‘The gloomy forebodings of this dread disease’, climate, famine and sleeping sickness in East Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Identifying the nature of the association between climate, environmental, socio‐economic and political context and disease remains a major challenge, yet a better comprehension of the linkages is imperative if predictive models to guide public health responses are to be devised. Our understanding of the relationships could be improved through investigations of historical epidemics. In this paper we draw on a range of published and unpublished documents to explore the complex relationship between climate, environmental change and epidemic disease (re)emergence in East Africa, and Uganda in particular. This is a region which has experienced climate variability at a range of temporal and spatial scales, but which also has a long history of episodic epidemic disease. We focus on the late nineteenth and early twentieth centuries – a time of social, economic and political reordering in East Africa associated with European colonial intervention, but also a period which witnessed a variety of climatic, ecological and disease events. It will be argued that these developments coalesced, creating a set of spatially distinctive social and environmental conditions which fostered the emergence and prolongation of one of the most deadly episodes of disease in East African history, the sleeping sickness epidemic of c.1900–20.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it