The Iconic Muslim Superhero: Muslim Female Audience Perspectives of Marvel’s Muslim Superheroines
Bibliographic record
Abstract
<p>This dissertation critiques the construction of the American Muslim female superhero where Muslim identity is treated as an intersectional identity. It incorporates critical race theory, postcolonial feminism, affect theory, audience studies, postfeminism, and feminist comic studies. While American Muslim superheroes have existed for many decades, their representation flourished during the War on Terror. I first position the Muslim female superhero in the current social and geopolitical context in the West by discussing the underpinnings of the imperialist project in her construction. In the process, I discuss the ways she emphasizes Western exceptionalism and white male saviorism; and its implications for Muslim masculinities by depicting them as savage oppressors of women in comics written by White, non-Muslim men. I examine the attempts of Muslim writers to rehabilitate these images in the <em>Ms. Marvel</em> comic series, ending with a discussion for the potential of both these gendered representations in my Conclusion.</p> <p>The field of Muslim audience studies has been overlooked in scholarship despite the increase in negative representations of Muslims in Western media. This study contributes to that understudied area with an audience study examining young adult female Muslim perspectives of three Muslim superheroines – Sooraya Qadir (Dust), Monet St. Croix (M), and Kamala Khan (Ms.Marvel). If we analyze the conditions of possibility that led to an influx of American Muslim superheroes during the War on Terror, it becomes clear that the Muslim superheroine has two functions. For dominant audiences, she alleviates white guilt when we consider the increase in state violence committed against Muslims during this war. But for Muslim audiences who are frustrated with Orientalist depictions of them, she provides relief from these depictions, making their reactions an affective phenomenon. Because participants viewed their religious identity in conjunction with their racial, sexual, gendered, and cultural identity, I provide a critique of Arab Muslim femininity through emphasizing Black, South Asian, and LGBTQ Muslim identity. Finally, I discuss gendered Muslim identity in superhero comics through analyses of Islamic wear as costumes, and class representations of Muslim men.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".