Queer, Muslim, and Maghrebi: An Intersectional Analysis of Immigrant Identities in Contemporary France
Bibliographic record
Abstract
This study investigates the complex ways in which queer Muslim women with origins from the Middle East and North Africa (MENA) negotiate belonging and selfhood in France. Drawing on a three-month long digital ethnography, I employ an intersectional approach to explore the juxtaposition of “Muslim” and “lesbian/ bisexual” identities and to answer the question, “How do queer Muslim immigrant women negotiate and conceptualize their identities in contemporary France?” As a marginalized group within a marginalized minority of immigrants from the MENA region, queer Muslim immigrant women have been overlooked in scholarship, public discourses, politics, religious, LGBTQ+ spaces, and religious spaces. This research addresses this gap by exploring the identity-related struggles of queer Muslim immigrant women in France and contributes to studies on Muslim subjectivities, immigration, and gender. Based on my findings, I argue that queer Muslim immigrant women in France negotiate their identities through reconfiguring “secular” and “Muslim” identities and queering religious texts. This negotiation takes place, in part, by using social media to connect with others who share a similar conceptualization of their identities within digital spaces.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".