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Record W4383746539 · doi:10.1016/s2542-5196(23)00128-6

Scope and applicability of social–ecological resilience to antimicrobial resistance

2023· review· en· W4383746539 on OpenAlexaff
Didier Wernli, Peter Søgaard Jørgensen, E. Jane Parmley, Shannon E. Majowicz, Irene Lambraki, Carolee A. Carson, Melanie Cousins, Tíscar Graells, Patrik J. G. Henriksson, Anaïs Léger, Stéphan Harbarth, Max Troell

Bibliographic record

VenueThe Lancet Planetary Health · 2023
Typereview
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsPublic Health Agency of CanadaUniversity of WaterlooUniversity of Guelph
FundersJoint Programming Initiative on Antimicrobial ResistanceSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsScope (computer science)Resilience (materials science)Resistance (ecology)Psychological resilienceEnvironmental resource managementEcological systems theoryEcologyEcological resilienceAntibiotic resistanceCorporate governanceSocio-ecological systemBusinessBiologyPsychologyEconomicsEngineeringComputer scienceSocial psychologyEcosystem

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.110
GPT teacher head0.409
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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