Ecological education and action research: A transformative blend for formal and nonformal educators
Bibliographic record
Abstract
Action research, within the context of an ecological education graduate degree, can result in transformative learning experiences for formal and nonformal educators. Encountering layers of hegemony and awakening to relations of power facilitated a profound shift within these teacher-researchers, engendering a newly felt sense of empowerment. Integral to the transformative learning process were opportunities for reflection fostering greater balance between the personal and professional, learning to accept feelings of confusion and disorientation, and evolving a deeper understanding of ecological education. Moreover, this investigation reveals the existence of a synergistic relationship between ecological education, action research, and transformative learning. This kinship is substantiated through analysis of data from four cohorts of students engaged in capstone action research projects.
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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 | 0.067 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.057 |
| Scholarly communication | 0.027 | 0.019 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".