To cast out disease : a history of the International Health Division of the Rockefeller Foundation (1913-1951)
Bibliographic record
Abstract
1. Introduction PART I: ROSE'S VISION 2. The First Stage: Rose's Vision 3. Rose's Vision: Tuberculosis in France (1917-1924) PART II: DISEASE ERADICATION 4. The First Hookworm Campaigns (1913-1920) 5. Retreat from Hookworm (1920-1930) 6. Yellow Fever: From Coast to Jungle 7. Malaria: Killing Mosquitoes and Anophilines (1915-1935) 8. World War II: DDT, Typhus, and Malaria 9. Malaria: The Ultimate Kill PART III: A RESEARCH PROGRAM 10. Reorganization and Research Laboratories (1928-1940) 11. Yellow Fever Vaccines: A Slap in the Face 12. Disease for Research PART IV: TRAINING THE EXPERTS 13. Frustrations in Sao Paulo: The Wrong Step in Rio 14. Northern Lights: London and Toronto 15. Rough Seas: Prague, Rome, Tokyo PART V: FINALE 16. Post-War Confusion: What To Do Next? 17. Conclusion: Swinging Pendulums
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.037 | 0.013 |
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".