One Health for all: Implementing international frameworks with local communities
Bibliographic record
Abstract
The One Health concept emphasizes the interdependence of human, animal and environmental health. While the term “One Health” has only gained traction in this century, the idea itself is much older. For instance, many Indigenous Peoples and local communities have traditional cosmologies that recognize the interconnectedness of the ecosystem and the role of humans within it [1, 2]. It is the industrialized-focused worldview that has only recently come to terms with the fact that humans are part of a complex global ecology, not the masters of it. While some progress has been made in recognizing the importance of local, traditional and Indigenous knowledges in One Health policy documents, and towards including gender equality, disability and social inclusion (GEDSI) considerations, hurdles remain to meaningfully incorporate context-specific knowledge in practice (see S1 Fig for definitions of the different types of knowledges). In this article, we advocate for funding and engagement in deep context-specific social research before funding and engaging in One Health interventions. Through our own work on the Indo-Pacific Initiative for Sustainable Animal Health Cooperation, we seek to understand how factors such as gender and social inclusion can inform the uptake or rejection of One Health practices within local communities in the region. To keep communities safe and ensure equitable health outcomes, it is worth the time, money and effort to understand the dynamics that shape and motivate local interactions between humans, animals and the environment. This will undoubtedly help to develop more tailored, appropriate, trusted and sustainable One Health interventions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".