Cost of privatisation versus government alcohol retailing systems: Canadian example
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Alcohol retail monopolies have been established in many countries to restrict alcohol availability and thus, minimise alcohol-related harm.The aim of this study was to estimate the impact of the privatisation of alcohol sales on the burden and direct health-care, law enforcement costs and indirect costs (lost productivity due to disability or premature mortality) in Canada. DESIGN AND METHODS: Simulation modelling. International Guidelines for the Estimation of the Avoidable Costs of Substance Abuse were used. All burden and costs were compared with the baseline taken from the aggregate Cost Study on Substance Abuse in Canada 2002. RESULTS: If all Canadian provinces and territories were to privatise alcohol sales we assume that consumption would increase from 10% to 20% based on available Canadian literature. Under the 10% scenario the costs would increase from 6% ($828 million) and under the 20% scenario costs would increase 12% ($1.6 billion).This increase is substantially greater than the tax and mark-up revenue gained from increased sales,and represents a net loss. DISCUSSION AND CONCLUSIONS: Alcohol-attributable burden and associated costs will increase markedly if all Canadian provinces and territories gave up the government alcohol retailing systems.For public health and economic reasons, governments should continue to have a strong role in alcohol retailing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".