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Record W2899884404

How to Accumulate National Capital: The Case of the “Good” Muslim

2009· article· en· W2899884404 on OpenAlexaboutno aff
Krista Riley

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCapital (architecture)EconomicsPolitical scienceHistoryAncient history
DOInot available

Abstract

fetched live from OpenAlex

This paper explores the practices of certain high-profile Canadian Muslims who call themselves “progressive” or “moderate” as an example of attempts to increase one’s claims to national belonging through a reification of tropes that designate many Muslims as fanatical, scary and a threat to the Canadian nation. Through tracing the different understandings of “Muslim” and “Canadian” identities and an examination of articles printed in The National Post, this paper argues that this accumulation occurs in three main ways, with portrayals of the “good” Muslim as a patriotic Canadian, as an object of threat from other Muslims and as a protector of oppressed Muslim women. However, in a context marked by rampant Islamophobia throughout Canadian society, these nationalist practices may do more to produce further racialisation of and violence towards those that they positioned as “bad” Muslims than to ensure any lasting claims to national belonging for those who assert themselves to be representative of the “good” Muslims.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.169
GPT teacher head0.475
Teacher spread0.306 · 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 teacher head, not a consensus.

Study designObservational
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

Citations20
Published2009
Admission routes1
Has abstractyes

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