The Volumes of the Royal Medical Society of France, 1776–1793: a Window into Innovation, Patronage and Experimentation
Bibliographic record
Abstract
In 1776, Doctors Vicq d’Azyr and Joseph de Lassone founded the Royal Medical Society of France and that same year the new Society began publishing an annual volume of news of medical interest, obituaries on the deaths of outstanding doctors and surgeons, articles on new medicine and drugs, on new operations as well as reflecting on the causes of different diseases and illnesses. Between 1776 and 1793, ten of these volumes were published under the title Histoire de la Société Royale de Médecine: histoire et mémoires. The Osler Library of the History of Medicine possesses four of them. Breaking with the tradition of Galen and with the diagnoses based on bookish knowledge, the members of this group favoured experimentation, the dissection of corpses and the close observation of the symptoms of the sick and the dying. This article looks at two aspects of their work: first it examines the goals and the structures of the Society that published the volumes and second, it analyses the organization and the types of articles published in the annual volumes.ResuméLes médecins Vicq d’Azyr et Joseph de Lassone ont fondé la Société royale de médecine en 1776 et aussitôt la nouvelle société a commencé à organiser la publication annuelle d’un volume de nouvelles d’intérêt médicales. Il devrait comporter les avis de décès des médecins et chirurgiens de renom, les articles sur des médicaments et drogues qui venaient d’être mis sur le marché, les interventions particulièrement innovatrices et les réflexions sur les causes de différentes maladies et épidémies. Entre 1776 et 1793, dix de ces volumes sont apparus sous le titre, Histoire de la Société Royale de Médecine: histoire et mémoires. La bibliothèque Osler de l’histoire de médecine détient quatre de ces volumes. Les articles des membres de ce groupe rompent avec la tradition de Galien et avec les diagnostics fondés sur les connaissances livresques. Ils favorisent l’expérimentation, la dissection des cadavres et l’observation des symptômes présentés par les maladies et les mourantes. Cet article étudie deux aspects de ces travaux: d’abord, il décrit les buts et les structures de la Société elle-même et second, il analyse l’organisation et les types d’articles publiés dans les volumes annuels.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.021 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".