Challenging Complacency in K–12 Climate Change Education in Canada: Decolonial and Indigenous Perspectives for Designing Curricula beyond Sustainable Development
Bibliographic record
Abstract
This new critical volume presents various perspectives on teaching and teacher education in the face of the global climate crisis, environmental degradation, and social injustice. Teaching in the Anthropocene calls for a reorientation of the aims of teaching so that we might imagine multiple futures in which children, youths, and families can thrive amid a myriad of challenges related to the earth’s decreasing habitability.Referring to the uncertainty of the time in which we live and teach, the term Anthropocene is used to acknowledge anthropogenic contributions to the climate crisis and to consider and reflect on the emotional responses to adverse climate events. The text begins with the editors’ discussion of this contested term and then moves on to make the case that we must decentre anthropocentric models in teacher education praxis.The four thematic parts include chapters on the challenges to teacher education practice and praxis, affective dimensions of teaching in the face of the global crisis, relational pedagogies in the Anthropocene, and ways to ignite the empathic imaginations of tomorrow’s teachers. Together the authors discuss new theoretical eco-orientations and describe innovative pedagogies that create opportunities for students and teachers to live in greater harmony with the more-than-human world. This incredibly timely volume will be essential to pre- and in-service teachers and teacher educators.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.033 | 0.014 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".