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Record W2840780434 · doi:10.1080/14616742.2018.1480901

Postnational acts of citizenship: how an anti-border politics is shaping feminist spaces of service provision in Toronto, Canada

2018· article· en· W2840780434 on OpenAlexafffundabout
Salina Abji

Bibliographic record

VenueInternational Feminist Journal of Politics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizenshipSolidaritySociologyPoliticsState (computer science)Gender studiesPower (physics)FeminismImmigrationLawPolitical science

Abstract

fetched live from OpenAlex

Postnationalism has seen a modest resurgence in recent years as both a theory of citizenship and as a set of claims frequently articulated by anti-border movements. Yet the implications of postnationalism for feminist politics remain relatively under-theorized. Using interviews with feminist advocates in Toronto, Canada, this research examines how postnational challenges to state power are being mobilized in spaces of service provision addressing gender-based violence. I show how, for some advocates, a postnational politics deeply informed their critiques of state borders and restrictive immigration controls as fundamental sources of gendered and racialized violence. However, postnational approaches were also limited in offering few concrete alternatives to state protection from domestic or interpersonal violence, particularly for women with precarious immigration status. Significantly, it was through advocates’ everyday practices of service provision that they blueprinted an alternative feminist ethics of solidarity. I argue that these practices constitute postnational acts of citizenship, in so far as they attempt – albeit imperfectly – to de-border institutional spaces from within.

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)0.004
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 score0.196
Threshold uncertainty score0.933

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0450.027
Scholarly communication0.0110.002
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.028
GPT teacher head0.360
Teacher spread0.332 · 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

Citations16
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueInternational Feminist Journal of PoliticsSame topicMigration, Refugees, and IntegrationFrench-language works237,207