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Record W3035761124 · doi:10.12927/hcpol.2020.26224

Ten Years of Inaction on Antimicrobial Resistance: An Environmental Scan of Policies in Canada from 2008 to 2018

2020· article· en· W3035761124 on OpenAlexafffundvenueabout
Susan Van Katwyk, Jeremy Grimshaw, Steven J. Hoffman

Bibliographic record

VenueHealthcare policy · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsOttawa HospitalCentre for Global Health Research
FundersCanadian Institutes of Health Research
KeywordsResistance (ecology)Antibiotic resistanceAntimicrobialPolitical scienceEnvironmental planningBusinessEnvironmental resource managementGeographyEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

We surveyed Canadian healthcare experts to identify policies to address antimicrobial resistance (AMR) in Canada between 2008 and 2018. Respondents identified AMR policy interventions implemented in Canada during the previous 10 years. Additional policies were identified through systematic searches of seven electronic databases and a review of government documents. Fifty-two unique policies were identified, with at least one policy in most provinces and territories. This environmental scan suggests that Canadian AMR efforts are disjointed and inadequate, given the urgency of this public health threat. Governments have mostly refrained from using more powerful policy tools, including regulation, legislation and fiscal measures.

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.767

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.031
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2020
Admission routes4
Has abstractyes

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