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Record W4391617001 · doi:10.32920/25166666

The Iconic Muslim Superhero: Muslim Female Audience Perspectives of Marvel’s Muslim Superheroines

2024· preprint· en· W4391617001 on OpenAlexaff
Safiyya Hosein

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsToronto Metropolitan UniversityCentre for Social InnovationYork University
Fundersnot available
KeywordsIslamMuslim communityArtAestheticsMuslim worldLiteratureSociologyPhilosophyTheology

Abstract

fetched live from OpenAlex

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 Ms. Marvel comic series, ending with a discussion for the potential of both these gendered representations in my Conclusion. 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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0110.006
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.030
GPT teacher head0.250
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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