Municipalities’ organisational capacity to support the implementation of the Multi-Sector Nutrition Plan in Burkina Faso
Bibliographic record
Abstract
The Government of Burkina Faso committed to the multi-sector approach on nutrition in 2014 and has conducted the development of a Multi-Sector Nutrition Plan 2020-2024. This study aims to understand and analyse the Nutrition organizational capacities at the municipal level to support the scaling up of interventions within the National Multi-Sector Nutrition Plan. A qualitative study was conducted at the end of 2017, based on the framework for nutrition capacity developed by the United Nations Network Secretariat in collaboration with five funding agencies, to assess the organizational capacity dimension. Data collection consisted of focus groups and information collection through workshops with key informants. In total, 22 rural municipalities were targeted and 152 key informants were involved, including mayors, municipal councillors, members of the village development committee, and local technical agents in charge of agriculture, livestock and health. The gaps identified were poor integration of nutrition into local development strategic plans, less evolved coordination on nutrition, weak development of nutrition community approaches and dependence on the state budget matched to a non-existent budget monitoring system. The findings showed an unequal distribution and limited number of technical agents to cover villages within a given municipality, inadequate skills to support services expansions such as water and sanitation, health, agriculture and livestock. In addition, no reference was made to monitoring and evaluation, accountability or sharing information. The main capacity needs on nutrition are the transfer of technical competencies from the regional to the municipal level, the strengthening of technical skills on nutrition, and the setting up of an integrated data collection system involving key players. The identification of needs and opportunities and the newly finalized guide on nutrition integration into local development plans and strategies are useful to drive change for multisectoral implementation.
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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 | 0.000 |
| 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".