Orientation, Othering and medicalisation: a queer phenomenology of AMR community identity formation
Bibliographic record
Abstract
Global mobilisation to address antimicrobial resistance (AMR) is catalysing emergence of an AMR community, while simultaneously producing this community’s Others in the form of new subjectivities that emerge as problems to be solved. This article theorises epistemic community identity formation through a foundational global AMR governance document, the Global Action Plan on AMR. Drawing on Sara Ahmed’s queer phenomenology, it argues that through problem/solution framings, shared expert functions and normative commitments, the GAP-AMR produces an epistemic community oriented around a narrowly medicalised base of expert scientific knowledge and categorisation schema, and towards newly emergent subjects defined largely by behavioural deficits and a lack of expertise and capacity. It highlights the erasures produced through these relational identity-formation processes, which in turn indicate the importance of re-orienting relations in the global AMR response.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.061 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".