Embodied global flows : immigration and transnational networks between British Columbia, Canada, and Punjab, India
Bibliographic record
Abstract
Canadian politicians have stated that India-Canada relations are grounded in "people-to-people links". These links have been formed over the last century through a process of immigration that articulates specific regions of India—Doaba in Punjab—with particular regions of Canada—initially British Columbia, and now the metropolitan areas of Toronto and Vancouver. Employing the theoretical lens of transnationalism and a methodological approach based on networks, this thesis argues that the presence of extensive transnational linkages connecting immigrants to their sites of origin, rather than limit national Canadian citizenship practice, can actually enhance it. I examine how Punjabi immigrants activate linkages that span borders and fuse distant communities and localities, as well as highlighting how the state is involved in the regulation and monitoring of such connections. My findings indicate that the operation of state officials varies according to the nature of the exchange. Whereas immigration is differentially controlled at the micro-scale of the individual according to a range of factors such as race, class and gender; inanimate objects such as goods and capital are less regulated, despite the significant material effects associated with their transmission. Indian immigrants are not however, passive recipients of state regulation at the scale of the individual, and instead emerge as active participants in a Canadian democratic system that enables the individual to challenge certain bureaucratic decisions and hold federal departments accountable. In addition, contrary to ideas of transnational immigrant actors possessing new forms of transnational or "post-national" citizenship, this research suggests that immigrants value the traditional right of citizenship to protect national borders and determine who may gain access.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".