Developmental Benefits of Extracurricular Sports Participation Among Brazilian Youth
Bibliographic record
Abstract
Youth sporting activities have been explored as a way to impact positive personal transformation and development, glaringly demonstrated by world-wide investments in public policies, programs, and projects. We studied positive effects of participation in sports on the developmental assets of 614 adolescents (13.1 ± 1.7 years) actively engaged in extracurricular sport programs targeted at socially disadvantaged youths, from five municipalities across five states of the southern, south-eastern and north-eastern regions of Brazil. Participants responded to a developmental assets questionnaire designed to capture sociodemographic and human development data. Multilevel logistic regression was used to explore associations between years of participation in sport and human development indicators, controlling for age and sex. Our results showed that the quality of the young people's support network and duration of program participation positively influenced sport participation, which, in turn, was associated with willingness to learn. A strong association was also observed between sport participation and developmental assets. Thus, we offer new evidence of a relationship between positive development and environmental factors in which individual and contextual forces can be aligned, and we provide new reference data for developing countries.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".