Working Through a War: The Traders of John Holt & Co. in Cameroon During the First World War
Bibliographic record
Abstract
This paper will explore the experiences of John Holt & Co.’s European and African traders who were in German-controlled Cameroon when war broke out in August of 1914. Using company and government archives, the paper argues that local employees, who came from multiple European countries and from across the west coast of Africa, faced significant hardships but, through skill, experience, and self-interest, kept the company afloat at a time of crisis and transition. The paper begins with an investigation of how the German government in Cameroon made British employees prisoners of war and then, after the British conquest of Douala, German employees were subjected to the same treatment by occupying forces. The second part explores the breakdown of trading networks and the difficult situation of employees in the interior who suffered from a lack of security, the violence of invading armies, and the destruction of property. Despite the hardships, wartime conditions also created economic opportunities for some African employees, and part three explores their enlarged responsibilities during the war years. The final section examines the post-war era as the region transitioned from German to Anglo-French control, exploring some continuities with the pre-1914 period as well as the consolidation of some companies and an increasing expatriate dominance over the commodities trade.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.040 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| 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".