Critically Engaged Language and Literacy Workshops as a Disruptive Pedagogy in Plurilingual Classrooms
Bibliographic record
Abstract
Abstract This study explored racialized newcomer student participants' experiences in a rural high school in Western Canada, and utilized critically engaged language and literacy workshops (CELLWs) as a means to authentically represent participants' interrelationships with and relatability to their school and community spaces. CELLWs are an important avenue for self‐reflection that fosters socially just, diverse, and equitable educational practices. Understanding the nuanced lived experiences of newcomers, and how these inform educational practices today, represents a pivotal need in the development of educational pedagogies that encompass past and present experiences reinforced within different places and spaces. The study was guided by the following question: To what extent can CELLWs afford multicultural and plurilingual identities to establish a disruptive pedagogy and re‐imagine classroom spaces? The researchers centered arts and walking methodologies within four CELLWs sessions to open up subjective practices and analyses that intersect equitable, inclusive, and diverse theories and participants' life experiences. Data was drawn from a qualitative and thematic analysis that was obtained from participants' artwork, written reflections, and individual/group interviews. The study revealed the importance of CELLWs in research and in‐classroom practices as practitioners and scholars become accountable when appropriating such activities to create spaces for meaning‐making processes that consider relevant personal experiences and feelings within schools and communities.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".