Environment and its protection from tobacco: a step towards tobacco end game, a perspective from India
Bibliographic record
Abstract
The planet is facing numerous environmental concerns. Healthy soil, an appropriate quantity of clean and fresh water, and clean air are just a few of the basic essentials that allow humanity to survive, but are being stressed by rising populations and human demand for the earth's valuable resources. Tobacco-related processes are harmful to the environment, from cultivation to manufacture, distribution, product usage, and post-consumer trash. The tobacco industry's adverse influence on deforestation, climate change, and waste production is huge and expanding, and until now, these components of the tobacco control picture have received very little attention from researchers and policymakers. According to article 18 of the World Health Organization's (WHO) "framework convention on tobacco control (FCTC)," ratifying parties are required to give due consideration to environmental protection and the general well-being of people in relation to tobacco farming and production within their respective territories. Instead of focusing on controlling the tobacco epidemic, national and international discussions have centered on this idea to end it, which has sparked relatively longer-term strategy. Globally many countries including New Zealand, Scotland, United Kingdom, Ireland, United States of America, Canada, Australia, Sweden, Finland as well as India (third largest tobacco producer nation in the world) have already adopted various initiatives to adhere with end game strategy. This paper investigates the environmental impact of tobacco and its various other detrimental effects on health of living beings', as well as the "tobacco end game" approach to not only control the epidemic but also create a "tobacco-free world".
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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".