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Record W3102414796 · doi:10.1093/socpro/spaa046

Assembling the Local Politics of Noncitizenship: Contesting Access to Healthcare in Toronto-Sanctuary City

2020· article· en· W3102414796 on OpenAlexaffabout
Patricia Landolt

Bibliographic record

VenueSocial Problems · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitizenshipPoliticsDiscretionHealth careState (computer science)SociologyNarrativePolitical scienceImmigrationGender studiesPublic administrationLaw

Abstract

fetched live from OpenAlex

Abstract The article presents a case study of precarious noncitizen healthcare politics based on participant observation and interviews conducted between 2009 and 2012, as well as on documentary evidence collected during this period and up to 2016. It examines how state regulations, social networks, cultural narratives, and discretion come together to assemble the terms of access to healthcare for migrant noncitizens. Analysis shows how local contestation over healthcare policies, procedures and delivery practices contribute to the production of the formal and substantive boundaries between and within citizenship and noncitizenship. The case study identifies how precarious legal status and illegality inform the regulatory incongruencies and discursive fragility of Canada’s liberal welcome for newcomers. It contributes to specifying the conceptual terrain of contemporary battles over the terms of membership for migrant noncitizens in the Global North.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0200.015
Scholarly communication0.0040.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.235
GPT teacher head0.471
Teacher spread0.236 · 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 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

Citations14
Published2020
Admission routes2
Has abstractyes

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