Bureaucratic Emotionalities: Managing Files, Forms, and Delays in the Canadian Spousal Reunification Process
Bibliographic record
Abstract
Based on an ethnographic study of Canadian women’s intimate relationships with a racialized man from the Global South, this article focuses on their experiences of the spousal reunification process. More specifically, I examine how the women emotionally and materially engage with spousal reunification procedures and administrative temporalities and how interactions with the Canadian immigration bureaucracy affect their subjectivity as women and citizens. I look at three embodied modes of involvement with bureaucratic procedures—waiting, working and fighting—each bringing forth its own set of emotions and creative coping strategies. I argue that love is central to the experience of the administrative procedures, as an ideological and technological tool used both by the state to regulate and discredit non-desirable relationships and by applicants to make sense of their position (of vulnerability) and to create meaningful narratives within state-imposed categories. A form of defensive agency emerges in women whose enormous application files, filled with “proof” of the authenticity of their relationship, shows how they have endorsed social anxieties about North-South intimacies and the strategies they have developed in order to legitimize their union.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.028 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".