Bibliographic record
Abstract
Aims: To study the effect of changes in income as well as prices of beer and arrack, on alcohol sales in Sri Lanka during the period 1981–2017. Design: The analyses were conducted by means of ARIMA time series analysis for arrack and beer separately. Measures: Yearly data on the sales of beer and arrack in the entire country were used. National GDP figures were used as a proxy measure of income, and yearly price data for arrack and beer were from Colombo, the largest metropolitan area in the country. Results: No short-term effects of changes in price or income were found on sales. However, changes in the price of beer were significant, with a lag structure, which implies a delayed effect of price changes on the sales of beer. A significant cross-price effect of changes in the price of beer on arrack sales was found as well. Conclusions: Sales of alcohol in Sri Lanka are not affected by price changes to the same extent as in high income countries. Most likely, the explanations will be found in the different drinking cultures between Sri Lanka and these countries.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".