Deepening Ecological Relationality Through Critical Onto-Epistemological Inquiry
Bibliographic record
Abstract
Indigenous worldviews remain at the margins of education, science, and sustainability efforts. The emergence of sustainable science holds promise as a means of advancing deep sustainability and recentering Indigenous knowledge. Transformative learning’s engagement with sustainable science has the potential to play an integral role in this paradigmatic shift which necessitates a broader legitimation of our ecology as a deeply interconnected living system. An important part of this project is learner-centred critical onto-epistemological inquiry—the critical study of one’s own reality and implications for ecological relationship. Drawing on Intuitive Inquiry and Kaupapa Māori research, this article illuminates the partial decolonization of my own Life-World and arrival at a deepened sense of ecological relationship. Initially focusing on “the dreaming,” it integrates my visceral experiences of the land and Indigenous constructions of reality through interviews with Ngāi Te Rangi and Plains Cree elders. The implications for transformative learning and sustainability are discussed.
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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 | 0.023 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.094 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".