British American Tobacco (BAT) and retail merchandising: Vype e-cigarette promotion in Ontario, Canada
Bibliographic record
Abstract
Electronic cigarettes (e-cigarettes) were initially offered by many independent producers, but multinational tobacco companies, which have notable marketing budgets, have increasingly acquired e-cigarette brands and developed their own ‘next generation products.’1 In the USA, for example, the top-selling e-cigarette brands during 2018 were JUUL, Vuse, MarkTen XL, Blu and Logic, which collectively accounted for a 97% market share.2 3 With the exception of JUUL, the leading e-cigarette brands were all produced by multinational tobacco companies. While JUUL is the evident brand leader by possessing an estimated 72% market share, Altria bought a 35% minority ownership of the e-cigarette producer for $12.8 billion in December 2018.4–6 Specialty vape shops were initially the standard for acquiring e-cigarettes, but convenience stores are emerging as key retailers given the established distribution channels of multinational tobacco companies. British American Tobacco (BAT) is the parent company of Imperial Tobacco Canada Limited—Canada’s largest producer of combustible cigarettes with an approximate 51% market share—and offers Vype among their portfolio of ‘next generation products.’7 8 As seen in figure 1, Vype promotions have circulated in Canada’s most populous province, Ontario, since August 2018, being placed on petrol pumps at Esso as well as the exterior and interior of affiliated Circle K convenience stores. Within the convenience store, promotional signage and displays for Vype e-cigarettes can also be seen (figures 2–4), including directly behind the cash register at point of sale (POS) and situated where conventional cigarettes and tobacco products are stored for sale. Like previously observed for tobacco retail merchandising, the display and advertisement locations for e-cigarettes are often at low-eye levels adjacent to candy, which suggests that their reach includes young consumers.9–13 Moreover, the juxtaposition of e-cigarette promotions with those of milk and sweet-flavoured beverages serves to normalise the product and build …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".