Punishing Survivors and Criminalizing Survivorship: A Feminist Intersectional Approach to Migrant Justice in the Crimmigration System
Bibliographic record
Abstract
Scholars have identified crimmigration – or the criminalization of “irregular” migration in law – as a key issue affecting migrant access to justice in contemporary immigrant-receiving societies. Yet the gendered and racialized implications of crimmigration for diverse migrant populations remains underdeveloped in this literature. This study advances a feminist intersectional approach to crimmigration and migrant justice in Canada. I add to recent research showing how punitive immigration controls disproportionately affect racialized men from the global south, constituting what Golash-Boza and Hondagneu-Sotelo have called a “gendered racial removal program” (2013). In my study, I shift analytical attention to consider the effects of the contemporary crimmigration system on migrant women survivors of gender-based violence. While such cases constitute a small sub-group within a larger population of migrants in detention, nevertheless scholarly attention to this group can expose the multiple axes along which state power is enacted – an analytical strategy that foundational scholars like Crenshaw (1991) used to theorize “structural intersectionality” in the US. In focusing on crimmigration in the Canadian context, I draw attention to the growing nexus between migration, security, and gender-based violence that has emerged alongside other processes of crimmigration. I then provide a case analysis of the 2013 death while in custody of Lucía Dominga Vega Jiménez, an “undocumented” migrant woman from Mexico. My analysis illustrates how migrant women’s strategies to survive gender-based violence are re-cast as grounds for their detention and removal, constituting what I argue is a criminalization of survivorship.The research overall demonstrates the centrality of gendered and racialized structural violence in crimmigration processes by challenging more universalist approaches to migrant justice.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".