Transitions from Exile to Academia: Experiences and Identities of Refugee Women Teachers from the Former Yugoslavia
Bibliographic record
Abstract
Western academic literature frequently represents refugee women through the lens of deficit, particularly as powerless victims of war, rape, domestic violence, and mental disorder. This representation is, however, limited in scope and problematic in its colonising nature. This article explores the experiences of three refugee women teachers from the former Yugoslavia who immigrated to Ontario and Quebec during and after the Yugoslav wars (1991–1995) and whose narratives remain largely outside the master narrative of exile and settlement research. These women's stories challenge the image of a victimised and submissive refugee woman in the Canadian context and bring to the centre of the discourse the image of a refugee woman who is an aspiring academic. Through narrative inquiry, the ‘storying stories' model, transcript poems and personal narrative of the researcher this article explores the issues of gender, forced migrations, and academic identity.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".