Bibliographic record
Abstract
It gives me great pleasure to write a forward on this topic at a time when there is such a groundswell of international support for plain packaging of tobacco products. World No Tobacco today in 2016 had as its tag line “Get ready for plain packaging” and the world’s health ministers are doing just that.When Australia became the first country in the world to remove all colours and logos on tobacco packs in 2011 – recognising their allure to young new smokers – the tobacco industry tried every move in their book to stop us. Lobbying, donations, advertising campaigns, threats, dodgy research, front groups, overblown claims and legal action dominated our political debate for two years. When all these local manoeuvres failed, the industry switched its effort to ensuring we were the only country to take this step. Writing in November 2016, it is clear that those efforts, both local and international, have manifestly failed. Country after country – France, the UK, Ireland, Canada, Norway, New Zealand – are implementing plain packaging, passing their laws or consulting with the community before introduction and many more countries will move this way in the coming months and years.Plain packaging of tobacco products is now truly an international movement. It is an epidemic of the best sort, as countries catch on to its value, purpose and ease of implementation. We will now see its introduction spread like wildfire around the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.060 | 0.040 |
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".