Social pathology of respiratory diseases in infancy and childhood
Bibliographic record
Abstract
Introduction: Social pathology, in the sense of association between diseases and social conditions, may be considered for any disease. Immediate and long-term adverse effect of passive exposure to parental smoking, indoor air pollution, less physical activity, poverty etc. on diseases of respiratory system have been reported (Pattenden, S. et al.Tobacco Control 2006; 15:294-301). Aim: To analyze the spreading of social determinants on respiratory diseases in infancy and childhood in Bulgaria. Methods: Data were collected by direct individual self-administer questionnaire among 347 women whose children have been visiting nursery schools in Pleven municipality, Bulgaria. Results: Three quarter of children are exposed to second hand tobacco smoking at home. For about 20% of them the exposure starts at the intrauterine period because mother had been smoking during the pregnancy. Although the majority of parents (95.7%) reported that they understand harm of passive smoking, more than a half of them do not avoid smoking in presence of their children. The impact of indoor air pollution due to smoking is enhanced by the solid fuel heating in a quarter of reported cases, overcrowding of dwellings (64.5%) and restricted time of outdoor activities (13.9%). Although the study results are in consistence with other studies and national statistics, there are reasons to suspect even worse reality because the sample does not include families from marginalized groups in terms of economic and education profile. Conclusion: The influence of behavior, environmental and economic risk factors on children9s health is mediated by the family background so it should be the target of social therapy of respiratory diseases in the childhood.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".