Philip Morris International: a New Year’s resolution
Bibliographic record
Abstract
In January 2018, Philip Morris International (PMI) placed ads in UK newspapers explaining that their New Year’s resolution was ‘to stop selling cigarettes in the UK’ (see figure 1).1 To help achieve this goal, the PMI ads refer to four commitments for 2018: Figure 1 Philip Morris International ads in the UK. 1. Launch a website and campaign to provide smokers with information on quitting and on alternatives to cigarettes 2. Offer to support Local Authority cessation services where smoking rates are highest 3. Seek Government approval to insert, directly into our cigarette packs, information on quitting and on switching 4. Expand the availability of new, alternative products in the UK. While the second commitment is contrary to Article 5.3 obligations of the WHO Framework Convention on Tobacco Control (FCTC),2 and the third prohibited by the Standardised Packaging of Tobacco Products Regulations 2015,3 the latter, at least, could be amended by the UK government. The relevant text, ‘No insert or additional material may be attached to or included with the packaging of a unit packet or container packet of cigarettes’, could be revised with the addition of ‘unless specified by Government (eg, to educate …
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.075 | 0.042 |
| Insufficient payload (model declined to judge) | 0.053 | 0.026 |
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".