Across seven seas, I followed you here: Caste, marriage migration and multiculturalism in the Indian diaspora
Bibliographic record
Abstract
This dissertation explores the experiences of marriage migrant women from India to Canada in relation to migration policies and changing expectations of education, employment, and domestic and care labour. I engage with the narratives of twenty-four Indian marriage migrant women who arrived in Canada as international students, economic immigrants or as spouses of economic immigrants. Using an intersectional and transnational feminist lens, I unpack their complicated agency in decision-making processes around marriage and migration to Canada, inflected by structures and processes of caste, class, race and gender. Neoliberal and Canadian multicultural discourses consider these twenty-four mostly Hindu, Telugu-speaking, middle-class and upper-caste women as the new Indian woman, model minority and designer migrants. However, I put these discourses in tension with the challenges presented to the women by the Canadian immigration system and the pressures they face in navigating conjugal, familial, community, and caste norms. I further this analysis with multi-sited and mixed methods, using interviews with bridal grooming schools and critical engagement with diasporic pageant competitions for married women, and media and cultural portrayals of marriage migration.\nThis dissertation further examines caste practices in the Indian diaspora in Canada to understand the intersection of race, caste, class and gender across the transnational space of India, Canada and the Indian diaspora, and the replication of caste discourses in the practices of diasporic communities at various levels domestic, professional, and at the community level. I argue that the horizontal culturalization of racism within Canadian multiculturalism, in conjunction with an understanding of caste as cultural practice rather than a hierarchical structure, enables a particular privileged configuration of Indian economic immigrants to assume the model minority mantle within Canadian society.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.042 | 0.015 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".