Transformative learning at the community-university-land interface: A political ecology of knowledge, education and health
Bibliographic record
Abstract
As awareness grows of the catastrophic implications of global environmental change, multiple scholarly fields addressing health-environment relationships have advocated 'transformative' educational strategies. Holistic Indigenous health-environment models inspire and inform many such efforts, but related land-based learning initiatives involving universities are often impeded by the competitive processes of academia. In this article we report on a community-university partnership – Pedagogy for the Anthropocene (P4A) – aimed at developing transformative educational responses to pressing global crises, inspired by land-based approaches. We integrate political ecologies of health, education, and knowledge to understand the troubled production of pedagogical knowledge in P4A, participant experiences in the resulting educational programs and the role of health and bodies in both. We first trace the production of knowledge as shaped by macroscopic and localized institutional forces; organizational and occupational dynamics; interacting knowledges and individuals; and material factors. Next, we explore participant experiences in the resulting educational programming. In both steps, affect-laden bodies of academics, trainees and community members reveal entanglements with human communities and more-than-human elements, shaped in variable ways by institutional forces such as settler colonialism and university neoliberalization. One key finding involves the role of universities in relation to land dispossession at home and abroad; another includes the challenges of pursuing transformational community-university research within contemporary universities. Tracing such entanglements yields implications for future land-based learning efforts in university settings, and broader praxis for environmental justice in the shadow of higher education's complicity with settler colonialism and globally extractive neoliberal capitalism.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.092 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".