Antenatal smoking in vulnerable population groups: An area of need
Bibliographic record
Abstract
Antenatal smoking is a potentially preventable risk factor associated with pre-term birth and low birth weight. Rates of antenatal smoking, low birth weight, and infant mortality are all higher among the Indigenous populations than the non-Indigenous populations of Australia, Canada, New Zealand and the USA. Given this, it might be expected that publications examining smoking cessation efforts in Indigenous antenatal groups would be substantive. We examined the differences in the number and type of antenatal smoking publications for Indigenous and non-Indigenous populations across three time periods (1984-86, 1994-96 and 2004-06). Articles were classified as research studies (focusing on measurement, descriptive, or intervention studies), literature reviews, descriptions of programmes or research (with no data), or discussions. There was a significant increase in the number of publications relating to antenatal smoking among Indigenous populations in the time periods examined, but the total number of publications remained small. The number relating to general antenatal populations increased, but remained substantially lower than that relating to low birth weight. There was no increase in the proportional allocation of research articles to the intervention category in the later time period. The pattern of research output relating to antenatal smoking by mainstream or Indigenous populations is not optimal for advancement of knowledge in the field. There is a clear need for intervention-based research to allow the development of evidence-based practice for reducing the prevalence of antenatal smoking and associated health issues.
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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 | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".