Bibliographic record
Abstract
This chapter explores how the evolving disease environments of the tropics shaped free and forced migration patterns at English sites. The globalization of forced labor markets and trade were catalysts in the spread of yellow fever and falciparum malaria, diseases that originated in Africa and that disproportionately weakened or killed English migrants to the tropics. These were the two deadliest mosquito-borne fevers that the English encountered in the tropics. The ways in which the English understood and responded to evolving tropical disease environments and their differential effects on European and non-European populations contributed to the rise of enslaved majorities in the tropics and informed ideas about human difference that would coalesce into nineteenth-century racism. The chapter will also show how epidemiology made English footholds in the tropics much more precarious and dependent on non-Europeans than the English footholds in other more temperate zones of the empire. The chapter relies on case studies of disease outbreaks in the Caribbean, on the West African Gold Coast, and in Sumatra at key points in the seventeenth century.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.141 | 0.049 |
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".