Differences in School-readiness among Pre-school Children in Rural and Urban areas of Kisumu County, Kenya
Bibliographic record
Abstract
This study compared primary school preparedness of urban and rural preschool children in Kisumu county, Kenya. Children were assessed on their level of learning and development in the following domains: pre-academic skills (pre-literacy and pre-mathematics, executive function, and socioemotional cognition. The sample consisted of 390 preschool children who had completed their curriculum and were transitioning to Grade One. Children were assessed using an adapted and validated form of the Measurement of Development and Early Learning (MODEL) global item set. We hypothesized that urban children would score higher on all domains of learning and development than rural children. Results showed that indeed urban children were more prepared for primary school than were rural children in all the domains of learning examined in this study. In order to achieve Sustainable Development Goal 4 on equitable quality education that ensures life-long learning for all, county and national government should invest in early childhood development and education (ECDE) in both rural and urban so that all boys and girls can be ready for primary education and improve future outcomes for all children.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".