Navigating One Health in research-for-development: Reflections on the design and implementation of the CGIAR Initiative on One Health
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
Adopting One Health approaches is key for addressing interconnected health challenges. Yet, how to best put One Health into practice in research-for-development initiatives aiming to 'deliver impacts' remains unclear. Drawing on the CGIAR Initiative on One Health - a global initiative to address zoonotic diseases, antimicrobial resistance, and food and water safety - we reflect on challenges during program conception and implementation, prompting us to suggest improvements in multisectoral collaboration, coordination, and communication. Our approach involves conducting a researcher-centered process evaluation, comprising individual interviews that are subsequently thematically analyzed and synthesized. The key takeaway is that limited time for planning processes and short program timelines compared to envisioned development impacts may impede research-for-development efforts. Yet, collaborative work can be successful when adequate time and resources are allocated for planning with minimal disruption throughout implementation. Additionally, due to the multifaceted nature of One Health initiatives, it is important to pay attention to co-benefits and trade-offs, where taking action in one aspect may yield advantages and disadvantages in another, aiding to identify sustainable One Health development pathways. Forming close partnerships with national governments and local stakeholders is essential not only to promote sustainability but also to ensure local relevance, enhancing the potential for meaningful impact. Finally, regularly assessing progress toward development goals is critical as development stands as an overarching objective.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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