Legal technologies: Conceptualizing the legacy of the 1923 <i>Hague Rules of Aerial</i> Warfare
Bibliographic record
Abstract
Abstract Many contemporary armed conflicts are shaped by the reliance on airstrikes using traditional fighter planes or remotely piloted drones. As accounts of civilian casualties from airstrikes abound, the ethics and legality of individual airstrikes and broader targeting practices remain contested. Yet these concerns and debates are not new. In fact, a key attempt to regulate aerial warfare was made 100 years ago. In this article, we approach the regulation of aerial warfare through an examination of the 1923 Hague Draft Rules of Aerial Warfare and the contemporary scholarly discussion of these rules. While the Draft Rules have never been converted into a treaty, they embody logics of thinking about civilians, technologies of aerial warfare, and targeting that are still resonating in contemporary discussions of aerial warfare. This article argues for a contextualized understanding of the Draft Rules as an attempt to adapt International Humanitarian Law (IHL) to the new technological realities while maintaining distinctions between different kinds of spaces and non-combatants. We argue that the Draft Rules prefigure later debates about the legality of aerial bombing by tacitly operating with a narrow understanding of the civilian and by offering a range of excuses and justifications for bombing civilians.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.006 | 0.094 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".