The contested terrain of citizenship and exclusion in Canada: Sri Lankan women's narrative accaounts of school and social exclusion in the diaspora
Bibliographic record
Abstract
Research on the experiences of minority ethnic women tends to generalize across many nationalities. The experiences of Sri Lankan women are often regarded as similar to those of their South Asian counterparts. First and foremost, the aim of this project is to eradicate this problem by conceptualizing how social, cultural and structural power relations surrounding the marginalized voices of young Sri Lankan female immigrants become manifest in their personal accounts of the diaspora, and by revealing the forms of exclusion they attribute to such experiences in education and society. To achieve this purpose, the thesis recounts the migration, education and social experiences of five young women of Sri Lankan origin currently residing in Toronto, Canada, who have experienced the education systems and cultural contexts of both Sri Lanka and Canada. A number of themes relating to exclusion and gender are uncovered in these narrative accounts: the school and social experience in Sri Lanka and Canada; the ways in which such experiences expose something about the social order of the two nations; and notions of diaspora, citizenship, home, and nation. The ultimate aim, then, is to arrive at an understanding of how issues of exclusion and gender, through an examination of their expression in these women's narrative accounts, shape the social and educational experiences of young Sri Lankan female immigrants.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.020 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| 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".