Finding Courage in the Unknown: Transformative Inquiry as Indigenist Inquiry
Bibliographic record
Abstract
Educators often wonder how to respond purposefully to vexing issues such as ecological sustainability, social justice and holistic health and wellness. The search for useful ways of proceeding can be addressed through engagement in the process of transformative inquiry, a mode of inquiry for educators that resonates with indigenous views and ways of being. At its heart, the approach seeks to support preservice teachers in their personal journeys towards decolonizing and indigenizing. Ultimately, these efforts ripple out to affect their future students and the institutions in which they learn, teach and, hopefully, inquire. Weaving poetry written from my own experience on becoming indigenist, with the work of scholars such as Manulani Meyer, Lorna Williams, Marie Battise, Shawn Wilson, and Gregory Cajete, I highlight salient aspects of transformative inquiry that can be particularly useful in changing the trajectory of both education and educational research: welcoming spirit, deep and generous listening, connecting to place, and finding courage in the unknown.Keywords: Transformative inquiry; indigenizing education; decolonizing research; teacher education; educational research
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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 | 0.043 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.022 | 0.204 |
| Scholarly communication | 0.027 | 0.031 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.014 |
| 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".