Defying Norms: A Contrapuntal Reading of Gender Performance in the works of Amy Tan and Anita Nair
Bibliographic record
Abstract
Gender is a complex universal discourse with culturally inherent dogmas and rigid social bias. Gender performativity, often framed in terms of masculinity and femininity, is frequently restricted by associations with biological sex. However, counter deliberations such as the notion of female masculinity challenges rigid gender role attributions of the conventional hegemonic structures, affirming the fact that the gender binaries addressed as ‘masculinity’ and ‘femininity’, is not specific to any particular biological or social group, rather it enables women to transcend the stigmas associated with traditional gender roles, framed and maintained by hegemonic patriarchy. The theory of ‘female masculinity’, proposed by Judith Halberstam is the chosen axiom for the existing discussion. The proposed manuscript endeavors to apply the theory of female masculinity in two literary narratives, namely Ladies Coupe by Anita Nair and The Kitchen God’s Wife by Amy Tan. The study attempts to analyze the characters as depicted in the novels to explore the notions of female masculinity and how it acts as a strategic counter discourse against the suppression encountered by women in a patriarchal society. Although originating from different geographical contexts, the works portray the shared experiences and survival struggles of women across diverse societies, irrespective of time and place. The female characters of both the novels express traditional masculine traits, thus defying the norms of gender performance. It is thus anticipated that the works of Amy Tan and Anita Nair revises the traditional gender roles and that female masculinity subverts the gender performance practiced and maintained through patriarchy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".