Doing it by numbers: A simple approach to reducing the harms of alcohol
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alcohol use is one of the top five causes of disease and disability in almost all countries in Europe, and in the eastern part of Europe it is the number one cause. In the UK, alcohol is now the leading cause of death in men between the ages of 16-54 years, accounting for over 20% of the total. Europeans above 15 years of age in the EU on average consume alcohol at a level which is twice as high as the world average. Alcohol should therefore be a public health priority, but it is not. This paper puts forward a new approach to reduce alcohol use and harms that would have major public health and social impacts. Our approach comprises individual behaviour and policy elements. It is based on the assumption that heavy drinking is key. It is simple, so it would be easy to introduce, and because it lacks stigmatising issues such as the diagnosis of addiction and dependence, it should not be contentious.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it