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Record W2074734703 · doi:10.1080/09652140020013791

Roles of commercial interests in alcohol policies: recent developments in North America

2000· review· en· W2074734703 on OpenAlexaffabout
Norman Giesbrecht

Bibliographic record

VenueAddiction · 2000
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental Health
FundersCenter for Substance Abuse Prevention
KeywordsGovernment (linguistics)NewspaperAlcohol industryPsychological interventionBusinessHealth policyAlcohol advertisingOrder (exchange)Public economicsPublic relationsEconomic growthPoison controlSuicide preventionMarketingPolitical scienceEconomicsEnvironmental healthMedicineAdvertisingHealth careFinance

Abstract

fetched live from OpenAlex

This paper examines recent developments in Canada and the United States and the role of commercial interests in alcohol-related policies bearing on taxes, outlet density, advertising, counter-advertising, health messages and prevention. Case-study material is drawn from published papers, project reports, government documents and newspaper accounts. The main focus is at the federal level, with some reference to provincial, state and local experience. Alcohol industries have as their primary agenda that of maintaining and expanding their markets and maximizing profits. In order to achieve this they typically oppose restrictions on access to alcohol, tax increases, controls on marketing and some counter-advertising campaigns. They are powerful in influencing policy in both countries, at national and regional levels, and their efforts impact policy agenda and outcome of government deliberations. Their prevention efforts, which tend to be oriented to information and education, are mainly individualistic in focus and typically not supportive of environmentally based policy reforms. Governments appear to have a declining interest in policy issues, due partly to resistance by the industries to alcohol control policies. Governments are encouraged to apply an evidence-based orientation to funding prevention, and facilitate evaluation of industry-sponsored prevention efforts. Greatest attention and resources should be directed to interventions that are most likely to have the greatest impact in reducing drinking-related problems, and funding for prevention from alcohol industries should involve arms-length arrangements. Alcohol industries are encouraged to consider strategies that do not increase access to alcohol but rather reduce drinking-related risks.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.930
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.069
GPT teacher head0.360
Teacher spread0.292 · 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 designOther design
Domainnot available
GenreReview

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

Citations37
Published2000
Admission routes2
Has abstractyes

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