Bibliographic record
Abstract
The Somaliland Burgher Contingent, consisting of Afrikaans and English speaking South Africans, was the first South African volunteer unit who fought on foreign soil. Volunteers hailed not only from South Africa but from Britain, Rhodesia, America, Ireland, Scotland, Canada and Austria as well. This truly cosmopolitan unit fought during the Third Expedition (1902-1903) in Somaliland against Mohammed Abdulle Hassan (1856-1920) - the so-called Mad Mullah. During this expedition the South Africans fought side by side with British troops of the King's Royal Rifle Corps, Indian troops and the King's African Rifles whose members consisted of Somalis, Sikhs, Sudanese and Yaos (Africans). These troops endured many hardships during the campaign: they had to march in extreme heat in thick bush country with meager rations and water. The Somaliland Burgher Contingent was involved in skirmishes with the Dervish forces of the Mullah but not in the disasters of Gumburu and Daratoleh during which two British forces were cut up. The Third Expedition was a military failure for the British and a victory for the Mullah who wanted to rid his country of the British infidel. The Mullah resisted British and Abysinian intrigues in his country until his death in 1920. Apart from the campaign, the composition, character, mobilization, demobilization and compensation of the Somaliland Burgher Contingent as well as the reasons why volunteers joined up, are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".