Scope and applicability of social–ecological resilience to antimicrobial resistance
Bibliographic record
Abstract
Social-ecological systems conceptualise how social human systems and ecological natural systems are intertwined. In this Personal View, we define the scope and applicability of social-ecological resilience to antimicrobial resistance. Resilience to antimicrobial resistance corresponds to the capacity to maintain the societal benefits of antimicrobial use and One Health systems' performance in the face of the evolutionary behaviour of microorganisms in response to antimicrobial use. Social-ecological resilience provides an appropriate framework to make sense of the disruptive impacts resulting from the emergence and spread of antimicrobial resistance; capture the diversity of strategies needed to tackle antimicrobial resistance and to live with it; understand the conditions that underpin the success or failure of interventions; and appreciate the need for adaptive and coevolutionary governance. Overall, resilience thinking is essential to improve understanding of how human societies dynamically can cope with, adapt, and transform to the growing global challenge of antimicrobial resistance.
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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) | 0.003 | 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".