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Record W3092256935 · doi:10.1017/err.2020.84

Reducing the Harmful Use of Alcohol: Have International Targets Been Met?

2020· article· en· W3092256935 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Risk Regulation · 2020
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsMental Health Research CanadaUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAlcohol consumptionNon-communicable diseaseSustainable developmentBurden of diseaseAction planAction (physics)TreatyConsumption (sociology)BusinessEnvironmental healthPolitical sciencePublic economicsInternational ActionDevelopment economicsEconomic growthAlcoholDiseaseEconomicsMedicineLawBiology

Abstract

fetched live from OpenAlex

Alcohol use has been identified in major United Nations (UN) initiatives, such as the Sustainable Development Goals and the Non-Communicable Disease Action Plan, as a major contributor to the global burden of disease. As a result, levels of alcohol use serve as an official indicator of progress towards these UN-set goals. Given current trends, UN targets for reduced alcohol consumption are unlikely to be met. Moreover, in many countries, especially in low- and middle-income countries, the alcohol-attributable burden of disease continues to increase. Pressure will need to be exerted on national and international decision-makers to arrive at more powerful and normatively persuasive instruments, such as a treaty.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.142
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.066
GPT teacher head0.283
Teacher spread0.217 · 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