Creating Inclusive Classrooms Using Postcolonial and Culturally Relevant Literacy
Bibliographic record
Abstract
This article provides an interesting look at how a group of South Asian Canadian young women take up issues of identity, identities, and identification as they interact with texts by racialized Canadian authors. When texts written by Canadian authors who also define themselves as belonging to ethnic minority groups (such as Dionne Brand, Wayson Choy, Joy Kogawa, Rohinton Mistry, and Shyam Selvadurai) are seen by Canadian high school students as novelty items, boring reads, or books which incite shame or embarrassment, it is critical that we as educators reconsider our role and influence on the reading experiences of students. To bring marginalized, racialized, and silenced Canadian stories into the centre of our literacy teaching demands responsible and purposeful disruption of familiar teaching methods, privileged curricula, and normalized learning structures. Through research with South Asian Canadian adolescent girls, it became evident that culturally relevant curricula and culturally responsive teaching were key to their engagement, inclusion and development of identity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".