Evaluation of the national alcohol control strategy (Green Paper on Alcohol Policy) of Estonia
Bibliographic record
Abstract
INTRODUCTION: Estonia is a Baltic country with high adult alcohol per capita (APC) consumption. Since 2013, its alcohol control policy has been guided by the Green Paper on Alcohol Policy (GP), which is the equivalent of a non-binding national alcohol action plan. This contribution attempts to evaluate the overall impact of the GP on APC. METHODS: For the overall evaluation, APC was quantitatively compared for three periods: pre-GP (2000-2012), the core period of the GP (2013-2019) and the COVID-19 phase (2020-2022), using Analysis of Variance. RESULTS: APC decreased on average by 0.25 L of pure alcohol per year in the 7 years defined as the core period of the GP, whereas it increased in the other periods between 2001 and 2022 (period 2001-2012: +0.47 L; 2020-2022: +0.27 L). These differences were statistically significant (F [1, 18] = 5.22, p = 0.035). Moreover, there was no overall trend of decreasing APC during the core period of the GP in neighbouring countries (Latvia, Lithuania and Poland). DISCUSSION AND CONCLUSIONS: The combination of the various measures of the national alcohol policy was associated with a marked decrease in APC.
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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".