Teacher Identity as Pedagogy: Towards a Field-Internal Conceptualisation in Bilingual and Second Language Education
Bibliographic record
Abstract
This article explores the transformative potential of a teacher's identity in the context of bilingual and second language education (SLE) programmes. The first section examines several theoretical options by which this potential might be conceptualised. Drawing on post-structural notions of discourse, subjectivity and performativity, the author emphasises the contingent and relational processes through which teachers and students come to understand themselves and negotiate their varying roles in language classrooms. Simon's (1995) notion of an 'image-text' further develops this dynamic, co-constructed understanding and shifts it more specifically towards pedagogical applications: the strategic performance of a teacher's identity in ways that counteract stereotypes held by a particular group of students. These post-structural ideas on teachers' identities are then evaluated in reference to the knowledge base of bilingual and SLE. The author then proposes a 'fieldinternal' conceptualisation by which such theories might be rooted in the types of practices characteristic of language education programmes. The next section of the article describes the author's personal efforts to realise these concepts in practice. 'Gong Li – Brian's Imaginary Lover' is a story of how the author's identity became a classroom resource, a text to be performed in ways that challenged group assumptions around culture, gender, and family roles in a community, adult ESL programme serving mostly Chinese seniors in Toronto.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.049 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".