Bibliographic record
Abstract
This book has two purposes. It offers an overview of Africa's historical encounters with the seven cholera pandemics from 1817 to the present. Second, it explores the epidemiology of the contemporary African experience during the seventh cholera pandemic, for which evidence is more robust and for which the analysis has immediate policy relevance. Scientific interest in cholera continues to be significant. Not only did the disease help launch the new field of epidemiology in the late nineteenth century, it also represents a fascinating and complex challenge in the newest research specialties of disease ecology, membrane biology, and trans-membrane signaling. In public health circles, cholera raises questions for global health workers concerned with new and reemerging infectious diseases. Part One describes the first six cholera pandemics through to 1947, emphasizing how the disease affected Africans. Of course, Africa's experience with cholera cannot be isolated from that of other parts of the globe, especially the Middle East and the Indian Ocean region, long active as favorite routes for cholera's diffusion into the African continent. Nor can the experience of Europe and the Americas be overlooked, especially efforts in the industrializing countries to diagnose and treat this dreaded disease. Chapters 1 and 2 explore cholera's global trajectory and the medical responses the disease provoked. Much of the record of Africa's early experience with cholera has not survived, which may explain why this is the first attempt to produce a study of cholera in Africa.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.473 | 0.310 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".