The Composition of the Rhodesia Native Regiment during the First World War: A Look at the Evidence
Bibliographic record
Abstract
Several scholars of the First World War in Southern Africa have briefly looked at the composition of the Rhodesia Native Regiment (RNR), which was formed in Southern Rhodesia in 1916 and fought in the German East Africa campaign until the armistice in November 1918. According to Peter McLaughlin, who has written the most about Zimbabwe and the Great War, “[b]y 1918 seventy-five per cent of the 2360 who passed through the ranks of the regiment were ‘aliens;’ over 1000 came from Nyasaland. The Rhodesia Native Regiment had thus lost its essentially ‘Rhodesian’ character.” This would seem to suggest that because the RNR had many soldiers who originated from outside Zimbabwe, this regiment was somehow less significant to Zimbabwe's World War I history. While McLaughlin admits that “the evidence on the precise composition of the Rhodesia Native Regiment is not available”, he claims that “approximately 1800 aliens served in the unit.” In a recent book on Malawi and the First World War, Melvin Page agrees with McLaughlin's estimate that “probably more than 1000 Malawians joined the Rhodesian Native Regiment.” However, Page freely admits that the evidence on which this approximation is based is far from conclusive. By looking at the available evidence, particularly a previously unutilized regimental nominal roll in the Zimbabwe National Archives, it is possible to gain a clearer picture of the composition of the only African unit from Zimbabwe to have fought in the First World War. This analysis will not only deal with the nationality of the soldiers, which is what the two previous writers focused on, but also their ethnic/regional origin and pre-enlistment occupations.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".