The British and Ethiopian Disposal of Italian Property in Ethiopia, 1941-1956: A Historical Review of the Theory and Practice of the Custodianship of Enemy Property
Bibliographic record
Abstract
During the Second World War, the Horn of Africa staged unusual and fast shifting encounters among the colonizers, the colonized, and would be super powers. Governments acted according to their own war time needs and postwar aspirations imbued with the Cold War. Investigating how this transpired in Ethiopia offers valuable insights about the wartime status of international laws regarding the management of property belonging to enemy states and their nationals. However, this is a sidelined aspect in the historiography of the Second World War. Using fresh archives and secondary sources, this article situates the British and Ethiopian treatment of Italian property in Ethiopia in the global discourse of the custodianship of enemy property. States mostly disregarded international law as political exigency and war time needs were given priority. As abstract laws had nominal respect, only individuals with technical, political and security profiles relevant to the victors enjoyed a relatively better protection. Besides, the victors absolved themselves from responsibility by including self-serving clauses in the peace agreement signed in Paris. Like other success factors, custodianship of enemy property was crucial in the rise and fall of firms. In this regard, the twentieth century was hardly progressive than preceding centuries were.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".