Indigenous Education, Relational Pedagogy, and Autobiographical Narrative Inquiry: A Reflective Journey of Teaching Teachers
Bibliographic record
Abstract
Abstract In this chapter, we explore our experiences of co-teaching an undergraduate elementary teacher education class titled, “Teaching Language Arts in FNMI (First Nations, Métis and Inuit) Contexts.” In our curriculum-making for the course, we drew on Narrative Inquiry as pedagogy, as well as on Indigenous storybooks, novels, and scholarship. We chose to work in these ways so that we might attempt to complicate and enrich both our experiences as teacher educators, and the possibilities of what it means to engage in Language Arts alongside Indigenous children, youth, and families in Kindergarten through Grade 12 classrooms. Thus, central to this chapter will be reflection on our efforts to co-create curriculum alongside of students – considered in their multiplicity also as pre-service teachers, mothers, fathers, brothers, sisters, daughters, sons, etc. – in ways that honored all of our knowing and experience. The relational practices inherent to Narrative Inquiry and Indigenous approaches to education, such as the creation and sharing of personal annals/timelines and narratives, along with small and large group conversations and talking circles are pedagogies we hoped would invite safe, reflective, and communal spaces for conversation. While certainly not a tension-free process, all of the pedagogical choices we made as teacher educators provide us the opportunity to attend to the relational and ontological commitments of Narrative Inquiry, to the students in their processes of becoming, to Indigenous worldviews, and to the responsibilities of the Alberta Language Arts curriculum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.053 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".