A Small Stage for Global Conflicts: Decolonization, the Cold War, and Revolution in Zanzibar
Bibliographic record
Abstract
The process of decolonization in Zanzibar and the events surrounding its subsequent merger with Tanganyika to become the United Republic of Tanzania in 1964 reveal that postcolonial states did not enter a strictly bi-polar world, forced to choose between the two Cold War superpowers. Instead there were many geopolitical battles that complicated decolonization. In 1964 nearly every major global conflict played out in the islands. Not only were the Americans and Soviets vying for power, but the Arab-Israeli Conflict, the East-West German Conflict, and the Sino-Soviet Split — among other rivalries — all affected the new Zanzibar state. Events in Zanzibar also reveal that Africans, too, had agency in shaping their own futures. In fact, local and regional issues combined with the desires and aims of local power brokers were often the most decisive factors in determining the outcome of events. Not only were there multiple layers to decolonization, but influence moved in multiple directions. Africans were not just pawns in the superpowers' game; their actions shaped the contours of the various international conflicts involved as well as the foreign policies of the major players. The story of Zanzibar thus demonstrates that in order to understand decolonization in Africa during the age of the Cold War, the process has to be seen as a multi-polar, multidirectional, and multilayered affair. This paper also argues for the benefits of understanding the global dimensions of conflicts like those between the Arabs and Israelis, the Chinese and the Soviets and between the two Germanys. These were global conflicts in their own right and not just subplots or regional sideshows of the larger Cold War.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.023 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".