Partition Of India: A Boon Or Curse, With Special Reference To Women Struggle In Deepa Mehta’s Film 1947: Earth
Bibliographic record
Abstract
Nationalism in India had grown as a form of movement which was fought against British colonialism for independence and power. However, the views on the country’s partition are ambivalent. Deepa Mehta, an Indo- Canadian film director and screenwriter has reflected the condition of India during the pre- partition and partition phase. The movie 1947: Earth was released in 1998, reminding the bloodiest history of India. The religious sentiment has been played as a trump card by the British colonizers resulting to bloodshed among the common people. The decision of the colonizers to divide British India into two parts India and Pakistan has ended up with bloodshed, dislocation and boundaries. Therefore, the paper describes the partition scenario of India and its aftermath through the film “1947: Earth” by Deepa Mehta. It also reflects the condition of women who had to face two battles, one with the colonizers and the other with their own society. The theory of new historicism, feminism and Bhabha’s theory of otherness are to be applied here. Along with all these, the paper will showcase the eminent role of women both as a victim and a powerful one during the time of partition.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".