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Record W2247138475 · doi:10.82308/5665

Critical pedagogy in the ELT Industry: can a socially responsible curriculum find its place in a corporate culture?

2007· dissertation· en· W2247138475 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2007
Typedissertation
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumPedagogyFlexibility (engineering)Context (archaeology)Critical pedagogyMulticulturalismSociologyManagement

Abstract

fetched live from OpenAlex

This study qualitatively evaluated the adoption of critical approaches to teaching English as a second or foreign language (ESL) in the particular context of the private language school industry. The research questions focused on the flexibility of the curriculum, on the room it affords for critical pedagogy and on the challenges of implementing critical lesson plans in the ESL classroom. With the help of four teachers, I explored the practical implications of implementing critical lessons in multicultural ESL classrooms at a Canadian private language school. While the general conclusion of the teachers' experiences provides an encouraging and a positive outlook on a more generalized integration of critical pedagogy in the ELT curriculum, some of the challenges encountered included preparation time for lesson planning, addressing students' linguistic needs, and the tension between the business culture of the ELT industry and the principles of critical pedagogy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.021
Scholarly communication0.0100.007
Open science0.0010.008
Research integrity0.0020.003
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 head0.039
GPT teacher head0.321
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreOther

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

Citations9
Published2007
Admission routes1
Has abstractyes

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