Bibliographic record
Abstract
OBJECTIVE: To assess smoking policies at Canadian acute care hospitals. METHOD: A questionnaire was designed, piloted and faxed to all acute care hospitals in Canada. The questionnaire was designed to address the following: what is the current policy regarding patient smoking? Are staff and/or visitors allowed to smoke inside the hospital? Is there a separate policy for psychiatric patients? Are smoking cessation products available at the hospital pharmacy? Is the policy governed by regional or municipal legislation? RESULTS: A total of 852 hospitals were included in the study. Of these, 476 responded to the questionnaire, for an overall response rate of 56%. Twenty-seven per cent of respondents allowed patient smoking inside the hospital. While staff smoking was not allowed inside most hospitals (93%), 32% of hospitals in Quebec allowed staff to smoke inside the building. Thirty per cent of hospitals had a separate policy for psychiatric patients, and 27% of hospitals had provisions for visitor smoking. Sixty-seven per cent of hospitals were able to offer patients smoking cessation products while they were in hospital. CONCLUSIONS: Many Canadian hospitals continue to allow smoking inside their facilities. There is considerable variation in hospital smoking policies across the country.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".