Transcending Gender Binaries: Exploring Manjukapur's “A Married Woman” and “The Immigrant”
Bibliographic record
Abstract
Gender studies speak of gender exploitation gender stereotypes and gender equity. The whole issue hinges on sex differentiations, which is natural and its variance from gender differentiations, patriarchy has ruled the roost side-lining women as the ‘second sex’. Nature does not permit any differentiation among the sexes based on gender roles. But for generations, women have been victims of oppression, exploitations and denial of rights. In fact, they have become complicitous in their own subjugation by passively accepting and fulfilling stereotypical roles of self – denial, self - sacrifice and spiritual suicide. So, one feels the time has come to de -gender ourselves and be classed as ‘humans’ capable of conscious living and intelligent thinking. This is the solution implied in Manju Kapur’s A Married Woman (2002) and The Immigrant (2008) the two novels have been chosen as test cases. Both the protagonists undergo a metamorphosis in the white heat miserable, familial and social existence. Astha though, she returns to family - life is a different person at the close of the novel. She has seen the bitterness of both sites of life, inner and the outer, the familial and the experimental and become sadder and wiser. Nina in the final chapter of The Immigrant is ‘Arthanari’ having become semi – man expecting a new opening in a new land. The novel portrays her odyssey from India to Montreal and from a helpless immigrant to a militant citizen of the world.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".