Collaborative Pedagogies: Seeking and Finding Truth Within Indigenous Children’s Literature Through Multiliteracies
Bibliographic record
Abstract
Abstract In this chapter, we highlight the work of two teachers as they engaged in collaborative practice while designing a curriculum that incorporated Indigenous perspectives and ways of knowing through a multiliteracies approach. We describe how these teachers used postcolonial Indigenous children’s literature as a launching point to explore historical and critical issues of Indigenous peoples with their students in an elementary classroom. We use data generated from interviews, focus group discussions, children’s drawings, journal writings, and photographs of classroom sessions. Using a multiliteracies pedagogical framework (situated practice, overt instruction, critical framing, and transformative practice), we show how these teachers transformed their practice and students’ understandings as they participated in learning events together. We also share some possible practices for incorporating Indigenous perspectives and ways of knowing into elementary classrooms. In conclusion, we discuss implications for teachers’ practice and the need for further research as we continue the important work towards truth and reconciliation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".