Healing the Jesuit Body: François de Rougemont (1624-1676) and His Compendium of Medicinal Recipes
Bibliographic record
Abstract
This dissertation considers the early modern encounters between European and Asian curative ways to investigate how Jesuit missionaries acquired, reconfigured, and applied medical knowledge to secure their permanence in the overseas missions and buttress their pastoral activities. When exchanging recipes, inventorying nature, observing native therapeutics, and experimenting with indigenous materia medica, the missionaries participated in experiential knowledge-making practices. To explore these practices, I trace the activities and writings of the Flemish Jesuit François de Rougemont (1624-1676). Sent as a missionary to China, Rougemont recorded in his Breve Compendio (Short Compendium) the information he received along the way from confreres, travelling companions, congregation members, and medical practitioners. His compendium chronicled the missionaries’ engagements with various curative ways in order to learn to diagnose diseases, prepare remedies using locally available medicinal substances, and administer treatments.By analysing the content of Rougemont’s collection of recipes, I demonstrate how local knowledge traditions informed the Jesuit healing practices in missions in India and China. I also explore the different values ascribed to the manuscript as an object in motion by tracing its trajectory across global networks of communication. Following a largely chronological approach, this dissertation is divided into three parts, with each part showcasing the missionary’s participation in medical and natural knowledge exchanges during the transoceanic travels, in India, and China.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".