FEMALE EXPERIENCES AS INDIANWIVES IN THE \nNOVELWIFE BY BHARATI MUKHERJEE
Bibliographic record
Abstract
According to Shilpi Pradhan, Mukherjee is included as one of American India woman \nauthor with literary career that was acclaimed started from 1971. Mukherjee's works focus on \nthe phenomenon of migration, the status of new immigrants, and the feeling of alienation that \noften experienced by expatriates as well as on Indian women and their struggle. Actually \nMukherjee as an immigrant makes her own struggle with identity first as an exile from India, \nthen as an Indian expatriate in Canada, and finally as an immigrant in the United States has \nled to her current contentment of being an immigrant in a country of immigrant. (1998) \nFrom that viewpoint, the writer concludes that Bharati’s works might provide several \nevidences through her personal issues. Her novel Wife is actually the shape of women \nexperience. The story of Wife tells about two women named Dimple Dasgupta and Ina \nMullick. Dimple who have been suppressed by such men and attempts to be the ideal Indian \nwives, but out of fear and personal instability, Dimple kills her husband and eventually \ncommits suicide. On the other hand, Ina Mullick tries harder to reach her dream; she wants to \nbe different from traditional Indian wives. This novel indicates the dilemma of the Indian \nwomen whose social role arranged by tradition. \nFrom those theoretical and historical reasons, the writer is interested to propose the \nstudy about feminist view of Dimple Dasgupta and Ina Mullick as the main character in Wife \nnovel by Bharati Mukherjee in a research entitled “Female Experiences as Indian wives in \nthe novelWIFE by BharatiMukherjee”
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".