Visible Muslims, Political Beings: The Racialized and Gendered Contours of a Digitally-Mediated Muslim Womanhood
Bibliographic record
Abstract
The purpose of this project is to examine how contemporary contexts of Islamophobia contribute to shaping notions and performances of Muslim womanhood. I center Muslim female social media influencers in my analysis and examine how they perform and (re)define Muslim womanhood through fashion, aesthetic labor, the hijab, and modest embodiment practices online. The specific research question that undergirds this project is, "How do contexts and discourses of Islamophobia contribute to shaping notions and performances of Muslim womanhood?" My data is derived from interviews with Muslimah social media influencers in the US, UK, and Canada; a survey with their social media followers, and a content analysis of their photo and video posts on Instagram and YouTube. Findings suggest that racialized and gendered expectations of Muslim womanhood emerge on the one hand, from the western non-Muslim community's racialized perceptions and understandings of Muslim women and Islam, and on the other, from the western Muslim community's reaction to its racialization in the global war on terror. The result of these expectations is the imposition of representational and moral responsibilities on Muslim women, who are regarded as visible and public representations of the Muslim community and of Islam as a faith. Findings also suggest that in response to the burden of these expectations, Muslim women exercise their agency to mobilize Islamic feminisms to their advantage in order to negotiate with, resist, and critique western Muslim and non-Muslim expectations of modesty, piety, empowerment, and the hijab. Consequently, Muslimah influencers are forcing western Muslim and non-Muslim communities to reevaluate their expectations of who fits within the category the 'Muslim Woman' while also opening up a discursive space for the possibility of new formulations and conceptualizations of Muslim womanhood that are more aligned with egalitarian Islamic feminist interpretations of Muslimah ways of living and being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.005 |
| 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".