Beyond Binary Justice: A Comparative Study of Gender Neutrality in Indian and International Criminal Laws
Bibliographic record
Abstract
Across criminal justice systems, “gender neutrality” has become a contested aspiration. Many jurisdictions have moved from gender specific offences especially in the domains of sexual offences, workplace harassment, and domestic violence toward gender inclusive or at least gender aware drafting. India’s recent overhaul of its penal code (the Bharatiya Nyaya Sanhita, 2023), together with legacy frameworks like the POSH Act, 2013 and the Protection of Women from Domestic Violence Act, 2005, has reignited debate on whether formal neutrality better advances equality than targeted, gender specific protections. This paper offers a doctrinal, comparative analysis. It (i) sets out working definitions and theoretical lenses (formal equality, substantive equality, and intersectionality), (ii) examines Indian constitutional and statutory developments alongside leading Supreme Court decisions, (iii) compares approaches in the United Kingdom, Canada, South Africa, New Zealand, and the United States, and (iv) reads these domestic frameworks against international and regional instruments (CEDAW, the Istanbul Convention, the Rome Statute/ICC Elements of Crimes, the Yogyakarta Principles). I argue that formal gender neutrality sometimes obscures structural asymmetries, while context sensitive neutrality paired with robust procedural protections and implementation can extend protection without erasing the realities of gendered violence. The paper concludes with a reform blueprint for India that reconciles constitutional equality with practical protection: making victim facing provisions gender inclusive, retaining targeted programming where warranted, clarifying consent standards, improving data and implementation capacity, and aligning with comparative best practices and India’s human rights commitments.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".