Nature Education for Sustainable Todays and Tomorrows (NEST): Hatching a New Culture in Schooling
Bibliographic record
Abstract
Abstract Within the North American public education system, institutionalised structures of schooling often prevent teachers from aligning their values with their practice when it comes to environmental education (Bowers, 1997; Weston, 2004). In response to this, this article will outline our lived experiences, as teachers and researcher, in disrupting the traditional school system as we work toward building a new culture in schooling through nature-based education. Acts of disruption that we will speak to include: going outside for learning on a regular basis, teaching for empowerment, involving families in the education, attempts to play with structural confines of schooling, and finding ways to stay empowered ourselves. Through this work, we have found that there is a rippling effect to the disruption that requires courage, grit, and resilience such that we do not slide back into conventional approaches. We have also become empowered in our practices through implementing these changes, watching our students become active stewards within their communities and beyond. We are learning deeply about the work of structural change within a public school district and offer words here as inspiration and support for others wishing to make changes within their own context.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".