<i>Problematising</i> ‘Transformative’ Environmental Education in a Climate Crisis
Bibliographic record
Abstract
The Editor's Introduction sets the stage for this Special Issue with calls for action in light of the climate crisis and other environmental problems sweeping our planet. It then offers a brief overview of the topics our contributors address, and in some cases the philosophical sources they brought into this conversation. It then surveys the background literature on ‘transformative’ environmental education, the topic being problematised and developed by our contributors. This review of the literature reveals a wide range of interpretations, but also shows some productive hybrids in terms of transformation and transgression: seen as opportunities for effecting the changes in attitude, values and behaviours we need for our collective survival. Questions of efficacy are briefly discussed, although it was not the purpose of this Special Issue to decide which are the most effective eco-pedagogies. In closing, we remark on the need for foresight in educational planning and policy, as in government generally, to address the magnitude of problems threatening all life on this planet.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.018 |
| 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".