MétaCan
Menu
Back to cohort
Record W4400451808 · doi:10.1002/casp.2840

Health citizenship reveals ‘extra’ work managing biopolitical risk for immigrants in <scp>Canada</scp> during <scp>COVID</scp> ‐19: <scp>A</scp> qualitative study

2024· article· en· W4400451808 on OpenAlexafffundabout
Doris Leung, Sepali Guruge, Angel Wang, C. M. Lee

Bibliographic record

VenueJournal of Community & Applied Social Psychology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsToronto Metropolitan University
FundersToronto Metropolitan University
KeywordsCitizenshipPublic healthQualitative researchImmigrationSociologyPolitical sciencePublic relationsSocial psychologyPsychologyMedicinePoliticsSocial scienceNursing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.112
GPT teacher head0.480
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Community & Applied Social PsychologySame topicEmployment and Welfare StudiesFrench-language works237,207