As the World Burns: Reconceptualizing Critical Global Citizenship Education Through an International Youth Climate Change Project
Bibliographic record
Abstract
As the planet is increasingly characterized by widespread environmental destruction and anthropogenic climate change, with unevenly distributed causes and unevenly experienced effects, how are educators to consider forms of planetary citizenship education that address students’ diverse positions and contexts yet shared responsibility to address these issues? Existing critical global citizenship education (GCE) theory provides a helpful conceptual framework for considering how to educate students in the face of climate change. However, there is a need to theorize critical GCE more fully in relation to environmental and climate issues for what we might term “planetary citizenship education.” As youth are those who both experience current education systems and will be most affected by changing climates, this paper thus turns to the experiences of youth themselves. Drawing on the perspectives of ninety-nine youth in thirteen countries with a collaborative, international climate change and education project, this paper will explore how critical CGE might evolve in the face of planetary crisis in order to educate for planetary citizenship.
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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 | 0.024 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.030 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".