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Record W2132792397 · doi:10.1111/jlme.12275

Addressing Antibiotic Resistance Requires Robust International Accountability Mechanisms

2015· article· en· W2132792397 on OpenAlexaff
Steven J. Hoffman, Trygve Ottersen

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsMinistry of Health and Long Term Care
FundersWorld Health Organization
KeywordsAccountabilityLaw and economicsValue (mathematics)Action (physics)Resistance (ecology)International lawPolitical scienceBusinessPublic relationsRisk analysis (engineering)Computer scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Most proposals for new international agreements aim to address important global challenges. If the goal is to solve problems, then the value of these agreements depends on their ability to influence the world — to shape norms, constrain behavior, facilitate cooperation, and mobilize action. A recent review of empirical studies has suggested that many international agreements fail to achieve their aspirations. The review indicates that the form in which states make commitments to each other — through an international legal agreement or through other means — may not be as important as commonly thought. It is the content of the commitments and how these are supported by mechanisms to encourage implementation that matter the most. When developing proposals for new international agreements, like the one that has recently been proposed to address antibiotic resistance (ABR), attention to implementation mechanisms should therefore be equal to if not greater than the attention paid to its form.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.190
GPT teacher head0.397
Teacher spread0.207 · 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 designBench or experimental
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

Citations26
Published2015
Admission routes1
Has abstractyes

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