Bibliographic record
Abstract
Alcoholic beverages, and their harmful use, have been familiar fixtures in human societies since the beginning of recorded history. Worldwide, alcohol is a leading cause of ill health and premature mortality. It accounts for 1 in 17 deaths, and for a significant proportion of disabilities, especially in men. In OECD countries, alcohol consumption is about twice the world average. Its social costs are estimated in excess of 1% of GDP in high- and middle-income countries. When it is not the result of addiction, alcohol use is an individual choice, driven by social norms, with strong cultural connotations. This is reflected in unique patterns of social disparity in drinking, showing the well-to-do in some cases more prone to hazardous use of alcohol, and a polarisation of problem-drinking at the two ends of the social spectrum. Certain patterns of drinking have social impacts, which provide a strong economic rationale for governments to influence the use of alcohol through policies aimed at curbing harms, including those occurring to people other than drinkers. Some policy approaches are more effective and efficient than others, depending on their ability to trigger changes in social norms, and on how well they can target the groups that are most at risk. This book provides a detailed examination of trends and social disparities in alcohol consumption. It offers a wide-ranging assessment of the health, social and economic impacts of key policy options for tackling alcohol-related harms in three OECD countries (Canada, the Czech Republic and Germany), extracting relevant policy messages for a broader set of countries. Â
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".