Arundhati’s Literary Voice through the Lens of Rokeya’s Subaltern Enlightenment: A Reading on The Ministry of Utmost Happiness and Padmarag
Bibliographic record
Abstract
Subaltern" genders in South Asia denote the subordination of female gender and transgender, who cannot speak against the patriarchal social dominance.To make the subalterns speak, in 1924, Begum Rokeya in her Padmarag, and in 2017, Arundhati Roy in her The Ministry of Utmost Happiness, boldly resist in the same tone for the stigmatized and dispossessed against the social construction.To enlighten and boost up the silent spirits of the subalterns, Rokeya introduces "Tarini Bhaban" and Arundhati "Jannat Guest House," two paradises full of reason, nature, freedom, progress, and happiness in the society of the Indian subcontinent.This paper aims to show "Jannat Guest House" and "Tarini Bhaban" as places of enlightenment for the subalterns, who are considered inferior rank in the society and family of the Indian subcontinent.The paper also explores the miserable socio-living conditions of those oppressed genders.In Rokeya's time, women named Tarini, Soudamini, and Sakina were marginalized in patriarchal social power and denied health, education, employment, liberty, and individuality.Also in Arundhati's novel, transgender Anjuman; straightforward woman Tilottoma, and many paradoxical identities are mistreated and rejected by their blood relations and excluded from any kind of social forms and organizations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".