A Decade Later and Still on Target: Revisiting the 2006 Israeli Targeted Killing Decision
Bibliographic record
Abstract
The increasing use by States of extraterritorial targeted killing as a counter-terrorism tool in recent years has given rise to controversial questions concerning its legality under international law. This article first explores the international legal regimes purporting to govern State-sponsored targeted killing and evaluates their ability to effectively regulate it. It then focuses on the use of targeted killing by States against members of non-State terror groups in an international armed conflict. In this regard, the article revisits the 2006 landmark decision of the Israeli Supreme Court in the Targeted Killing case and evaluates its influence and legacy over the past decade. It argues that this decision remains relevant and instructive since it exposes some of the lingering weaknesses of international law in governing the use of targeted killing as a counter-terrorism tool, while at the same time demonstrating how such weaknesses may be overcome within the existing international legal framework. The impact of the decision in this regard is clearly evident in the evolution of Israel’s targeted killing practice over the past decade.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".