Barren or biodiverse schoolgrounds :their effects on children
Bibliographic record
Abstract
This study compared the effects on children of two schoolgrounds chosen for maximum variability of vegetation, one richly biodiverse and the other relatively barren. A total of 349 children in grades one through seven participated in three sections of the user-based research by: (1) sharing perceptions of each schoolground through interviews and classroom brainstorming sessions, (2) stating their preferences for various schoolground elements in a survey, and (3) indicating how they used their schQolground by drawing cognitive maps. Analysis of both qualitative and quantitative data indicated that on the biodiversified schoolground the quality of the children's outdoor experience is richer, the children's stated preferences are more diverse and more oriented toward nature, and the use of their outdoor environment is more complex, especially for primary children and for intermediate girls. All 19 Mann-Whitney tests showed statistically significant differences in comparing children's preferences for fourteen schoolground elements. Additionally, the biodiverse schoolground afforded children more opportunities for imaginative play, reflection and conversation. The results of this research made recommendations regarding participatory schoolground management based on interviews with several stakeholders, including children, teachers, administrators, parents, noon-hour supervisors arid ground maintenance staff. It also has implicatons or future study on curricular integration of environmental education, the healthy development of children, and for the design, management and maintenance of sustainably biodiverse schoolgrounds.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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".