A Series of Unfortunate Events: “First Battles” of the Nigerian Contingent in the Cameroon Campaign (1914–1916)
Bibliographic record
Abstract
Abstract The outbreak of the First World War marked the first time that Nigerian colonial soldiers were deployed against troops of another colonial power on the continent. British-ruled Nigeria’s newly unified army confronted its first combat challenge in Cameroon against the German colonial Schutztruppe . The initial confrontations between British colonial Nigerian soldiers and German Cameroon forces during the early stages of the First World War in West Africa resulted in a series of resounding defeats for the Nigerians. Nigeria Regiment units gathered at Yola, Maiduguri, and Ikom were tasked with defending the Nigerian borders from German incursions and launching offensives into Cameroon against critical frontier towns like Garua, Mora, and Nsanakang. Using the “first battles” principle articulated by military historians Charles Heller and William Stofft, this study concludes that inadequate preparation, failure of intelligence, and indecisive leadership by British officers led to a series of first battle defeats for British Nigeria’s colonial units. Furthermore, this work argues that the lessons learned from the defeats led to organisational and tactical shifts by the British Nigerian units and ultimately contributed to the expulsion of the Germans from Cameroon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".