Women undercover: exploring the intersectional identities of Muslim women through modest fashion
Bibliographic record
Abstract
Significant discrimination is directed toward Muslim women who dress modestly. Despite this Muslims will spend an estimated US$75 billion on modest fashion by 2020, a 70% increase since 2015. Past research in modest fashion has focused on influencers, the industry, or on veiling. Muslim women’s everyday dress practices and their lived experiences have not been studied. Through an intersectional framework, this research uses wardrobe interviews with sixteen Muslim women and digital storytelling with four of them to explore how they embody their identity through modest fashion, how intersectionality impacts their clothing choices, and what contexts influence their sartorial decisions. Three themes emerged: what influences their style; how they shop and style outfits; and what consequences are faced. My research found that by prioritizing modesty as a sartorial practice, these women are diverting the Western gaze, navigating away from superficial and oppressive Western beauty ideals, and challenging narrow Islamophobic stereotypes. Keywords: modesty, female modesty, sartorial agency, dressed bodies, fashion, hijab, Muslim, Islamophobia, intersectionality, fashion diversity, Western gaze, Orientalism
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".