Bibliographic record
Abstract
The relative age effect (rae) refers to the performance-related advantage of being born early in a cohort. In education economics, the rae shows that children born early in the year obtain better results than their peers. This is also true in sports education in which children are grouped by age during their training period. The main explanation of rae is the cutoff dates in youth sport. Because the cut-off date never changes, it is particularly difficult in education economics to identify the causal effect of the cut-off date on rae. On the other hand, sports and in particular soccer provides cases where the cut-off date in youth school changed : The French Football Association changed the cut-off date from during the 1995-1996 season. We show (1) the rae is caused by a change in the cut-off date ; (2) the rae still exists for older players (3) football players born in the fourth quarter have a physical superiority measured by the body mass index (bmi). Codes JEL : L83 ; C90
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.007 |
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".