Leslee Udwin’s India’s Daughter (2015), the power of storytelling and question of social change in the #MeToo era
Bibliographic record
Abstract
In an op-ed, Leslee Udwin, the filmmaker of the controversial but meaningful documentary, India’s Daughter speaks of the tensions she faced in India amidst her film’s release. After her movie was banned in India, she abruptly left the country to avoid arrest. Her film explores the complexities and nuances of the 2012 Delhi rape case. It drew criticism when the trailer was released because it allegedly focused on the rapist’s narrative. Drawing upon my interview with Udwin and archival research, I explore the multitude of ways in which Leslee’s position as a powerful storyteller and an outsider influenced her documentary’s success within and outside of India. A medium of social change, Udwin’s documentary underscores the patriarchal and misogynistic attitudes that continue to exist while simultaneously challenging the role of the state, politicians and law enforcement who are in charge of protecting women’s rights.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| 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".