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Record W3092013773 · doi:10.1080/13504630.2020.1814718

The construction of national and religious identities amongst Australian Isma’ili Muslims

2020· article· en· W3092013773 on OpenAlexaff
Karim Mitha, Shelina Adatia, Rusi Jaspal

Bibliographic record

VenueSocial Identities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMulticulturalismSociologyIdentity (music)Gender studiesReligious identityEthnic groupIslamophobiaIslamNarrativePoliticsNational identityMedia studiesPolitical scienceSocial scienceLawNegotiationAnthropologyGeographyAesthetics

Abstract

fetched live from OpenAlex

Australian civic society has become increasingly multicultural and diverse. Nevertheless, in the current political climate, Australian Muslims may feel as though they live under a microscope of scrutiny with their sense of affiliation and allegiance questioned. The narrative regarding Muslims in Australia has largely focused on Sunnis and ethnic Arabs. This qualitative study examines the Australian Shi’a Isma’ili Muslim community – a minority within a minority – and how attachment to supraordinate identity markers of ‘Muslim’ and ‘Australian’ influence their identity construction. It utilised semi-structured interviews with 16 first- and second-generation Isma’ili Muslims to examine the intersection of national, religious, and cultural identities via the lens of Identity Process Theory (IPT). Religious identity was important to respondents, who spoke of how their ‘double minority’ status distinguished them vis-à-vis the broader Muslim community in Australia and Australian society overall. Nevertheless, respondents noted a strong sense of instrumental attachment to Australia which enabled them to develop a distinct niche of Isma’ili Muslim identity unique to the Australian landscape.

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)0.003
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0020.001
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.297
Teacher spread0.258 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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