The Development of E-cigarette Policy in Australia: The Policy, How It Came About and How It Is Justified
Bibliographic record
Abstract
Abstract Australia has banned the sale of nicotine-containing e-cigarettes as consumer goods. Australian policy allows their use on prescription, but it has been very difficult for Australian smokers to legally access them for smoking cessation. Regulatory changes introduced in October 2021 may allow smokers’ easier access to these products via a medical prescription, but Australian policy still differs markedly from that of other high-income English-speaking countries where e-cigarettes can be legally purchased as consumer goods (e.g. UK, US, Canada and New Zealand). This chapter discusses the history of Australian regulatory approaches to e-cigarettes. It begins by describing how Australian tobacco control policies influenced policy on e-cigarettes and then outlines the rationale that regulators and health organisations have used for the policy. We then discuss the factors that played a crucial role in producing an e-cigarette policy in Australia which is so starkly different from that in UK, Australia’s original colonial power and a major model for other Australian public health policies.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".