Relationship between Physical Activity Level and Physical Literacy in Iranian Ethnic Children: A Cross-Cultural Study
Bibliographic record
Abstract
The purpose of this cross-cultural study was to investigate the relationship between the level of physical activity and physical literacy among Iranian children. Descriptive-correlation was implemented in the current investigation. The study population consisted of 270 students from the centers of Khuzestan, Lorestan, Kurdistan, Tehran, East Azarbaijan, and Sistan and Baluchestan provinces in 2021, with an age range of 8 to 12 years (135 males, 135 girls). Using the cluster sampling method, they participated in this investigation. Data was collected using the Canadian Physical Literacy Test-2 and the International Child and Adolescent Physical Activity Questionnaire. Additionally, SPSS version 23 software was employed to conduct Pearson’s correlation coefficient test and two-way multivariate analysis of variance for data analysis. The results showed a positive and significant relationship between physical literacy and physical activity (P=0.001). The results of the geographical regions analysis indicated that the participants residing in Khorramabad, Sanandaj, and Zahedan exhibited significantly higher levels of physical activity and physical literacy than those residing in Tehran, Ahvaz, and Tabriz (P=0.001). The results of the study on the place of residence indicated that the children residing in the village exhibited a higher level of physical activity and physical literacy. Physical literacy (p=0.001) and physical activity (p=0.001) were significantly improved by gender. Based on the research findings, it seems that the physical literacy of children is influenced by a variety of factors, including gender, geographical regions, place of residence, and socio-cultural aspects. This is why it is advised that physical education programs implement decentralized planning.
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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 | 0.001 |
| 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) | 0.001 | 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".