Preparing Teachers for Work in a Time of Environmental Crises: A Grass-roots Response
Bibliographic record
Abstract
Our planet faces numerous environmental threats of anthropogenic cause, including climate chaos, plastic pollution and deforestation.All of these impact biodiversityour life support mechanism.With regard to this, Education can be said to have failed humanity and all living things by largely ignoring these issues and by being complicit in a way of living on the planet that is not sustainable.There is a growing concern that education systems are making environmental problems worse by prioritizing the preparation of young people for an unsustainable economic paradigm, and framing success in terms of economic wealth and consumption.Education should now have a crucial role to play in helping to address, minimize and mitigate the impact environmental threats while helping to build a sustainable future.Initial teacher education programmes can be seen as a driver of change in education systems so it can be argued that they should be preparing new teachers for this existentially important work.To date, however, teacher education programmes in Canada have generally done a poor job of preparing student teachers for environmental and sustainability education.This paper reviews the collaborative strategies developed and employed by a group of teacher educators in Canada who have sought to address the shortfall in environmental and sustainability education in pre-service teacher education.Their grass-roots work has drawn attention to the issue and advocated for change, both within institutions and more widely.It has also created new research opportunities and by sharing success stories significant progress in praxis has been made in recent years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.017 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.009 | 0.010 |
| 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".