Negotiating Identities through Canadian Multicultural and Indigenous Picturebooks: A Collective Autobiographical Narrative Inquiry
Bibliographic record
Abstract
Canadian multicultural and Indigenous picturebooks greatly influence both children's and educators' being and becoming. Identity is closely related to our engagement with literacy practices, including book reading. In this paper, two researchers who immigrated from Mainland China engage in autobiographical narrative inquiry, a methodology that asks the researchers to self-face, and to "world"-travel to our earlier landscapes, times, places, experiences, and relationships. In personal, educational, and academic settings, we tell and retell our storied experiences of critically reading four multicultural and Indigenous Canadian picturebooks, to fight the hegemony of the Canadian dominant culture. Our article sheds light on the importance of negotiating one's identity in multicultural and Indigenous picturebooks, as little work presents minority educators' and adult newcomers' voices of reading diverse Canadian picturebooks. By making visible our critical reading experiences, this inquiry opens space to maximize the outcomes of utilizing children's literature in teaching and learning.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.031 | 0.023 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| 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".