Patrolling the White Man’s Grave: The Impact of Disease on Anglo-American Naval Operations Against the Slave Trade, 1841-1862
Bibliographic record
Abstract
The Northern Mariner/Le marin du nord He was only twenty-four years old. 2 Lawrence's fate was typical of many British and American sailors of the nineteenth century whose antislavery duties exposed them to the tropical diseases of Western Africa. Between 1825 and 1861, at least 1845 men from the Royal Navy's African Squadron died. 3 The United States Navy, with far fewer personnel assigned to the African Station, lost eighty-six men. 4 Tropical fevers were responsible for the vast majority of these deaths. Mosquitoes bearing malaria afflicted white sailors who lacked the natural resistance of native Africans. European visitors to the infamous Slave Coast died at a horrific rate that earned the region the sobriquet of "The White Man's Grave." Indeed, one noted historian estimates that half of all Europeans who arrived in West Africa were dead within one year. 5 The dangers of tropical disease profoundly influenced British and American naval operations against the slave trade. Despite a primitive understanding of malaria and its origins, seasoned naval officers recognized that outbreaks of fever remained confined to coastal regions and employed measures aimed at limiting contact with the littoral. Strict orders prohibited sleeping ashore, while boat excursions into the interior were allowed only under extraordinary circumstances. Moreover, medical officers urged squadron leaders from both navies to abstain from using African ports, preferring distant St. Helena, Ascension, and the Cape Verde Islands. Not surprisingly, these limitations posed a dilemma for officers tasked with patrolling an extensive coastal region that afforded natural protection for shallow-draft slavers. Naval leaders recognized inshore blockades and coastal operations as the most effective means of interdicting slavers, and sought to establish a balance between service requirements and health concerns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".