Where Precision Is the Aim: Locating the Targeted Killing Policies of the United States and Israel within International Humanitarian Law
Bibliographic record
Abstract
Summary If state practice is any indication, targeted killing is increasingly becoming regarded as a viable and effective response to the threat posed by terrorist organizations. Its growing role in armed conflict makes it particularly important that international humanitarian law (IHL) prove capable of providing an effective framework within which this practice may be governed. As it is currently conceived, however, IHL has shown itself ill-suited to the particular nature of armed conflicts between states and terrorist organizations on a broad level and, more specifically, to the practice of targeted killing. This article examines the decision of the Israeli supreme Court in Public Committee against Torture in Israel v. Government of Israel as an example of an effort to fit targeted killing within IHL, focusing on its characterization of “terrorists” and its imposition of the “least harmful means” requirement. The author suggests that, while the former exposes the difficulty of reconciling this development in armed conflict with existing rules, the latter demonstrates the benefits of relying on fundamental principles of IHL, in this case that of military necessity. The article concludes by contending that it is these principles, rather than existing rules, that should be viewed as the appropriate mechanism by which to accommodate targeted killing within IHL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".