Smoke-free parks and beaches: an interrupted time-series study of behavioural impact in New York City
Bibliographic record
Abstract
BACKGROUND: In 2011, New York City (NYC) parks and beaches became smoke-free. There is currently little research evaluating the impact of such laws on smoking behaviour at the population level. METHODS: We used an interrupted time-series study design to analyse data from the New York State Adult Tobacco Survey to assess the law's impact using the rest of New York State as a comparison. Trends in how frequently respondents noticed people smoking in parks and beaches were analysed between the third quarter of 2009 and the fourth quarter of 2012, comparing NYC to the rest of the state. RESULTS: The trend in the frequency of NYC residents noticing people smoking in local parks and beaches decreased significantly over the six quarters after the law took effect. There was no comparable decline among residents in the rest of the state. An increase in the number of respondents who never noticed people smoking in NYC contributed to this decline. CONCLUSIONS: These results are consistent with previous studies and provide population-level evidence that suggest the law has reduced smoking in parks and on beaches.
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 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 | 0.000 | 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) | 0.000 | 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".