Pregnant and Precarious: Canadian Immigration through the Lens of Reproductive Justice
Bibliographic record
Abstract
In a context where migration has become a contentious global and national issue, and maternal health and reproductive rights continue to be leading priorities for the Canadian state, there is a disconnect between the ideals of Canadian exceptionalism and the discourses and policies surrounding reproductive rights for non-citizens. While legal rights protections for non-citizens have generally been expansive in many liberal democratic states, the politics governing reproductive rights, however, present a unique tension. In countries like Canada with jus soli citizenship, supporting a non-citizen who is giving birth is not simply about providing services, it’s also about formal membership. Given this, the reproductive rights of migrants are positioned against national sovereignty. A fuller account of reproductive citizenship as it intersects with immigration status is needed. In particular, there is a need for analysis that resists this positioning and takes seriously the realization of sexual and reproductive autonomy as a global human right. \n \nUsing reproductive justice as an analytic lens, this dissertation contributes to our empirical and theoretical knowledge of how reproductive citizenship is experienced by pregnant people with precarious immigration status. Drawing on 24 narrative interviews with temporary status and non-status women living in Montreal, Canada, 13 key informant interviews with service providers, and a review of relevant policies, this dissertation situates the lived experiences of pregnant precarious status migrants within Canadian immigration and reproductive politics. This analysis reveals how neoliberal notions of choice and the racialized and gendered practices of nation-building intersect in the lives of migrant pregnant people and argues that immigration status is barrier to reproductive justice. In particular, narrative interviews showed how immigration and reproduction strategies are often co-produced; however, who can access these strategies and how they are received when they do is shaped by nationality and highly racialized. Precarious immigration programs are not amenable to the needs of pregnant people, such that migration management on the part of the state is experienced as reproductive management in the lives of precarious status migrants. Specifically, they face challenges maintaining their status and accessing basic public services and protections as they navigate pregnancy, childbirth, and motherhood.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".