The public-private decision for alcohol retail systems: Examining the economic, health, and social impacts of alternative systems in Finland
Bibliographic record
Abstract
Background: Organising alcohol retail systems with more or less public ownership has implications for health and the economy. The aim of the present study was to estimate the economic, health, and social impacts of alcohol use in Finland in 2018 (baseline), and in two alternative scenarios in which current partial public ownership of alcohol retail sales is either increased or fully privatised. Methods: Baseline alcohol-attributable harms and costs were estimated across five categories of death, disability, and criminal justice. Two alternate alcohol retail systems were defined as privately owned stores selling: (1) only low strength alcoholic beverages (public ownership scenario, similar to Sweden); or (2) all beverages (private ownership scenario). Policy analyses were conducted to estimate changes in alcohol use per capita. Health and economic impacts were modelled using administrative data and epidemiological modelling. Results: In Finland in 2018, alcohol use was estimated to be responsible for €1.51 billion (95% Uncertainty Estimates: €1.43 billion, €1.58 billion) in social cost, 3,846 deaths, and 270,652 criminal justice events. In the public ownership scenario, it was estimated that alcohol use would decline by 15.8% (11.8%, 19.7%) and social cost by €384.3 million (€189.5 million, €559.2 million). Full privatisation was associated with an increase in alcohol use of 9.0% (6.2%, 11.8%) and an increase in social cost of €289.7 million (€140.8 million, €439.5 million). Conclusion: The outcome from applying a novel analytical approach suggests that more public ownership of the alcohol retail system may lead to significant decreases in alcohol-caused death, disability, crime, and social costs. Conversely, full privatisation of the ownership model would lead to increased harm and costs.
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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 | 0.001 | 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".