Alcohol and health in Central and Eastern European Union countries – status quo and alcohol policy options
Bibliographic record
Abstract
The aim of this narrative review is to give an overview of alcohol consumption, attributable health harm, and potential alcohol control policies to reduce this harm in five Central and Eastern European Union countries: Czech Republic, Estonia, Latvia, Lithuania, and Poland. The overall level of alcohol consumption was high, with the two highest-consuming countries in the world being situated in Central and Eastern Europe (Czech Republic, Latvia), and all five of these countries being in the top 15% of World Health Organization member states with respect to consumption. Accordingly, alcohol-attributable health harm was high. Implementation of alcohol control policies could be improved, especially the implementation of pricing policies such as taxation increases. A moderate increase of the tax share on alcohol could result in thousands of lives being saved in Central and Eastern Europe in a single year. As taxation increases not only save lives, but also increase state revenue, the implementation of this alcohol control measure should be made a priority.
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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 | 0.001 | 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 | 0.000 |
| 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".