Can green schools influence academic performance?
Bibliographic record
Abstract
The adoption of green building certification schemes, such as Leadership in Energy and Environmental Design (LEED) for Schools, establishes common building factors among certified schools. Many building factors influence student performance outcomes including cognitive skills, standardized test scores and rates of absenteeism. This review synthesizes current research from 28 new studies and 101 other studies that were previously included in 15 reviews of associations between LEED-specified building factors and these performance outcomes in schools. In appraising the relative quantity and quality of studies, along with the frequency of LEED credits found in certified schools, this review finds that building features common to 100% of LEED-certified schools also have the strongest research supporting associations with academic outcomes, and largely come under the purview of indoor air quality (e.g., minimum ventilation rate, filtration or air cleaning) and acoustic performance. Comparatively, building factors related to the school site and daylighting have fewer associated studies, but findings suggest these are good targets for future research as they may be important for influencing student performance. Achieving a transition to a lower carbon future requires that schools be built with their energy impacts in mind; and this review provides value to those involved in the planning and design of these green schools that facilitate improved student performance outcomes.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Review synthesizing evidence on green school buildings; appraises the evidence base but answers a substantive domain question about student performance.
The review synthesizes evidence about green schools and academic performance rather than studying evidence synthesis.
Review linking green-school building factors to student academic outcomes; education environment, not research as object.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".