Conclusion: Prospects for Nonviolent Resistance in Palestine-Israel
Bibliographic record
Abstract
T he objective of this volume is to bring further attention to the use of nonviolent resistance in Palestine-Israel, 1 particularly during the second intifada, while also contributing to the scholarship of nonviolent resistance by exploring the changing actors, tactics, and perceptions shaping popular struggle in the region. The contributions in this volume provide a much broader discussion of Palestinian nonviolent resistance than is usually found in the scholarly literature, and examine the opportunities and challenges that come with broadening the discussion of unarmed struggle not only in theory but also in practice. The contributors to this book, coming from a range of professional, geographic, and disciplinary backgrounds, have provided varied insights into the phenomenon of nonviolent resistance in Palestine-Israel, based primarily on direct observations and personal experiences. Each chapter has provided a rich analytical snapshot of nonviolence in the region, illustrating the diversity of people, actions, and ideas involved in this type of struggle. Because this volume, unlike many on the Israeli-Palestinian conflict, is written largely by scholar-practitioners, the authors are concerned not only with how the acts of nonviolent resistance contribute to theoretical understanding of the phenomenon, but also ask practical questions regarding the significance of these findings for nonviolent resistance movements in Palestine-Israel and elsewhere.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".