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Record W2778660763 · doi:10.1177/145507251002700507

A Complex Picture

2010· article· en· W2778660763 on OpenAlexaffabout
Norman Giesbrecht, Gerald Thomas

Bibliographic record

VenueNordic Studies on Alcohol and Drugs · 2010
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsStatus quoEnvironmental healthPublic healthConsumption (sociology)Alcohol consumptionAlcoholBusinessPolitical scienceMedicineSociology

Abstract

fetched live from OpenAlex

This paper examines access to alcohol, trends in consumption, drinking patterns, damage from alcohol, and developments in prevention and alcohol policy – focusing on the Canadian experience over the last two decades. Consumption, as measured by official sales, declined initially and then has increased since 1996. During this time there was a gradual increase in access to alcohol, with steeper increase in some jurisdictions undergoing partial or full privatization of retail alcohol sales. According to survey data, the proportion drinking in a high risk manner is greater among youth and young adults, and the trend in the proportion of high risk drinkers does not necessarily follow the trend in alcohol sales. In light of intensive and multi-dimensional efforts to curtail drinking and driving, these rates have gone down during the period under study. Several provinces have introduced alcohol strategies and a national strategy introduced in 2007 is being implemented. Nevertheless there are ongoing challenges of getting alcohol on the broader public health agenda, even though it is major contributor to disease and disability. The rising consumption and increased access to alcohol, combined with intensive marketing, represent a major public health challenge. It is unlikely that there will be significant strides in reducing the damage from alcohol to Canadian populations, unless there is a substantial change in the status quo involving implementation of the most effective policies and prevention strategies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.056
GPT teacher head0.344
Teacher spread0.289 · 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 designObservational
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

Citations7
Published2010
Admission routes2
Has abstractyes

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