Refugee settlement as dialogue: conversations and contestations between the Tanzanian state, Mozambican liberation leaders and humanitarian officials (1964–1971)
Bibliographic record
Abstract
During decolonization, African host states, liberation leaders and humanitarian officials debated, negotiated and modified who they each thought best to manage refugee settlements: expatriates or African staff. Using 1960s postcolonial Tanzania as a case study, this article synthesizes a range of archival materials from the agencies responsible for establishing Mozambican refugee settlements in Tanzania: the Lutheran World Federation, Tanganyikan Christian Refugee Service and United Nations High Commissioner for Refugees. It demonstrates and interrogates why these humanitarian agencies and the Tanzanian state sought to have fewer expatriates in refugee camps, while the Mozambican liberation movement, FRELIMO, advocated for the opposite. It argues the Tanzanian state preferred nationalist staff over expatriates due to governmental presumptions that African staff could better monitor refugee daily life – and identify subversive activity – than expatriates could. This put the Tanzanian state at a crossroads with FRELIMO, while humanitarian agencies often found themselves caught between the two agendas.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.036 | 0.036 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".