The Role of Bollywood in Creating the Ideal Rape Victim in India
Bibliographic record
Abstract
Abstract The paper seeks to explore the role of popular Hindi cinema (Bollywood) in the creation of the image of an ideal rape victim that is expected by members of the criminal justice machinery (CJM) in cases of rape against adult women in India using theoretical, conceptual and interdisciplinary methodologies. The article would begin by reviewing contemporary literature on how Bollywood impacts society in the way certain crimes and victims are perceived and how the CJM deems certain victims more credible than the others. The article would then analyse the depiction of rape scenes in Bollywood movies from 1980 to 2022 to understand how specific characteristic markers are expected from rape victims by the CJM in India. Thereafter, the paper discusses the impact of each of these markers on the CJM and the role of media in shaping the opinion of society before offering possible solutions to address the issue and thereafter conclude.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".