings, while putting gender mainstreaming at the center of the discussions and reforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".