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Record W4283575779 · doi:10.3390/ijerph19137744

The Alcohol Industry and Social Responsibility: Links to FASD

2022· article· en· W4283575779 on OpenAlexaff
Peter Choate, Dorothy Badry, Kerryn Bagley

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of CalgaryMount Royal University
Fundersnot available
KeywordsAlcohol industryHarmFetal Alcohol Spectrum DisorderAlcohol consumptionEnvironmental healthPublic healthBusinessSocial responsibilityDistribution (mathematics)Public relationsAlcoholConsumption (sociology)PregnancyMarketingPsychologyMedicinePolitical scienceSocial psychologySociologyAdvertisingNursingSocial science

Abstract

fetched live from OpenAlex

Fetal Alcohol Spectrum Disorder is directly linked to the consumption of alcohol during pregnancy. Prevention programs have been targeted at women of childbearing age and vulnerable populations. The beverage alcohol industry (manufacture, marketing, distribution, and retail) is often seen as playing a role in prevention strategies such as health warning labels. In this paper we explore the nature of the relationship between the industry and prevention programming. We consider the place of alcohol in society; the prevalence, social and economic costs of FASD; the ethical notion of alcohol-related harm and then move onto the question of public health partnerships with the industry including the potential conflicts of interests and ethical challenges in such partnerships.

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)0.002
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.084
GPT teacher head0.411
Teacher spread0.327 · 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
GenreOther

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

Citations3
Published2022
Admission routes1
Has abstractyes

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