Improving Women Farmers' Welfare through a Goat Credit Project and Its Implications for Promoting Food Security and Rural Livelihoods
Bibliographic record
Abstract
In rural areas of Ethiopia, women do most of the household and farm work such as keeping livestock, growing crops, and preparing or cooking food for family members. They are, however, economically less empowered and often do not have access to resources. To address this problem, the Research and Extension Office of Haramaya University, Ethiopia, distributed locally adapted goats to poor and vulnerable women farmers. The project sought to link economic rehabilitation through a credit-in-kind approach with a clear focus on gender and the empowerment of women farmers. The objective of the current study was to determine the effect of the goat credit project on women farmers’ welfare. It was observed that 88% of the women farmers who sold goats earned mean annual cash income of 2644 Ethiopian Birr. As a result, they acquired assets and diversified their livelihoods by purchasing and raising poultry, cows, oxen, and donkeys. The women farmers became more economically empowered, which enabled them to gain greater control over their resources, which in turn increased their capacity to participate in social activities and household decision making. The goat credit project brought about substantial changes by enhancing food security and diversifying the livelihoods of women farmers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".