Bibliographic record
Abstract
This research argues that during the inter-war years in Palestine, British power was dependent upon intelligence. Intelligence was fundamental to the security of the country, since it varyingly augmented understrength force, or supported overwhelming force. Intelligence also supported policymakers as issues of governance were debated. It allowed British decision makers to avoid making a decision on self-government during the 1920s and it supported Britain’s failed attempts to introduce a constitution during the 1930s. Intelligence also was crucial to Britain’s relations with the Arab nationalist and Zionist communities. Of particular importance was Britain’s partnership and subsequent war with the Mufti of Jerusalem, Hajj Amin al-Husseini. This thesis sheds new light on the role of intelligence in British colonial policymaking, the development of the Arab-Zionist conflict, and how Britain failed to manage communal violence. This research offers a new and improved explanation of the origins, unfolding, and defeat of the Palestinian Arab rebellion. British intelligence and policymakers failed to grasp the sophistication of the Palestinian national movement until the mid-1930s, and even then, they focused on clan competition and the politics of ‘notables’. Intelligence and military records explain how British police and military struggled, but ultimately succeeded to suppress and defeat this rebellion. Victory was made possible by innovations within the intelligence and planning staffs, as well as Zionist cooperation. Intelligence shaped policy most clearly at the beginning and end of the period under examination. During 1918-20, the military government was administered by intelligence officers who guaranteed Britain’s future control in Palestine both domestically, and at the League of Nations. In 1939, British policy abandoned its traditional Zionist partners when the need to impose a solution on Palestine coincided with the opportunity, revealed by signals intelligence, to bolster and leverage the influence of ‘Abdul ‘Aziz ibn Sa’ud over the Arab national movement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".