A Systems Thinking Approach to Green Schools
Bibliographic record
Abstract
The school facility is positioned to provide contextual cues for informal and formal learning in environmental education (EE). Evidence suggests that incorporating the school facility with EE also provides a context in which students can engage with environmental issues like waste management and energy conservation. Using the school building as a learning tool has been well documented and is supported as an instructional approach in Ontario’s public schools. The purpose of this study is to explore the interacting attributes of Ontario EcoSchools to identify themes supporting the integration of the school facility with EE. This qualitative study examines how this occurs within the context of whole school sustainability. This is achieved through a secondary data analysis of the results from 2017/2018 EcoSchool Platinum applications to determine how these schools are integrating the school facility with EE. Platinum certification allows high achieving schools to deepen their existing green school program. A school’s building and operations are important components in achieving school board policies for EE and sustainability while also supporting national and provincial climate change mitigation and sustainability objectives. The findings in this investigation highlight the themes, Formal/Curriculum Learning, Non-formal Learning, Building Attributes, Cross-Cutting and Partnerships within the school facility that is a sub-system functioning as a place where students are learning about environmental issues through direct and indirect engagement with their surroundings. Integrating the school facility with EE reflected non-linear approaches to EE where students were reflexive as they engaged in sustainable practice while co-creating their sense of place with the school facility.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".