Illuminating beginning teachers' ways of being and thinking to create decolonizing and indigenizing learning spaces
Bibliographic record
Abstract
In a pivotal time of education transformation in the Canadian Truth and Reconciliation Era, there is a need for literature to inform teacher educators how pre-service teachers see and articulate the ways they take up thought and actions to decolonize and Indigenize learning spaces, in Turtle Island north. This lack of information can impact how teacher educators plan for their majority non-Indigenous teacher candidates and allow for assumptions which limit possibilities for decolonizing and Indigenizing teacher education. Through the worldview of a non-Indigenous educator, this dissertation asks how pre-service teachers talk about/name their creation of spaces for knowing, learning and being. It is contextualized in the place where the whole, interconnected Syilx Okanagan ways of knowing and being intersect with fragmented Anglo-Eurocentric ways of understanding and being in the world. I use a dialogic focus group format, informed by Syilx Pedagogy and by the dialogic work of Paulo Freire. Aligned with decolonizing curriculum theory, the process engages participants with provocations and evocations involving: the settler view of Syilx Indigenous Knowledge, participant and researcher experiences, and collective threads of understanding. Guided by the key tenets of researcher positionality, reflexivity, and accountability, I gathered and analyzed data which reveal key dialogic moments of beginning educators’ decolonizing and Indigenizing thought and praxis. Opening onto insights to inform teacher education, the findings highlight that teacher candidates in place embody a sense of urgency to transform their ways of knowing and being while seeking to grasp the expanse of their teacher agency to do their transforming work. They demonstrate a relationally accountable orientation to their current and future students. Aware of decolonizing pedagogy, they tend to prioritize making space for the interconnectedness of students, Indigenous Knowledge, and learning. Teacher candidates grapple with seeking acceptance of self as settler and getting past settler shame. They engage in a mental dance of process-as-Indigenizing and content-as-Indigenizing, alongside a continuous psychological struggle with/against fear of tokenization. Teacher candidates understand their transformative educator role as deconstructing and reconstructing Canada’s history while practicing Indigenous, Syilx-informed processes in a protocol-abiding way. The insights open onto implications and contributions toward ongoing teacher education reform.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.034 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".