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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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 teacher head, 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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