State-directed political assassination in Israel: A political hypothesis
Bibliographic record
Abstract
Extant theories explain reasonably well why the Israeli state exercises a given level of violence against substate actors. Based on economic or sociological models of human action, these theories attribute the level of state violence, respectively, to the narrow cost-benefit calculations of state officials or the institutionally embedded norms that govern their deliberations. The strength of such theories notwithstanding, this article argues that they fail to account for the willingness of Israeli officials to order the assassination of high-ranking political opponents during the second intifada, or Palestinian uprising against Israel. This article’s analysis of published sources concerning the assassination of Hamas leaders Ahmed Yassin and Ismail Abu Shanab and of interviews with 74 Israeli counterterrorist experts suggests that the decision to engage in state-directed political assassination in the period 2000–5 was based less on narrow calculations and institutionally specific norms than on identifiable political contingencies. Specifically, the second intifada appears to have led many Israeli decision-makers to favour creating chaos in the Palestinian political system, a goal that was well served by the policy of political assassination. The policy’s effect was to forestall the founding of a viable, independent Palestinian state.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".