Associations Between Elementary Students’ Victimization, Peer Belonging, Affect, Physical Activity, and Enjoyment by Gender During Recess
Bibliographic record
Abstract
School recess scholars have called for more research into collective relations between social, personal, and physical factors on students’ engagement and enjoyment of recess. Overall and by gender, this study serves to investigate a proposed model among 355 elementary school students from victimization to enjoyment through peer belonging, positive affect, and physical activity. Consenting students completed an online survey, and structural equation modeling (overall and in boys and girls) revealed an excellent fit of the data to the model (comparative fit index [CFI] and goodness of fit index [GFI] > .95, standardized root mean square residual [SRMR] < .08, root mean square error of approximation [RMSEA] < .10). Each of the path regression coefficients was significant ( p < .001) except for between victimization and positive affect. Results by gender revealed that all factor loadings were significant for both males and females, and all pathways between factors were significant for males, whereas for females, all pathways were significant except from victimization to affect and from physical activity to enjoyment. Boys were also significantly higher in victimization and physical activity during recess. For enhanced recess enjoyment among elementary school students, some schools may need to better consider how to support students’ reciprocal needs for peer belonging, affect, physical activity, and reduced victimization.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".