CEDAW’s General Recommendation No. 35: A Quarter of a Century of Evolutionary Approaches to Violence Against Women
Bibliographic record
Abstract
This article analyzes the contribution to international human rights law of the third and latest General Recommendation on gender-based violence issued by the Committee on the Elimination of All Forms of Discrimination Against Women. Described as an “update” on General Recommendation No. 19 (1992), this article examines the extent to which General Recommendation No. 35 (2017) makes a more fundamental contribution toward accountability for women’s human rights. This analysis is motivated by the quarter-century gap since the previous recommendation but also the obvious limitations of the two earlier recommendations. An expansive document that reaffirms global commitments toward ending gender-based violence, General Recommendation No. 35 makes some significant conceptual advancements in how it frames gender-based violence and the scope of the issues brought within its ambit. Yet the Committee falls short when it comes to depth of analysis and in its ability to guide states on the implications of present-day concerns.
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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 | 0.046 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.053 | 0.039 |
| Insufficient payload (model declined to judge) | 0.013 | 0.012 |
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".