Health citizenship reveals ‘extra’ work managing biopolitical risk for immigrants in <scp>Canada</scp> during <scp>COVID</scp> ‐19: <scp>A</scp> qualitative study
Bibliographic record
Abstract
Abstract One's health security (i.e., the ability to minimize risks and respond to public health threats) is a conferred right of citizenship but individuals construct identities during the process of securing their health. However, how this occurs, in relationship to the state, remains largely implicit or taken‐for‐granted. The Coronavirus Disease 2019 (COVID‐19)' provided a unique opportunity to explore the relationship between oneself and governing social norms of health citizenship. We drew on secondary analysis of data from a previous (published) qualitative descriptive study that was conducted during May to September 2020 of COVID‐19, to explore 72 immigrants' experience (from 21 countries) of health security in the Greater Toronto Area, Canada. Data were collected through semi‐structured interviews and analysed using critical realism. The majority of participants were women. We demonstrate how individuals implicitly engaged in ‘extra’ work—gendered and driven by mechanisms of good citizenship—connected to the will to health, against ethopolitical work to regulate risks, of and for themselves, in public discourse. Public discourse tended to follow racialized hegemonic norms, which also reproduced systemic cultural racism. We argue that empathetic understanding of this process is conducive to enhancing one's resistance to stereotypes, and to bolstering immigrants' resilience to seeking health security during public health emergencies.
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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 | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.007 |
| 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".