Analyzing big tobacco’s global youth marketing strategies and factors influencing smoking initiation by Nigeria youths using the theory of triadic influence
Bibliographic record
Abstract
BACKGROUND: Major transnational tobacco companies (TTCs) have identified Nigeria, the seventh most populous country in the world, as a market with a significant revenue potential, given its high youth population and growing gross domestic product (GDP). This research analyses tobacco industry-related strategies and activities targeting youth (aged 15 to 24 years) in Nigeria involving existing, but most importantly, future tobacco users. Nigeria is the focus of this study because the tobacco industry has viewed it as a major emerging market since the 1990s. Successful marketing in Nigeria could provide the industry with a template for similar initiatives in other emerging markets in low- and middle-income countries. METHODS: The research began with a systematic review of secondary literature to determine how the tobacco industry has targeted youth globally and factors contributing to youth smoking initiation. It then used the theory of triadic influence as a heuristic framework to categorize the various factors influencing youth smoking initiation and industry strategies related to increasing tobacco use among youths. Quotations from internal tobacco industry documents were organized into the three streams of the theory of triadic influence: biology/personality, social and cultural/environmental streams. A total of 12 interviews were conducted with 6 policymakers and governmental officials, 2 civil society organization representatives, a high school principal, a journalist and 2 researchers to investigate how the tobacco industry had targeted youth in Nigeria. RESULTS: The findings indicate that TTCs have actively targeted youth in Nigeria since the 1990s, focusing on changing behaviour through the biology/personality, social and environmental/ cultural streams. CONCLUSION: The study suggests that Nigeria implement and vigorously enforce its 2015 National Tobacco Control Bill as well as a package of other measures to prevent tobacco companies targeting youth.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".