Availability restrictions and alcohol consumption: A case of restricted hours of alcohol sales in Russian regions
Bibliographic record
Abstract
Kolosnitsyna, M., Sitdikov, M., & Khorkina, N. (2014). Availability restrictions and alcohol consumption: A case of restricted hours of alcohol sales in Russian regions. The International Journal Of Alcohol And Drug Research, 3(3), 193 – 201. doi:http://dx.doi.org/10.7895/ijadr.v3i3.154Aim: To determine how new restrictions on hours of alcohol retail sales influence alcohol consumption in Russia.Design: Natural experiment with combined regional and micro-data.Setting/Participants: Cross-sectional samples from the Russian Longitudinal Monitoring Survey, corresponding to waves 18 and 19, years 2009–2010, 32 Russian regions and more than 7,000 adults (aged 15 and up) consuming alcohol at least once per month.Measures: Descriptive analysis of per capita alcohol sales at the regional level and regression analysis of pure spirit consumption at the individual level, controlling for various socioeconomic factors, including sales bans.Findings: We revealed a significant positive correlation between the amount of alcohol consumed and the number of hours of allowed alcohol sales when other factors were controlled. The results gained from analyzing the micro-data were confirmed using the regional sales information. In terms of drinking reduction, sales restrictions in the evening hours seem more efficient than restrictions in the morning hours. Restricted hours of sale do not increase consumption of beer or home-distilled alcohol.Conclusions: Alcohol consumption depends on the hours of sale, all else being equal. Restricting the legal hours of alcohol sales in Russian regions has the potential to reduce consumption levels. These findings indicate a need for a further reduction in sales hours in the regions where heavy drinking is especially widespread.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".