Exploring the success and challenges of the <i>Girinka</i><sup>1</sup> programme and the need for social work involvement: Southern Province, Rwanda
Bibliographic record
Abstract
This article discusses an indigenous approach labelled „girinka programme‟ designed for reducing poverty and fighting against child malnutrition. The approach consists of providing a milk cow to poor households in order to ensure milk supply to children. The issued milk cows are not only for milk consumption but also for enabling beneficiaries to get out of poverty through selling surplus milk and using manure to increase land fertility for agricultural production. The objectives of this article is to understand how girinka programme works, highlighting its success in empowering poor households and examining the challenges and obstructions it faces, and eventually put emphasis on the role of social work in coping with them. In addition to the 21 individual interviews with practitioners in Huye district, 18 more interviews with girinka programme beneficiaries and potential beneficiaries were conducted in both Huye and Gisagara districts, and during June-July 2016 annual workshop on social work in Rwanda held in Huye, a group discussion with 7 advisory committee members was also conducted. Though this programme was designed to decrease poverty and fight against malnutrition, challenges and obstructions such as unaffordable preconditions, insufficient training in animal husbandry and cooperative management, misappropriation of milk cows, cases of bribery, and poor follow up were observed. The article recommends the use of not only veterinary and agricultural technicians but also social work practitioners in addressing these challenges and obstructions to the success of girinka programme. The role of social work practitioners along with local public staff in charge of social services would for instance be that of using „strengths perspective‟ to facilitate beneficiaries and potential beneficiaries of the programme on the waiting list to find alternative solutions to their problems and build up their self-sufficiency through empowerment approach.Keywords: Indigenous Empowerment, Girinka programme, Poor Household, Huye, Gisagara, Rwanda
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".