The Impact of Canadian Social Discourses on L2 Writing Pedagogy in Ontario
Bibliographic record
Abstract
This paper attempts to illustrate the impact of Canadian social, political, and academic discourses on second language writing pedagogy in Ontario schools. Building upon the views that regard teacher knowledge as teachers’ sociocultural interactions and lived experiences, and not merely intellectual capabilities gained within teacher preparation, this article proposes that the impact of dominant social discourses on classroom practice might be more profound than teachers’ creativity and initiative. This idea is demonstrated by examining the findings of a grounded theory study of frequently employed strategies that can deal with intercultural rhetoric in EAL (English as an additional language) academic writing. Guided by Foucauldian critical discourse analysis, this article approaches the experiences of five Ontario EAL teachers with intercultural rhetoric in order to show the significance of the influence of dominant Canadian social discourses on their practice. This report, in particular, explores possible connections between the popularity of strategies that employ students’ first languages in EAL academic writing and dominant social, political, and academic discourses in Canada over the past 50 years. This paper, finally, poses questions about the future of EAL writing pedagogy as anti-multiculturalism discourses gain more dominance in Canada.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.049 | 0.018 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".