Bordering in Canadian Health Care: How the “Birth Tourism” Discourse Informs Claims of Deservingness of Health Coverage and Undermines the Right to Health
Bibliographic record
Abstract
This dissertation examines the discourse of “birth tourism” and notions of health-related deservingness in Canada. I used the concept of bordering to provide insight into how people deemed outsiders to a nation are socially excluded. The purpose of the research was to explore how deservingness is assessed in Canadian health care settings and how this shapes decision-making around eligibility for health coverage. The questions guiding the research were: What constitutes the discourse of “birth tourism” in Canada and how is it mobilized in health care? How is the right to health “bordered” for people deemed undeserving of social and political membership? The point of departure for the study was instances of denial of health coverage registration to babies born to medically uninsured parents in Ontario hospitals. Negotiations around access to coverage between parents, their advocates, and hospital staff provided a unique opportunity through which to analyze broader questions of deservingness of social and political membership in Canada. To conduct the research, I used the discourse historical approach to critical discourse analysis to analyze newspaper articles, health policy documents, and 16 interviews with health care providers, administrators, and researchers. My analysis of the media revealed that “birth tourism” is an imaginary construct based on racist and xenophobic ideas about who has a right to social and political membership in Canada, who has a right to health care, and whose children have a right to citizenship. My analysis of the interview and document data showed that bordering of suspected “birth tourists” happens at the policy and administrative levels through four mechanisms: omission, devolution, obfuscation, and intimidation. Together, the research demonstrates that assessments of deservingness of health coverage are rooted in assessments of deservingness of social and political membership in Canada, which are in turn based in settler colonial and neoliberal ideologies. The unjust denial of access to health coverage threatens the realization of the right to health, marginalizing people deemed undeserving. Ultimately, my research offers a better understanding of how deservingness of citizenship and health care is discursively constituted so that exclusionary discourses and bordering practices can be reconceptualized and resisted.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.063 | 0.056 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".