Bibliographic record
Abstract
Gender issues were very much in evidence at the 1998 Rome Diplomatic Conference during the drafting and adoption of the Statute of the International Criminal Court (ICC). For example, difficult discussions surrounded the inclusion of provisions on the selection of a "fair representation of female and male judges", on the crime against humanity and war crime of forced pregnancy; and on the term ‘gender’ itself. Negotiations also took place on provisions related to other crimes against humanity and war crimes of sexual and gender-based violence, as well as on gender-sensitive participation of victims in the proceedings of the Court, victim protection, and composition of the staff of the Registry and the Office of the Prosecutor. Given the number of gender-related provisions, it is not surprising that the Rome Statute has been hailed for its attention to issues of gender. This attention to gender was not as evident at the Review Conference of the Rome Statute in June 2010 in Kampala, Uganda. While nearly all of the issues discussed in Kampala had gendered aspects, gender issues only really came to the fore in the stocktaking exercise, particularly under the theme of “the impact of the Rome Statute system on victims and affected communities”. This chapter outlines and examines the discussion of gender issues within the context of the official stocktaking exercise on victims, as well as in related side-events. It looks at gender issues related to the International Criminal Court’s outreach program and the Trust Fund for Victims. It concludes by making recommendations on U.S. engagement with respect to ICC victims issues.
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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 | 0.032 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".