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Record W7133055095

Growing as English Language Teachers: A Case Study of International Graduate Students in Toronto

2025· dissertation· W7133055095 on OpenAlexaffabout
Wenyangzi Shi

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsVector Institute
Fundersnot available
KeywordsConstruct (python library)Identity (music)IntersectionalityNegotiationFocus groupPower (physics)Discourse analysisQualitative researchPoliticsEnglish language
DOInot available

Abstract

fetched live from OpenAlex

This qualitative case study explores how international graduate students (IGSs) who use and intend to teach English as an additional language construct their language teacher identity (LTI) in language teacher education (LTE) or related programs in Toronto. The study examines how intersecting personal and social identities influence IGSs’ LTI development and how they incorporate their own and their students’ identities into their teaching. It aims to illustrate how LTE programs can help IGSs optimize their identities to construct their desired LTIs and design identity-oriented pedagogies that meet diverse student demands.Framed by the frameworks of intersectionality and identity as pedagogy, the study sheds light on how IGSs’ identities are shaped by various social categories and power dynamics. These frameworks reveal the potential of IGSs to challenge marginalizing discourses and transform conventional language teaching practices. I collected data from nine IGSs at different stages of their studies through autobiographical descriptions, semi-structured and focus group interviews, participant-produced artifacts, and observations. The findings highlight the complex impact of IGSs’ diverse experiences across personal, interpersonal, and institutional levels on their LTI construction. Their professional aspirations, pedagogical practices, and perceptions of teacher responsibility are shaped by their personal traits, interactions with key stakeholders, and engagement with institutional policies and power structures. The findings suggest that a range of intersecting identities, beyond linguistic identity, have contributed to LTI development, sometimes aligning harmoniously, but often requiring ongoing negotiation and adaptation. IGSs actively incorporated their own and their students’ diverse identities into teaching through strategies like using authentic materials. However, they faced external (e.g., political narratives) and internal constraints (e.g., limited understanding of diverse student populations). These barriers complicated the implementation of identity-focused pedagogies, yet participants remained committed to leveraging identities as pedagogical resources. Participants selected their programs for their alignment with professional goals and Canada's multicultural environment. While they appreciated program support, they reported academic, professional, and personal challenges encountered during their studies. As a result, they advocated for more resources to help IGSs navigate these challenges and grow as English language teachers. The thesis concludes with methodological, theoretical, and pedagogical implications, with recommendations for future research.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.860

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0250.012
Scholarly communication0.0050.002
Open science0.0030.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.068
GPT teacher head0.556
Teacher spread0.488 · 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
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

Citations0
Published2025
Admission routes2
Has abstractyes

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