MétaCan
Menu
Back to cohort
Record W4412520372 · doi:10.1080/10894160.2025.2535187

Beyond binaries: Negotiating the diasporic “queer Muslim woman” in the memoirs of Samra Habib and Lamya H.

2025· article· en· W4412520372 on OpenAlexaboutno aff
Apeksha Pareek, Niraja Saraswat

Bibliographic record

VenueJournal of Lesbian Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Sexualities and LGBTQ+ Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMemoirQueerGender studiesNegotiationSociologyLesbianReligious studiesArtLiteraturePhilosophySocial science

Abstract

fetched live from OpenAlex

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.

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 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)0.002
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 score0.077
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.040
GPT teacher head0.373
Teacher spread0.332 · 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 teacher head, 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Lesbian StudiesSame topicAfrican Sexualities and LGBTQ+ IssuesFrench-language works237,207