Investment incentives and the implementation of the Framework Convention on Tobacco Control: evidence from Zambia
Bibliographic record
Abstract
PURPOSE: Policy misalignment across different sectors of government serves as one of the pivotal barriers to WHO Framework Convention on Tobacco Control (FCTC) implementation. This paper examines the logic used by government officials to justify investment incentives to increase tobacco processing and manufacturing in the context of FCTC implementation in Zambia. METHODS: We conducted qualitative semistructured interviews with key informants from government, civil society and intergovernmental economic organisations (n=23). We supplemented the interview data with an analysis of public documents pertaining to the policy of economic development in Zambia. RESULTS: We found gross misalignments between the policies of the economic sector and efforts to implement the provisions of the FCTC. Our interviews uncovered the rationale used by officials in the economic sector to justify providing economic incentives to bolster tobacco processing and manufacturing in Zambia: (1) tobacco is not consumed by Zambians/tobacco is an export commodity, (2) economic benefits outweigh health costs and (3) tobacco consumption is a personal choice. CONCLUSIONS: Much of the struggle Zambia has experienced in implementing the FCTC can be attributed to misalignments between the economic and health sectors. Zambia's development agenda seeks to bolster agricultural processing and manufacturing. Tobacco control proponents must recognise and work within this context in order to foster productive strategies with those working on tobacco supply issues. These findings are broadly applicable to the global context. It is important that the Ministry of Health monitors the tobacco policy of and engages with these sectors to find ways of harmonising FCTC implementation.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".