Bibliographic record
Abstract
In October 2000, the UN Security Council unanimously adopted Resolution 1325, calling for the “broad participation of women in peacebuilding, (and) post-conflict reconstruction.” The resolution highlighted the increased targeting of women and children in war and “the need to increase their role in decision-making with regard to conflict prevention and resolution.”1 In discussions preceding the resolution’s adoption, delegates implied that including women’s perspectives in peace-building would not only enhance justice and equity, it would also contribute greatly to the success of peace efforts. Durga Prasad Bhattarai of Nepal’s Permanent Mission to the UN, reflected the general tone of the speeches when he said that women tend to be “more sincere, more reliable, and more compassionate” than men, and “shunned violence more consistently.”2 UN Secretary-General Kofi Annan gave a glowing account of women’s potential for peacework:
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.044 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 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".