Relationships of Physical Activity to Brain Health and the Academic Performance of Schoolchildren
Bibliographic record
Abstract
This review examines possible relationships between academic performance and participation in sports, physical education, and other forms of physical activity. Recent fundamental research has reignited interest in the effects of physical activity on cognitive processes. Experimental studies of potential mediating variables point to physiological influences such as greater arousal and an increased secretion of neurotrophins and psychosocial influences such as increased self-esteem and connectedness to schools. In the specific case of sports, experimental studies are limited to demonstrations of greater attention and acute gains of mental performance immediately following such activity. Several quasi-experimental studies of other types of physical activity have been completed, mainly in primary school students; these have found no decrease in academic performance despite a curtailing of the time allocated to the teaching of academic subjects. Indeed, in some cases, experimental students undertaking more physical activity have out-performed control students. Many investigators have looked at cross-sectional associations between participation in sport or other forms of physical activity and academic performance. Despite difficulties in allowing for confounding variables, particularly socioeconomic status, the overall conclusion has been of a weak positive association. From the practical point of view, it can be concluded that the physical activity needed for healthy child development can be incorporated into the school curriculum without detriment to academic achievement.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".