Marketing IQOS in a dark market
Bibliographic record
Abstract
INTRODUCTION: Phillip Morris International (PMI) is pushing hard to promote IQOS heat-not-burn cigarettes in Ontario, Canada. Canada regulates IQOS as a tobacco product so that the robust tobacco marketing ban creates challenges to its promotion. METHODS: We collected data on IQOS promotion in 49 retail outlets, and through interviews with clerks and observations outside an IQOS store. RESULTS: The dominant marketing channel is the visible availability of IQOS in a large number of tobacco retail outlets-1029 across Ontario. Several stores display the price of 'heated tobacco' on one of three price signs which are permitted despite Ontario's total display ban. IQOS boutique stores are the locus of aggressive promotion including exchanging a pack of cigarettes or lighter for an IQOS device, launch parties, 'meet and greet' lunches and after-hour events. Outside the store, promotion includes a prominent IQOS sign, a sandwich board sign reading 'Building a Smoke-Free Future' and sales representatives regularly smoking IQOS. Membership services: Upon acquiring an IQOS device one can register to access the IQOS website store5 and receive customer support services, a map of retail locations and a product catalogue. Members receive regular email invitations to complete surveys with opportunities to win prizes. CONCLUSIONS: These promotion activities have undoubtedly made substantial numbers of Ontarians aware of IQOS. Yet, the government has not provided guidance as to absolute and relative potential harms. Our observations of tactics to promote a new tobacco product in a dark market may inform government regulatory policy and non-governmental organisation efforts wherever heat-not-burn products are introduced.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.002 |
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".