Relationship Between Socioeconomic Status and Organized Sports Among Primary School Children: A Gender-Based Analysis of Sports Participation
Bibliographic record
Abstract
Sports participation according to socioeconomic status (SES) was related to children in high-income Western countries. This study aimed to examine whether family or neighborhood-level SES is associated with current and continued organized sports participation, including the types of sports, among Japanese primary school children from preschool onward. The participants consisted of 269 girls, 255 boys, and their parents. Data on the type of sports participation at the current school or preschool, parental employment, and education were collected by questionnaire. Neighborhood-level SES was evaluated by the average annual income within 4 km of each school. The odds of sports participation was higher among children with mothers identifying as housewives or those with mothers employed part-time. Among girls, the odds of continued sports participation were lower if their mothers were junior high school or high school graduates or junior college/vocational school graduates. The odds of sports type like swimming were higher for children whose mothers had part-time jobs. Lower average community income was associated with lower participation in football and higher participation in baseball. These findings suggest that mothers' employment and academic background are important correlates of sports participation for children, with variations observed by sport type and gender.
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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 | 0.000 |
| 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".