Assessment of regional networks on nutrition in South Asia: a multi-methods study
Bibliographic record
Abstract
BACKGROUND: Many national and international organizations are working to improve maternal and child nutrition in countries with high malnutrition prevalence and burdens. While there has been progress in strengthening multi-organizational networks on nutrition at country and global levels, the regional level has received much less attention. We conducted a study to 1) determine the existing relationships and levels of engagement between international organizations working to improve nutrition at the regional level or in at least two countries in South Asia; and 2) examine the experiences and perspectives of international organizations on regional-level communication, coordination or collaboration on nutrition in South Asia. METHODS: A mixed methods approach involving organizational network analysis (ONA) and semi-structured interviews was used to develop an understanding of the existing network and relationships between international organizations working on nutrition in South Asia. ONA data from 43 international organizations was analysed using a social network analysis software (UCINET) to systematically quantify and visualize the patterns of relationships between organizations. RESULTS: We found a high degree of connectivity between most of the international organizations in South Asia, but there were gaps between the many organizations that knew each other and the work they did together regionally on nutrition. Most organizations worked together only 'rarely' or 'sometimes' on nutrition at the regional level and high-intensity (collaborative) working relationships were uncommon. Organizations of the same type tended to cluster together, and a small number of UN agencies and multilateral organizations were central brokers in the nutrition working relationships. Perceived constraints to the nutrition working relationships included organizations' agenda and mandate, threats to visibility and branding, human and financial resources, history, trust and power relations with other organizations, absence of a regional network for cooperation, and donor expectations. There was high demand to remedy this situation and to put network mechanisms in place to strengthen communication, coordination and collaboration on nutrition. CONCLUSIONS: Opportunities are being missed for organizations to work together on nutrition at the regional level in South Asia. The effectiveness of regional nutrition networks in influencing policy or programme decisions and resources for nutrition at country level should be explored.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".