Global tobacco control and economic norms: an analysis of normative commitments in Kenya, Malawi and Zambia
Bibliographic record
Abstract
Tobacco control norms have gained momentum over the past decade. To date 43 of 47 Sub-Saharan African countries are party to the Framework Convention on Tobacco Control (FCTC). The near universal adoption of the FCTC illustrates the increasing strength of these norms, although the level of commitment to implement the provisions varies widely. However, tobacco control is enmeshed in a web of international norms that has bearing on how governments implement and strengthen tobacco control measures. Given that economic arguments in favor of tobacco production remain a prominent barrier to tobacco control efforts, there is a continued need to examine how economic sectors frame and mobilize their policy commitments to tobacco production. This study explores the proposition that divergence of international norms fosters policy divergence within governments. This study was conducted in three African countries: Kenya, Malawi, and Zambia. These countries represent a continuum of tobacco control policy, whereby Kenya is one of the most advanced countries in Africa in this respect, whereas Malawi is one of the few countries that is not a party to the FCTC and has implemented few measures. We conducted 55 key informant interviews (Zambia = 23; Kenya = 17; Malawi = 15). Data analysis involved deductive coding of interview transcripts and notes to identify reference to international norms (i.e. commitments, agreements, institutions), coupled with an inductive analysis that sought to interpret the meaning participants ascribe to these norms. Our analysis suggests that commitments to tobacco control have yet to penetrate non-health sectors, who perceive tobacco control as largely in conflict with international economic norms. The reasons for this perceived conflict seems to include: (1) an entrenched and narrow conceptualization of economic development norms, (2) the power of economic interests to shape policy discourses, and (3) a structural divide between sectors in the form of bureaucratic silos.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".