Unveiling Voices and Empowering Narratives: A Comprehensive Exploration of Islamic Feminism in Marjane Satrapi's Persepolis
Bibliographic record
Abstract
This literature paper delves into the intricate layers of Islamic feminism within Marjane Satrapi's graphic novel Persepolis. The narrative unfolds against the backdrop of post-revolutionary Iran, providing a nuanced examination of the lives of Iranian women amid political and social transformations. Through a thorough analysis of female characters, with a focus on Marjane's experiences and those of her counterparts, the paper explores instances of resistance and agency as women navigate societal expectations. The concept of Islamic Feminism is introduced and contextualized, tracing its evolution, key principles, and objectives, while highlighting its role in challenging traditional gender norms within Islamic values. The historical and cultural background of Iran during the depicted period, encompassing the Iranian Revolution and its aftermath, sets the stage for feminist discourse.Examining specific scenes and dialogues, the paper identifies and analyses elements in the narrative that reflect Islamic Feminist ideas, illustrating how Satrapi skilfully navigates the intersection of feminism and Islamic culture. Challenges and criticisms surrounding the application of the Islamic Feminism label to Persepolis are addressed, considering perspectives from both proponents and sceptics. The study concludes by discussing the potential impact of Persepolis on readers' understanding of Islamic Feminism and its broader contribution to conversations about feminism within Islamic contexts. Through a comprehensive examination, it highlights the significance of embracing diverse perspectives and employing dynamic approaches to comprehend the complexities of women's experiences within the Islamic context. By integrating ijtihad and pluralist, liberal-rationalist, and contextual approaches, it aims to unveil voices and empower narratives, ultimately fostering gender equality and justice for all. This abstract encapsulates the essence of the findings, offering insights into the multifaceted nature of Islamic feminism as pictured in Persepolis.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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 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".