From Gilead to Syria: A Comparative Study of Patriarchal Oppression and Resistance in Margaret Atwood's “The Handmaid's Tale” and Nagham Haider’s “Winter Festivals”
Bibliographic record
Abstract
This paper examines the influence of Margaret Atwood's concept of feminist dystopia on Nagham Haider's Winter Festivals. The main objective of the research is to explore how Haider's literary works, specifically her Winter Festivals, reflect Atwood's feminist dystopian vision. The study adopts Atwood’s approach of feminist dystopia as represented in The Handmaid's Tale to explore themes of gender oppression, objection of the female body, government control, and patriarchal power structures. In her novel, Haider draws heavily from Atwood's feminist dystopian vision, particularly in her exploration of the intersectional oppression faced by the women during the Syrian Civil War. Haider's novel portrays a society in which women are oppressed and denied agency and autonomy, which is a central concept in Margaret Atwood's feminist dystopia. It can be concluded that Nagham Hayder's Winter Festivals echoes Margaret Atwood's feminist dystopian theory in several ways. Both authors present patriarchal societies where women are oppressed and controlled, with women's bodies commodified and controlled by men. Both novels showcase governments exerting complete control over citizens through surveillance and propaganda. Additionally, they emphasize the significance of women's resistance and solidarity in the face of oppression. Winter Festivals' portrayal of a revolution against the Syrian regime and The Handmaid's Tale's depiction of Handmaid resistance show Hayder's apparent influence from Atwood's feminist dystopian ideas in her writing. Finally, this research contributes to the growing body of scholarship on feminist dystopian literature, shedding light on the global reach and impact of Atwood's vision, as well as the diverse ways in which feminist writers around the world adapt and re-imagine this powerful genre to reflect their unique experiences and perspectives.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.021 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".