Contours of becoming: an autoethnographic account of gender, race, and language in transnational teacher identities
Bibliographic record
Abstract
This study highlights peripheral identities on transnational gendered and racialized subjects in the ongoing negotiation in language education learning environments. The role of gendered and racialized language in shaping the often-invisible identities of transnational teachers in the heteronormative landscapes remains underexamined. In globalization, where transnationalism, multilingualism, and mobility intersect, questions of porous identity construction and expression across linguistic and cultural landscapes become increasingly urgent. Drawing on autoethnography through personal diary and self-narrative writing, this study combines inductive and deductive analysis to trace how both visible and invisible aspects of transnational teacher identity emerge. The findings position these identities as critical sites for cultivating gendered inclusion in English language classrooms. This study concludes by offering guidelines for a pedagogical intervention aimed at addressing the ongoing painful realities of internalized homophobia, impostor syndrome, and xenophobia, while promoting inclusive curricula. It also identifies future directions for language education research.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".