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Record W7161956034 · doi:10.82308/32300

Contesting citizenship and faith: Muslim claims-making in Canada and the United States, 2001-2008

2011· dissertation· en· W7161956034 on OpenAlexaboutno aff
Sara N. Amin

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipIdeologyPoliticsFaithNarrativeIdentity (music)Collective identityNational identity

Abstract

fetched live from OpenAlex

This study analyzes the claims-making and counter-claims-making on citizenship and faith by American and Canadian Muslim political actors over the 2001-2008 period. It highlights the interactive processes by which competing discourses on citizenship and faith are negotiated to produce divergent constructions of Muslim citizenship: mainstream, liberal, secular, and progressive. Utilizing insights from theories of citizenship, collective identity and social movements, I show how divergent collective identities are produced within the same categorical group through complex interactions between: a) ideological baggage and biographies of claims-makers; b) demographic patterns of communities; c) historical tensions in the traditions and identities that are being negotiated; and d) the actual political constellations, both proximate and durable, in which such claims and counter-claims are being made. Moreover, such contests about collective identity, citizenship and faith are not only relevant for the group (American Muslim or Canadian Muslim), but also help highlight the inclusions, exclusions and blindspots in national narratives about belonging and hierarchies of obligations and how these are challenged.

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)0.007
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 score0.163
Threshold uncertainty score0.970

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0270.008
Scholarly communication0.0070.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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