Support for and potential impacts of key Smokefree 2025 strategies among Māori who smoke
Bibliographic record
Abstract
AIM: The recently passed Smokefree Environments and Regulated Products (Smoked Tobacco) Amendment Act has the potential to profoundly reduce smoking prevalence and related health inequities experienced among Māori. This study examined support for, and potential impacts of, key measures included within the legislation. METHOD: Data came from Wave 1 (2017-2019) of the Te Ara Auahi Kore longitudinal study, which was conducted in partnership with five primary health organisations serving Māori communities. Participants were 701 Māori who smoked. Analysis included both descriptive analysis and logistic regression. RESULTS: More Māori participants supported than did not support the Smokefree 2025 (SF2025) goal of reducing smoking prevalence to below 5%, and the key associated measures. Support was greatest for mandating very low nicotine cigarettes (VLNCs). Participants also believed VLNCs would prompt high rates of quitting. Participants who had made more quit attempts or reported less control over their life were more likely to support VLNCs. CONCLUSION: There was support for the SF2025 goal and for key measures that could achieve it. In particular, VLNCs may have significant potential to reduce smoking prevalence among Māori. As part of developing and implementing these measures it will be important to engage with Māori who smoke and their communities.
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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 | 0.001 | 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".