Ethical wayfinding in decolonizing child and youth care education
Bibliographic record
Abstract
In response to the Calls to Action from the Truth and Reconciliation Commission (2015), post-secondary institutions across Canada are attempting to decolonize and Indigenize their pedagogies and curriculum, while also grappling with the ongoing colonial nature of education. This dissertation is motivated by my own experiences of being unsettled by my complicity in the reproduction of settler colonialism within Child and Youth Care (CYC) education. Utilizing wayfinding as methodology, I offer accounts of my attempts to navigate the material-discursive landscapes of decolonizing CYC education, my own ethical entanglements in my daily practice as a CYC educator, and my actions and intentions toward decolonizing my field of praxis. Reading posthumanist and Indigenous philosophies in conversation with each other, I examine the ways coloniality is deeply embedded in the CYC curriculum, and how posthumanist and Indigenous philosophies can work together in support of decolonizing CYC education. Through this process, I hope to invite readers into their own wayfinding journeys within decolonizing CYC education in ways that resist stability and certainty, and emphasize instead the urgency, possibility, and agency of our individual and collective responsibilities in decolonizing education.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.110 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".