General Jan Smuts and his First World War in Africa, 1914–1917 (David Brock Katz) & Botha, Smuts and the Great War (Antonio Garcia and Ian van der Waag)
Bibliographic record
Abstract
The two books reviewed here represent detailed biographies of top South African political and military leaders of the First World War (1914-1918).Katz's treatment of Jan Smuts sustains a clear argument throughout the text.Previous historians have underestimated Smuts's military experience, portraying him as an amateur general, and unfairly denigrating his accomplishments in the war especially during the German East Africa campaign.The case is convincing in many ways, especially regarding Smuts's wartime qualifications.While some previous historians described Smuts's role in the South African War (1899-1902) as leading a Boer commando of a few hundred men, Katz shows that Smuts planned the rudimentary Boer republican war strategy as attorney general of the Transvaal, learnt highly mobile Boer warfare under the mentorship of accomplished leader Koos de la Ray, and eventually led several thousand fighters during an incursion into the Cape.Subsequently, in 1914 and as deputy prime minister and cabinet minister in the Union government, Smuts played the leading role in planning the initial South African invasion of German South West Africa (GSWA, now called Namibia) involving simultaneous landings at the Atlantic ports of the territory and overland columns pushing up from the South African border in the south.Although this operation was delayed by the ultimately failed Boer rebellion -during which his staff work supported Prime Minister Louis Botha's campaign in the field -Smuts eventually took command of a sizable South African contingent in southern GSWA when the invasion was renewed in 1915, supporting the main invasion force under Botha to the north.In the context of the Boer republics and early Union, which provided no formal advanced military command training, Smuts had led brigade-sized forces and planned and administratively supported higher-level military operations.As such, he arguably had just as much -or probably more -relevant experience and expertise as many British generals.Katz makes several other related and interesting points about the GSWA campaign.He explains that the reduction of coastal landings in Smuts's original plan led to the South African defeat at the Battle of Sandfontein in September 1914 rather than other factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".