Internalized Misogyny: A Transnational Exploration of Select Literary Narratives
Bibliographic record
Abstract
Patriarchy is a pervasive global phenomenon, that creates social, cultural and political disparities and perpetuates gender inequality, discrimination and bias. It is deeply embedded in various discourses of human civilization, operating through both identifiable and unidentifiable mechanisms. Internalized misogyny, many a time is a subtle apparatus that manifests and maintains patriarchy and gender inequality. Identifying internalized misogyny is a complex task owing to the fact that its practices are often legitimized and internalized by women, thus making it unrecognized. Periodically, when overt structures of patriarchal hegemonies are criticized, the covert means of hegemonic functioning, particularly internalized misogyny remains underrepresented and uncritiqued. Thus, addressing the problem of internalized misogyny is the need of the hour. This study adopts two literary narratives namely, The Bonesetter’s Daughter by Amy Tan and Idris: Keeper of the Light by Anita Nair for the ongoing discussion on internalized misogyny. The Bonesetter’s Daughter by Amy Tan inquire into multigenerational reverberations of internalized misogyny, through the traction of mothers and daughters impelling Chinese traditions and gender roles upon themselves and other women around them. Idris: Keeper of the Light by Anita Nair clasps the reader’s attention towards 17th Century India and how the female characters grapples with societal norms that incarcerate them into subservient roles. Hence, this proposed paper provides a comprehensive analysis of the select works to identify and examine the discourse of internalized misogyny, that perpetuates gender inequality. By scrutinizing both works, this paper divulges into the omnipresent nature of internalized misogyny irrespective of contrasting historical and cultural contexts.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 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".