Climate Justice Pedagogies for Youth and Planetary Well-Being: Perspectives from Canada*
Bibliographic record
Abstract
Climate justice education connects global ecological precarity with community and planetary well-being, challenging hegemonic Western epistemologies, settler colonialism, racial capitalism, and other related inequities. Educating for climate justice can address intergenerational, intersectional, and interspecies injustice and young learners’ frequent mental health distress about the impacts of climate change. This thesis research, situated in critical democratic citizenship and holistic education, generated insights about and for climate justice education in diverse Canadian* school contexts. The conceptual framework centers on how pedagogical approaches can deepen understandings of climate change and its root causes, support active and activist citizenship orientations toward addressing complex challenges and injustices, and nurture learner and planetary relational well-being. This qualitative study engaged 6 classroom educators (grades 5-10) in three Canadian* provinces (British Columbia, Alberta, Ontario) and 3 young Canadian* climate justice activists (British Columbia, Ontario) in interviews and a series of group dialogues—exploring under-studied pedagogical and curricular practices that these educators used - to attend to climate justice and their learners as whole persons. Findings uncover the myriad ways these educators attempted to address the scope, scale, and depth of ecological harm while engaging students in inquiry-based learning, critical thinking, and connections with ecosystems to inform and encourage action to resist climate change. These teachers' pedagogies, attentive to student well-being as well as to the climate multi-crisis, included alternative assessment practices; naming possibilities for cultural, social, and technological transformation; and emphasizing joy, interconnection, and reciprocal relationships within ecosystems. Participating youth activists, in their understandings and public pedagogies, were more likely than these six schoolteachers to address the structural causes of the ecological crisis and to confront complex climate emotions including grief and despair. This research identifies promising principles and pedagogical approaches towards decolonizing and regenerating critical democratic citizenship education for climate justice. It notes educators’ need for greater support to address the complexities and controversies of collective and political action-oriented curriculum for learners’ development of transformative agency to address the globalized, yet locally and inequitably experienced, climate emergency. Relationality was central to a critical and holistic approach to climate justice education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".