Extracurricular activity profiles and wellbeing in middle childhood: A population-level study
Bibliographic record
Abstract
This study examined profiles of participation in extracurricular activities (ECAs) in 4th grade children (N = 27,121; Mean age = 9.20 years; SD = .54; 51% male) in British Columbia, Canada. Latent class analyses were used to establish activity profiles and determine class membership; ANCOVA was used to investigate differences in mental wellbeing (optimism, life satisfaction, self-concept) and perceived overall health between groups. Data came from a cross-sectional, population-level child self-report survey (i.e., the Middle Years Development Instrument) implemented with 4th grade children in public schools. We found four distinct ECA profiles: participation in "All Activities", "No activities", "Sports" (i.e., individual and team sports), and "Individual activities" (i.e., educational programs, arts/music, individual sports). Wellbeing and health scores were highest for children in the "All Activities" and the "Sports" clusters, and lowest for those in "No Activities" and the cluster reflecting individual activities (i.e., "Individual activities"). Results are discussed in the context of previous research, and with respect to practical relevance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".