Do alcohol price control measures adequately consider the health of very remote Australians?: Minimum Unit Price in the Northern Territory
Bibliographic record
Abstract
Alcohol is one of the leading preventable causes of death and disability worldwide1 and its harmful use is especially problematic within the Northern Territory, Australia. Alcohol-related harms may be categorised as either lifetime harms, which can include chronic liver disease, diabetes, heart attack and cancer; or single occasion harms, which can include assault, suicide and self-inflicted injuries, and road traffic injuries.2 Both lifetime and single occasion harms are disproportionately noted among those living in very remote locations; according to the Australian Statistical Geography Standard (ASGS) Remoteness Structure, Darwin is outer regional, Katherine and Alice Springs are remote, and the rest of the Northern Territory is very remote. Of those living in both outer regional and very remote Northern Territory locations, 29% drink at levels that place them at risk of lifetime harm, and 43% of individuals living in very remote Northern Territory drink at levels that place them at significant risk of harm on a single occasion at least monthly.3 As a comparison, in the major cities of Victoria, Australian Capital Territory, South Australia and New South Wales, only 14–15% of people drink at levels that put them at risk of lifetime harm, and 22.5–24% drink at levels that place them at risk of harm on a single occasion.3 Recent estimates indicate that harm caused by alcohol-related incidents costs the Northern Territory approximately $1.38 billion a year.4 One of the most effective policy responses is price control, with strong evidence to suggest consumption decreases as price increases.5 There are two major forms of alcohol excise taxes: ad valorem, which is a percentage of the price prior to sale tax; and specific tax, which is a predefined sum per unit of alcohol (also called volumetric tax).6 Minimum Unit Price (MUP) is another economic measure, which involves setting a minimum price at which alcohol can be sold. Evidence from Canada and the UK suggests that an MUP is likely to reduce consumption and related morbidity and mortality7 as a complementary strategy to taxation.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".