A Case for Liquor Taxes that Reduce Harm Overview
Bibliographic record
Abstract
• Alcohol consumption in Canada has increased by over 11 % in the past decade. • Per adult absolute alcohol consumption in British Columbia has increased from 8.18 litres in 2002 to 8.53 litres in 2005. • Since 2002 the numbers of hospitalizations and neuro-psychiatric deaths attributable to alcohol in BC have increased by 11.7 % and 18%, respectively. • In 2005 there were an estimated 25,194 alcohol-related injuries and illnesses in BC requiring hospitalization compared with 4,817 related to illicit drug use. • There is extensive scientific evidence to support the use of pricing and taxation strategies as effective means of reducing alcohol consumption and related harms. • In British Columbia such strategies are readily achievable because the government alcohol monopoly directly controls liquor prices. • 65 % of the coolers now sold in BC contain 7 % alcohol content and have an average price of $5.41 per litre, compared with $8.07 for coolers with a 5-5.9 % alcohol content. • We recommend that liquor prices more closely reflect alcohol content and that these are regularly updated with the cost of living. • Beers and coolers with low alcohol content should have significantly lower price ‘mark-ups ’ applied to give manufacturers, retailers and consumers incentives to produce, market and consume these products. • Minimum prices also need to be set and updated regularly to ensure there are no cheap high strength products available. • We also recommend that a “nickel a drink ” tax be introduced to generate $95.7 million per annum for treatment and prevention programs. • Detailed results are available at the BC Alcohol and Other Drug Monitoring website (www.AODmonitoring.ca)
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.019 | 0.020 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".