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Record W2111165957 · doi:10.1080/13621025.2012.667613

Constructions of migrant rights in Canada: is subnational citizenship possible?

2012· article· en· W2111165957 on OpenAlexaffabout
Rupaleem Bhuyan, Tracy Smith‐Carrier

Bibliographic record

VenueCitizenship Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCitizenshipSocial rightsPoliticsImmigrationPolitical sciencePublic administrationGovernment (linguistics)Boundary (topology)LawSociologyPolitical economy

Abstract

fetched live from OpenAlex

Devolutionary trends in immigration and social welfare policy have enabled different levels of government to define membership and confer rights to people residing within the political boundary of a province or municipality in ways that may contradict federal legal status. Drawing upon theories of postnational and deterritorialized citizenship, we examined the legal construction of social rights within federal, provincial, and municipal law in Toronto, Ontario. The study of these different policy arenas focuses on rights related to education, access to safety and police protection, and income assistance. Our analysis suggests that the interplay of intra-governmental laws produces an uneven terrain of social rights for people with precarious status. We argue that while provincial and municipal governments may rhetorically seek to advance the social rights of all people living within their territorial boundaries, program and funding guidelines ensure that national practices of market citizenship and the policing of non-citizen subjects are reproduced at local levels.

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)0.006
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 score0.216
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0360.022
Scholarly communication0.0090.003
Open science0.0020.006
Research integrity0.0010.003
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 head0.052
GPT teacher head0.318
Teacher spread0.266 · 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

Citations30
Published2012
Admission routes2
Has abstractyes

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