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Record W3118291292 · doi:10.1086/710157

Language Use and Islamic Practices in Multilingual Europe

2020· article· en· W3118291292 on OpenAlex
Shahzaman Haque

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSigns and Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsIslamUrduSociolinguisticsArabicImmigrationQuarter (Canadian coin)SociologyLinguisticsFocus (optics)Gender studiesPolitical scienceHistoryLaw

Abstract

fetched live from OpenAlex

Abstract This article draws on fieldwork conducted into the linguistic practices of religious languages by three Muslim individuals in the Nordic countries and the Netherlands. All informants or their ancestors in the study were born in the Muslim quarter of the Indian sub-continent, with the exception of one informant who hails from Suriname. Few works (Schor 1985; Haque 2012, 2014; Zolberg and Woon 1999) in sociolinguistics focus on the practice of Islam by immigrants in their daily lives, where a plethora of languages are used for different functions. As a field of social inquiry, there is also an attempt to understand the role or impact of religion in the immigrant’s life as a practicing Muslim. The findings suggest that Arabic remains the principal liturgical language for prayers, while Urdu was rendered as a sanctified language for many believers, as literature on Islamic teaching is widely available in this language.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.375
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.137
GPT teacher head0.456
Teacher spread0.318 · 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