Support for New Zealand's Smokefree 2025 goal and key measures to achieve it: findings from the ITC New Zealand Survey
Bibliographic record
Abstract
OBJECTIVES: To assess support among smokers and recent quitters for the Smokefree New Zealand (NZ) 2025 goal and measures to facilitate its achievement. METHODS: Data from CATI interviews with 1,155 (386 Māori) smokers and recent quitters in Wave 1 (August 2016-April 2017) and 1,020 (394 Māori) in Wave 2 (June-December 2018) of the International Tobacco Control (ITC) NZ Survey. RESULTS: (Wave 2 unless stated): Almost all (95%) participants were aware of and more than half (56%) supported the smokefree goal. Support was highest (69-92%) for measures to reduce smoking uptake and protect children from exposure to secondhand smoke. Support was also high for other smokefree policies including mandated denicotinisation of smoked tobacco products (73%) and tobacco retailer licensing (70%, Wave 1). Support was lowest (<30%) for increasing the tobacco tax, but higher (59%) if additional revenue raised was used to help smokers to quit. Support for Smokefree 2025 and key measures to achieve it was generally higher among ex-smokers than smokers but mostly similar among Māori and non-Māori participants. CONCLUSIONS: There is substantial support among smokers and ex-smokers for the Smokefree 2025 goal and many measures that could help achieve it. Implications for public health: Implementing a comprehensive strategy to achieve Smokefree 2025 is likely to be acceptable among New Zealand's smokers and ex-smokers.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".