Towards an educational praxis for planetary health: a call for transformative, inclusive, and integrative approaches for learning and relearning in the Anthropocene
Bibliographic record
Abstract
Fuelled by the intersecting challenges of climate change, biodiversity loss, pollution, and profound social, economic, and environmental injustices, calls for new ways to work together for a healthy, just, and sustainable future are burgeoning. Consequently, there is a growing imperative and mandate across the higher education space for transformative, inclusive, integrative-and sometimes disruptive-approaches to learning that strengthen our capacity to work towards the goals and imperatives of planetary health. This educational transformation requires attention to pathways of societal, policy, and system change, prioritising different voices and perspectives across jurisdictions, cultures, and learning contexts. This Viewpoint seeks to explore the developing areas of education for planetary health, while additionally reflecting on a praxis for education in the Anthropocene that is rooted within the confluence of diverse knowledges and practice legacies that have paved the way to learning and relearning for planetary health.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".