[Inequalities in access to preventive health care for school children].
Bibliographic record
Abstract
UNLABELLED: Access to health care, including preventive health care for pupils affects the health of society. Equal access to pupils'preventive health care means the same level of preventive services for all children and adolescents regardless of school type, place and region of domicile. AIM: To analyse the quality of preventive health care for pupils in school year 2007/2008 in all school types in Poland, giving special attention to inequalities and access of this healthcare. MATERIAL AND METHODS: Reports from national public statistics filled by school nurses regarding preventive healthcare for pupils were analysed. Special attention was given to inequalites in access to RESULT: Disparities in access to preventive health care were observed. They affected more often pupils from rural schools, basic vocational schools and special schools. As a result, 60% rural elementary schools did not have a school health office. School nurses working in these schools were overburdened, each of them had to look after excessive number of pupils. Nearly one-quarter of basic vocational school pupils didn't have periodic check-up. Pupils from these schools less frequently participated in health education conducted by school nurses compared with pupils from other school types. In special schools school nurses were overburdened. One school nurse from these schools had to look after above limit of pupils' number (above 25% in urban and above 75% in rural schools). CONCLUSIONS: 1. Inequalities in access to preventive health care affected pupils from rural, basic vocational schools and special schools. They reflected existing social disparities in Poland. 2. Inequalities exist mainly in the social groups, who are at risk of social exclusion. 3. Equal opportunity for pupils'preventive health care requires systemic solutions in health and educational cooperation at government level.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".