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Record W2111465989 · doi:10.5539/elt.v6n10p32

The Impact of Canadian Social Discourses on L2 Writing Pedagogy in Ontario

2013· article· en· W2111465989 on OpenAlexaffvenueabout
Amir Kalan

Bibliographic record

VenueEnglish Language Teaching · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsPedagogySecond language writingRhetoricSociocultural evolutionPoliticsCreativitySociologyPopularityMulticulturalismPsychologyLinguisticsSocial psychologySecond languagePolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.306
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes3
Has abstractyes

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