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Record W2801042152 · doi:10.1787/9789264244580-12-fr

Impacts sur l'économie et la santé des principales mesures possibles en matière d'alcool

2015· book-chapter· fr· W2801042152 on OpenAlexaboutno aff
Franco Sassi, Michele Cecchini, Marion Devaux, Roberto Astolfi

Bibliographic record

VenueOECD eBooks · 2015
Typebook-chapter
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Les politiques en matière d’alcool offrent d’immenses possibilités pour limiter les méfaits de l’alcool, améliorer la santé, renforcer la productivité, faire reculer les délits et les actes de violence et diminuer les dépenses publiques. La Stratégie mondiale de l’OMS visant à réduire l’usage nocif de l’alcool propose une liste de mesures envisageables fondées sur le consensus international, que l’OCDE a utilisée comme point de départ pour recenser un ensemble d’actions et les évaluer dans le cadre d’une analyse économique s’appuyant sur un modèle de simulation par ordinateur. Les actions évaluées dans trois pays – le Canada, la République tchèque et l’Allemagne – incluent des politiques de prix, des mesures de réglementation et d’application de la législation, des programmes d’éducation et des interventions sanitaires. Les résultats de l’analyse de l’OCDE montrent que l’on peut considérablement améliorer la santé par de brèves interventions dans le domaine des soins primaires, qui ciblent généralement les consommateurs d’alcool à haut risque, mais aussi par des hausses de taxes, qui concernent tous les consommateurs d’alcool.

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)0.013
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.941
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.006

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 head0.174
GPT teacher head0.490
Teacher spread0.316 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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