Force Projection in the Time of Scurvy: The Destruction of the 1740-42 West Indies Expedition
Bibliographic record
Abstract
The massive British West Indies expedition of 1740-42 during the War of Jenkins’ Ear, launched with an ambitious goal, produced nothing beyond terrible losses. The enormous number of deaths from yellow fever has obscured the true reasons for the defeat at Cartagena de Indias that has often been blamed on the army’s slow siege tactics. The author, following his research for Disaster on the Spanish Main: The Tragic British American Expedition to the West Indies during the War of Jenkins’ Ear, has further developed evidence from British musters that upends common assumptions about yellow fever’s impact and, instead, traces the cause of the expedition’s failure to poor health management and misguided military leadership. L'expédition massive des Antilles britanniques de 1740-1742 pendant la guerre de l'Oreille de Jenkins, lancée avec un objectif ambitieux, n'a rien produit d'autre que de pertes terribles. Le nombre énorme de décès dus à la fièvre jaune obscurcit les véritables raisons de la défaite à Carthagène des Indes, souvent imputée à la lenteur des tactiques de siège de l'armée. L'auteur, suite à ses recherches pour Disaster on the Spanish Main: The Tragic British American Expedition to the West Indies during the War of Jenkins’ Ear, a étudié en profondeur les données probantes issues des registre militaire britanniques pour réfuter les hypothèses courantes sur l'impact de la fièvre jaune et attribuer plutôt l'échec de l'expédition à une mauvaise gestion de la santé et à un leadership militaire peu judicieux.
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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 | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".