Forensic justice for marital rape victims in India: deconstructing patriarchal walls through criminal jurisprudence
Bibliographic record
Abstract
“Women would tell me about being raped and I had to sit there and think as a lawyer, ‘Yes, but were they married?’ If (yes,) …I had no options to help them...” These words uttered by Sarah Lerner, London-based lawyer in 1970s, felt foreign to lawyers after spousal rape criminalization in UK (1991) and several other countries including Australia (1976), Canada (1983), South Africa (1993), and USA (1993). However, Lerner’s words are still everyday reality for Indian lawyers who continue to struggle with explaining marital rape victims as to why a country supporting abortion rights to guarantee female autonomy, pulls back on this guarantee as soon as demand of criminalizing marital rape is put forth. Duality of such partial guarantee of female autonomy raises following questions – Why does marital rape still exist without criminal justice recourse in India? Whether arguments against its criminalization are legitimate? Paper explores Indian criminal jurisprudence around marital rape, along with need, relevance, and practicality of criminalization of spousal rape in India, while examining sufficiency of available civil remedies. Further, considering difficulty of proving absence of consent in marital rape cases, paper focuses on kind of forensic evidences that can be used to aid complainants’ claims in such cases, and discusses admissibility and evidentiary value of such forensic evidence. Consequently, paper analyses onus of proof in cases of marital rape, and the need for acknowledgement that a husband can commit rape on his wife, express consent, and proposing introduction of marital rape as a ground for divorce.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.032 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".