Season of birth and school success in the early years of primary education
Bibliographic record
Abstract
Several studies have reported significant relationships between children’s season of birth and measures of their academic success (i.e., the ‘season of birth effect’). Whereas most of these studies were cross‐sectional, the current study uses growth curve modelling to analyse longitudinal data on 3,187 children in Flemish primary education. The results indicate season of birth effects on both grade retention and mathematics achievement during the first two years of primary school. Because the Flemish cut‐off date is 31 December, children born in the fourth quarter (October‐November‐December) invariably are among the youngest in their grade age group. Almost 20% of these children were found to have been retained or referred to special education by the end of Grade 2, whereas for children born in the first quarter (January‐February‐March), this was only 6.34%. First quarter‐born children also showed moderately higher mathematics achievement at the start of first grade. During the next two school years, this achievement gap between children born in the first and the fourth quarter narrowed significantly. Finally, differentiated instruction was not found to be related to the decrease of the season of birth effect.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".