Towards a critical translanguaging biliteracy pedagogy: the ‘aha moment’ stories of two Mandarin Chinese teachers in Canada
Bibliographic record
Abstract
Abstract Learning Mandarin Chinese as a heritage or additional language at Chinese complementary schools has long been a tradition for many Asian Canadians. However, research that looks at teachers' experiences and perceptions in Canadian settings, especially the power dynamics embedded in biliteracy development at complementary schools, is scant. Moreover, the COVID‐19 pandemic brought challenges and opportunities to Chinese complementary schools. In this paper, we, as two Mandarin teachers and literacy researchers, used collaborative autobiographical narrative inquiry to tell our stories to unfold (1) how power dynamics regarding biliteracy/multiliteracy were enacted and reflected in a Chinese complementary school during the pandemic and (2) our re‐understanding of Mandarin teaching and learning from critical literacy and translanguaging perspectives. Although the pandemic is over, racial discrimination and social inequity continue to remain in our lives. By analysing our teaching moments and reflections, we hope this study could provide some insights into how critical literacy and translanguaging can be integrated into language and literacy education in multilingual and multimodal settings in the pandemic and post‐pandemic contexts.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.063 | 0.031 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| 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".