Tobacco industry presence and practices in Mozambique: a ‘chaotic’ but worthy market
Bibliographic record
Abstract
BACKGROUND: Mozambique has experienced a series of tobacco industry consolidations both in tobacco leaf buying and processing, and in cigarette manufacturing and marketing. The growth of the tobacco industry presence in Mozambique was followed by an increase in tobacco industry's Corporate Social Responsibility (CSR) activities. This is the first paper to describe the history of tobacco industry activities in Mozambique, a party to the WHO Framework Convention on Tobacco Control (FCTC). METHODS: We reviewed industry documents and associated web-based information. Industry documents (1990-2021) were identified through University of California San Francisco's Truth Tobacco Industry Documents Library. We followed with a search of web-based sources pertaining to the tobacco industry in Mozambique. We complemented our analysis with select media sources to identify statements by government officials in relation to the tobacco industry. We mapped major tobacco industry players, industry partnerships and corresponding CSR activities. RESULTS: Tobacco production increased substantially in Mozambique in the 1990s when tobacco companies began targeting African countries. The increased attention to tobacco production, trade and sales in Mozambique was coupled with greater industry involvement in CSR activities. We identified 10 tobacco industry CSR programmes in Mozambique. Most of the CSR programmes focus on health including HIV/AIDS, social issues and environmental issues. CONCLUSIONS: Similar to other tobacco-growing countries, the industry facilitated an increase in tobacco production and continues efforts to increase the tobacco consumption market while engaging in CSR activities focused on social and environmental issues. As in other countries, CSR initiatives in Mozambique enhance industry's reputation. Importantly, these CSR programmes and partnerships breach national laws and the provisions of the FCTC. The continuation of these programmes suggests limited attention within government to protect public policy from industry interference in compliance with Article 5.3 of the FCTC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".