Implementation of CDC Guidelines for Recess: A Formative Research Study
Bibliographic record
Abstract
The American Academy of Pediatrics recognizes recess as an essential part of overall child development in schools, impacting children's cognitive, socioemotional and physical health and development. However, recess is often removed from the school curriculum in exchange for more classroom activities. The Centers for Disease Control and Prevention (CDC) and SHAPE America developed Strategies for Recess in Schools to promote high-quality recess through specific actions, yet is not known how these are successfully implemented, particularly, in underserved settings. This formative research study examined the implementation of the CDC strategy in an urban, inner-city charter elementary school to identify barriers and facilitators to successful recess implementation from the perspective of various stakeholders. Thirteen in-depth interviews and focus group discussions were conducted with parents, teachers, recess monitors, and school administrators. Interviews were recorded, transcribed, and coded for thematic analysis, supported by group discussion and analytic memos. Results suggested that although stakeholders recognized the importance of recess, the implementation of the CDC strategy was neither uniformly understood nor implemented, suggesting that additional frameworks may be helpful in implementing the CDC strategy in schools in underserved communities.
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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 | 0.099 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".