Differences on Motor Competence in 4-Year-Old Boys and Girls Regarding the Quarter of Birth: Is There a Relative Age Effect?
Bibliographic record
Abstract
The aim of this study was to evaluate the differences on motor competence between boys and girls aged 4 years old and investigate the existence of Relative Age Effect on their motor competence. In total, 132 preschool children were evaluated, of whom 60 (45.50%) were girls and 72 (54.5%) were boys. The distribution of the participants was from quarter 1 [n = 28 (21.2%)], quarter 2 [n = 52 (39.4%)], quarter 3 [n = 24 (18.2%)], and quarter 4 [(n = 28 (21.2%)], respectively. The Movement Assessment Battery for Children-2 (MABC-2) was used to collect the data. The data show the main effects on quarter of birth factor in manual dexterity (MD; p < 0.001), in aiming and catching (A&C; p < 0.001), in balance (Bal; p < 0.001) and in total test score (TTS; p < 0.001). There are also statistical differences on gender factor in MD (p < 0.001) and in TTS (p = 0.031). A significant effect was also found in the interaction between two factors (gender and quarter of birth) in MD (p < 0.001), A&C (p < 0.001), and Bal (p < 0.001). There are differences in all the variables studied according to the quarter of birth and only in manual dexterity and in the total score if compared according to gender (the scores are higher in girls).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".