Beyond binaries: Negotiating the diasporic “queer Muslim woman” in the memoirs of Samra Habib and Lamya H.
Bibliographic record
Abstract
This study contributes to the growing body of literature on the intersections of migration and queerness by investigating how queer Muslim women from Pakistan negotiate with religion, queer desire, and belonging in transnational spaces. Two memoirs by queer Muslim women—We Have Always Been Here (2019) by Samra Habib and Hijab Butch Blues (2023) by Lamya H.—not only map their authors’ journeys across geographical borders but also trace the realization, exploration, and assertion of their queer identities. By engaging with these two texts, this paper analyzes Samra and Lamya’s journeys, as they try to exercise and make sense of their agency (or lack thereof) with respect to their cultural and geographical displacement. This analysis highlights how the position of queer Muslim women in the diaspora both enables and challenges queerness. In addition, this analysis underscores subjective approaches to reconciling religion with queerness and emphasizes the significance of such life narratives for fostering intersectional polylogues on sexuality, religion, and migration. Consequently, this paper contributes to the project of Queer Worldmaking by showing how queer Muslim women create communities, support networks, and exhibit resilience by challenging conventional hierarchies to develop viable life possibilities for themselves in Canada and the United States.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.027 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".