Collateral kids: Weighing the lives of children in targeting
Bibliographic record
Abstract
Abstract The principle of proportionality under international humanitarian law prohibits an attack if the expected harm to civilian persons and objects is excessive in relation to the anticipated concrete and direct military advantage. In this article we argue that, when applying the principle of proportionality, the incidental harm to a child must be given a higher value as compared to incidental harm to an adult. This reflects the broader framework of international humanitarian law, which creates stratifications amongst different groups of civilians and provides special protection for children in times of war. This aligns with the practice of many militaries, which tends to implicitly assign a heightened worth to the lives of children due to moral and political considerations. Such reasons stem from the perceived vulnerability of children as well as their moral innocence reflecting harmlessness and blamelessness. Indeed, harm to children’s lives tends to generate a greater backlash among the community to which they belong and, as a result, a military disadvantage. We argue that the greater weight assigned to the lives of children in proportionality assessments is not simply a matter of morality or strategic calculations, but in fact a requirement from a more wholistic interpretation of international humanitarian law.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".