Constructing categories of ‘desirable migrants’ through bureaucracy in French and Canadian mobility regimes
Bibliographic record
Abstract
This paper comparatively examines ‘highly skilled’ Vietnamese migrants’ encounters with the mobility regimes in France and Canada, through their experiences with immigration administrative procedures in these countries. We seek to highlight how categories of ‘desirable migrants’ are constructed through these bureaucratic encounters, by the policies and bureaucrats but also by migrants themselves. We draw from ethnographic interviews with 64 Vietnamese university-educated migrants, including a majority of international students and graduates. Our findings highlight participants’ experiences of France’s and Canada’s mobility regimes through administrative processes; as well as how participants position themselves with regards to their receiving country’s immigration bureaucracy. Participants in both countries performed as ‘desirable migrants’ through ‘competent management’ of their paperwork. In France, facing procedural injustices and suspicion, ‘highly skilled’ migrants also emphasised their lawfulness. In contrast, in Canada, they experienced more procedural justice and support afforded by their financial capital. Nevertheless, participants presented themselves as ‘desirable migrants’ by emphasising their thoughtfulness in facilitating smooth procedures and their ‘merit’ or ‘hard work’ in securing employer sponsorship and handling paperwork independently. This study enhances our comprehension of mobility regimes as being characterised by dynamic interplays between state policies and migrants’ performances shaping the formation of categories and norms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".