Targeting of Asian Americans and Pacific Islanders by the tobacco industry: results from the Minnesota Tobacco Document Depository: Table 1
Bibliographic record
Abstract
OBJECTIVE: The study objective was to review internal tobacco industry documents written between 1985 and 1995 regarding the Asian American and Pacific Islander (AAPI) population in the USA. These documents detail opportunities and barriers to promotion of tobacco products, as viewed by the tobacco industry and its market research firms. DATA SOURCES: /methods: Researchers reviewed tobacco industry documents from the document depository in Minneapolis, Minnesota and the tobacco industry's website, The Tobacco Archive, in a systematic fashion. A combined technique was employed using title keywords, dates, and names to search the 4(b) index. FINDINGS: A review of internal tobacco company documents reveal that during the late 1980s, the industry and its market research firms recognised the importance of the AAPI community as a potential business market. Documents describe the population growth in this community, the high prevalence of smoking in countries of origin, high purchasing power of AAPI immigrants, cultural predisposition to smoking, opportunities afforded by the high proportion of retail businesses under AAPI ownership, barriers to developing the AAPI market, comprehensive campaigns, and political and lobbying efforts. Comprehensive campaigns were designed to integrate promotion efforts in AAPI consumer, retail, and business communities. CONCLUSIONS: The documents show that the tobacco industry developed specific promotion strategies to target the AAPI population. Tobacco control initiatives in the AAPI group have been slower to develop than in other targeted ethnic groups, and may benefit by increased awareness of industry methods to promote tobacco use.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".