Does One Health need an ontological turn?
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
One Health has gained global prominence in recent years. Alongside its emergence, there have been extensive social science critiques. In this contribution, we make the case for the value of recent theoretical discussions in the field of anthropology - sometimes referred to as an 'ontological turn'. We argue that taking theory seriously benefits One Health as an integrated approach that has interdisciplinary collaborations at its heart, but which encounters challenges when conversations based on different epistemological and ontological positions result in voices talking past each other. In this contribution, we offer two examples of what One Health specialists can gain from anthropologically-informed ontological thinking. Both require questioning ontological premises. Firstly, questioning assumptions about distinctions between animals and humans. Secondly, questioning the universality of biomedical knowledge. In the conclusion, we underline the importance of an ontological openness when it comes to the constitution and position of the actors as well as different bodies of knowledge that are involved in One Health and we show that talking to each other with awareness of different ontological positions is not impossible.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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