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Record W3165372535 · doi:10.1111/add.15569

Commentary on Meier <i>et al</i>.: Gender disparities in the effects of alcohol pricing policies on consumption and harm reduction

2021· letter· en· W3165372535 on OpenAlexaboutno aff
Heng Jiang, Anne‐Marie Laslett

Bibliographic record

VenueAddiction · 2021
Typeletter
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHarmHarm reductionConsumption (sociology)PopulationPoison controlInjury preventionDomestic violenceMedicineEnvironmental healthAffect (linguistics)PsychologyPsychiatryDemographyPublic healthSocial psychology

Abstract

fetched live from OpenAlex

Commentary on Meier et al.: Gender disparities in the effects of alcohol pricing policies on consumption and harm reductionWhile increasing alcohol tax and introducing a minimum unit price will probably have only a moderate impact on women's drinking, the harm that women experience from others' drinking could be substantially reduced.

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)0.014
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.067
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.098
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0060.007
Open science0.0110.004
Research integrity0.0670.070
Insufficient payload (model declined to judge)0.0210.015

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 head0.037
GPT teacher head0.299
Teacher spread0.263 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2021
Admission routes1
Has abstractyes

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