Relational Autonomy in Teacher Education: Deepening Teacher Quality through Indigenous and Decolonizing Education
Bibliographic record
Abstract
Drawing from transnational and critical studies in Indigenous and decolonizing education, this paper argues for relational autonomy as a key dimension of teacher quality. Bridging feminist critiques of autonomy and Indigenous and decolonial conceptions of personhood, it defines relational autonomy as the personal and social factors that allow individuals to take principled action to benefit their communities when applied to teacher education, relational autonomy helps us understand that good teachers are those who ably support students while transmitting a love of learning, an ethic of care, and a sense of responsibility. The article summarizes the strengths of relational autonomy. The article concludes by discussing how relational autonomy might enrich and decolonize efforts to conceptualize, administer, and evaluate teacher preparation programs going forward.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".