Bibliographic record
Abstract
Israel’s posture of nuclear ambiguity has achieved a high level of consensus among its security elite, but are there any alternative approaches and what circumstances could facilitate change? This article argues that the longevity of ambiguity has been buttressed by three external factors that may change in the future and lead to a reassessment: the lack of another nuclear state in the region, bipartisan support in the United States, and the lack of a well-established peace in the region. To gain insight into the ideas that would inform a broader reassessment, I outline the strategic logic of three alternative approaches that have existed continuously in Israel’s security discourse. Nuclear advocates seek to move toward an open posture; nuclear skeptics seek to prevent proliferation by joining international treaties; and nuclear pragmatists support maintaining ambiguity under a US umbrella. Based on interviews with former officials, primary sources of Israeli elite discourse, and a broad survey of previous research, this article provides new insights into the making of Israel’s nuclear strategy by highlighting the continuity of the basic predispositions of each approach over the past 70 years, demonstrating how external factors have upheld the core elements of the policy of ambiguity while allowing room for changes on its margins, and outlining the possible future scenarios that may facilitate a more substantial policy shift.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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 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".