‘You cannot touch taxes easily’: making the case for tobacco taxation in India
Bibliographic record
Abstract
India represents over 1.3 billion people with >100 million adult smokers. The catastrophic health costs of smoking are staggering; and estimates show that even modest increases in taxes on cigarettes and bidis would both raise substantial revenues for the government and save ∼69 million years of healthy life over the next four decades. Karnataka represents a good example of tobacco control efforts and their impact. This case study examines the factors that have contributed to tobacco control policy in Karnataka based on 23 semi-structured interviews with key informants engaged in tobacco policymaking and decision-making, tobacco control/taxation research and advocacy. Their narratives indicate that: (i) Domestic taxation policy is complicated by the complex tax structure and centralized control over taxation with the introduction of Goods and Services Tax; (ii) Implementation of legal frameworks is a challenge, due to conflicts with powerful industry and farmer lobbies. A vigorous civil society backed by the Courts is necessary to garner political support; (iii) Action on taxation is hampered by weak leadership and mixed messaging; and (iv) There is a need for innovative policy solutions to promote both demand- and supply-side measures for tobacco control. Tobacco control advocates need to recognize the political economy of tobacco control and generate strong, reliable and scientifically sound evidence to support their arguments. Working for incremental 'wins' in terms of more stringent application of existing legal frameworks can make a substantial difference even in contexts where enhancing tobacco taxes is a challenge. Promoting multisectoral action is critical, at both policy and the ground levels, by expanding ownership and responsibility for tobacco control to sectors beyond health. Finally, the health sector needs to recommit to its role as a champion for tobacco control. Failure to do so would amount to a failure on multiple fronts-public health, economic, fiscal and ethical.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".