Trends in Tobacco Consumption – a Comparative Analysis of WHO European Region Countries
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
Tobacco consumption, as well as the consumption of any other psychoactive substances, lead to addictions, which is a serious problem that modern societies have to face. To reduce the negative consequences of nicotine consumption and to provide sustainable development, many governments, in both developed as well as developing countries, adopt policies to reduce tobacco production and consumption. For example, they implement various health programs to combat addiction, and they also provide appropriate financial and fiscal resolutions. Any actions taken at different decision-making levels are often bounded with economic and financial policies of a particular state, including fiscal policy. State interventionism concerning tobacco is most visible in developed countries such as the US, Canada, and European Union countries. Developing countries and Asian countries have also started to introduce regulations concerning tobacco consumption on a large scale in response to the negative effects of nicotinism. The main aim of the paper is to show consumption trends as well as the fiscal and price policies of tobacco products. The theoretical part is supplemented by data from reports and analyses presented by the World Health Organization (WHO).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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