Tree cover and species composition effects on academic performance of primary school students
Bibliographic record
Abstract
Human exposure to green space and vegetation is widely recognized to result in physical and mental health benefits; however, to date, the specific effects of tree cover, diversity, and species composition on student academic performance have not been investigated. We compiled standardized performance scores in Grades 3 and 6 for the collective student body in 387 schools across the Toronto District School Board (TDSB), and examined variation in relation to tree cover, tree diversity, and tree species composition based on comprehensive inventories of trees on school properties combined with aerial-photo-based assessments of tree cover. Analyses accounted for variation due to socioeconomic factors using the learning opportunity index (LOI), a regional composite index of external challenges to learning that incorporates income and other factors, such as students with English as a second language. As expected, LOI had the greatest influence on student academic performance; however, the proportion of tree cover, as distinct from other types of "green space" such as grass, was found to be a significant positive predictor of student performance, accounting for 13% of the variance explained in a statistical model predicting mean student performance assessments. The effects of tree cover and species composition were most pronounced in schools that showed the highest level of external challenges, suggesting the importance of urban forestry investments in these schools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".