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Record W4229045151 · doi:10.1177/00377686221090786

When sharing religion is not enough: A transregional perspective on marriage, piety, and the intersecting scales of identity transmission among female converts to Islam in mixed unions

2022· article· en· W4229045151 on OpenAlexafffundabout
Géraldine Mossière

Bibliographic record

VenueSocial Compass · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIslamPietyIdentity (music)SociologyNegotiationContext (archaeology)Gender studiesIdentity negotiationArticulation (sociology)Ethnic groupPolitical scienceLawAnthropologySocial scienceTheologyPolitics

Abstract

fetched live from OpenAlex

Drawing on fieldwork conducted among converts to Islam (France and Quebec), this article focuses on women who are in unions with partners of Muslim background. As these women commit to make a union based on shared religious identity, they face the double challenge of learning to be a Muslim and of transmitting identity to the children. Addressing these issues opens a space of ongoing negotiations within the couple (sometimes involving the in-laws) over the definition of the ‘authentic’ Islam, and the articulation between religion and ethnicity. These conjugal debates create new areas of mixedness through women’s own identification processes as Muslim and French or Quebecois. This negotiation is framed by the social and cultural capital each partner is granted in their specific context of living, including experiences of having minority status, as well as by the specific representations each partner draws on the ethnicity and space of origin of the other.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.216
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0280.027
Scholarly communication0.0110.005
Open science0.0020.008
Research integrity0.0020.004
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 head0.095
GPT teacher head0.389
Teacher spread0.294 · 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

Citations2
Published2022
Admission routes3
Has abstractyes

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