Celebrating 25 Years of the UN’s Children and Armed Conflict Mandate: How Far Have We Come, and Where Do We Go from Here?
Bibliographic record
Abstract
Twenty-five years ago, the international community issued an urgent call to protect children affected by armed conflict. Horrified by the findings of Graça Machel’s historic study on the impacts of war on children, the United Nations General Assembly established the Children and Armed Conflict (CAAC) mandate in December 1996.Since then, the CAAC agenda has expanded and become one of the most significant, dynamic, and broadly supported multilateral initiatives within the UN system. It provides international policymakers a unique set of tools for promoting the protection of children in war and addressing grave violations of their rights. Even in today’s increasingly polarized world, policymakers can rally around the notion that no child should suffer the horrors of war.Despite progress, children continue to face the devastating impacts of armed conflict. In 2020, the UN documented nearly 24,000 grave violations against children. More children are living in conflict zones than at any time in the previous two decades. At the same time, the rapid expansion of the global counterterrorism agenda threatens to unravel established laws and norms for protecting children’s rights. The COVID-19 pandemic has further exacerbated children’s vulnerability to rights violations and other forms of exploitation and abuse.This commentary reflects on the progress made over the past 25 years, remaining gaps and challenges, and emerging concerns for children in war. It also provides recommendations for the years ahead.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.026 | 0.031 |
| 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".