The inclusion of disadvantaged children in preschool programs: The children’s rights and social responsibility
Bibliographic record
Abstract
Participation of at least 95% of children between the ages of 4 and the mandatory school age in high-quality preschool programs represents an important contribution to the achievement of the Europe 2020 strategy. Slovenia is not far from achieving this objective; however, if we consider participation in preschool programs from the perspective of the entire population of preschool children and the realisation of children?s rights, we note that nearly a quarter of children - among them (at least in the wider European area) the most disadvantaged - have not realised the right to education. We studied the awareness of the importance of ensuring access to preschool programs for all children on a representative sample of 106 Slovenian preschool principals by means of quantitative pedagogical research. The results show a high percentage of disadvantaged children in the preschool areas and in the preschools themselves; on the other hand, only a low percentage (only one-third) of preschools collect data about disadvantaged children and implement preschool programs for them; only one-fifth of preschools implement preschool programs for disadvantaged children. In order to act responsibly and enable all children the right to education, we must start devoting greater attention to identifying and including disadvantaged children in preschool programs.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".