Insights and future directions: Applying the One Health approach in international agricultural research for development to address food systems challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For more than 15 years, the International Livestock Research Institute (ILRI) has been striving to understand and address One Health challenges at the intersection of livestock, humans, and the environment. We present an overview of ILRI One Health projects implemented with partners across Asia and Africa, reflecting on key learnings and future directions for One Health research and food systems transformation. Drawing on a review of peer-reviewed and grey literature, we analyzed processes and outcomes of ILRI-led and supported initiatives using a realist evaluation framework (context, mechanisms, outcomes), and present insights within select One Health topic areas such as zoonoses, food safety, antimicrobial resistance. Our findings emphasize the need for stronger cross-sectoral collaboration, greater engagement with policymakers to translate research findings into actionable strategies, and the development of adaptable and context-specific interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it