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Record W1852620369 · doi:10.24908/ss.v5i3.3427

Re-Thinking Citizenship: (Un)Healthy Bodies and the Canadian Borde

2002· article· en· W1852620369 on OpenAlexaffabout
Sarah Marie Wiebe

Bibliographic record

VenueSurveillance & Society · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBiopowerCitizenshipImmigrationPolitical subjectivityPoliticsAgency (philosophy)SubjectivityConceptualizationSociologyState (computer science)Corporate governanceLegislatureLawPolitical scienceEnvironmental ethicsSocial scienceGender studiesEpistemology

Abstract

fetched live from OpenAlex

The Canadian state screens potential citizens based on their physical and mental health in order to assess individuals' likelihood of becoming contributive and productive members of Canadian society. Immigrants are not only screened as potential security risks in a traditional sense, but appear in Canadian discourse as threats to economic stability. These potential citizens are consequently screened and surveilled for health concerns. This essay examines these screening practices from a critical political science approach using Foucault's theory of biopolitics to evaluate the correlation between biopolitics – the governance of life – and immigration by focusing on Citizenship and Immigration (CIC) Canada's policy and legislative discourse. This essay argues that Canadian modern political subjectivity is predicated on the notion that citizens must be healthy in order to be truly political and to have political voice and agency. Finally, the essay calls for a re-conceptualization of the category of "citizen" in the modern Canadian state.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.866
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.039
Scholarly communication0.0140.004
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.023
GPT teacher head0.266
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2002
Admission routes2
Has abstractyes

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