Critical posthuman ethnography: grappling with human-more-than-human interconnection for critical public health
Bibliographic record
Abstract
To address the intertwined health issues of our time, from climate change to colonialism, from mass extinction to mass consumption, this commentary argues that critical public health must grapple with relationality onto-epistemologically. In it, I offer the provocation that entangling ethnography, both as method and methodology, with critical posthumanism can offer the potential to hold the tensions, nuances and multiplicities needed to account for human-more-than-human relationality as multiple inputs of data. This argument is made in three parts: first, via a discussion of relationality within public health; second, by means of a cartography of critical posthumanism; and third, with a discussion of how a critical posthuman ethnography might disrupt anthropocentric approaches to health. The paper concludes with a discussion of the possibilities of, and potential for, critical posthuman ethnography in public health research. In summary, critical posthuman ethnography provides one way of methodologically approaching some of the intertwined health issues of our time.
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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 | 0.050 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.103 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".