Bibliographic record
Abstract
After a brief account of the uncertainty of medicine in early modern thought, this paper focuses on two supple, sophisticated accounts of medicine by 'non-medical' writers--Michel de Montaigne's views of medical theory and medical practice and Francis Bacon's proposals for renovating both--in which the claims of individual sufferers are set against the normativity of medicine as a whole. From around 1500 to around 1680, in the common ensemble of both learned and popular invective, medicine was disparaged as poor philosophy and worse practice, even as the 'lowest of professions'. In remarkably broad, elegant interventions, Montaigne argues that medicine is based on 'examples and experience' (and 'so is my opinion', he adds), impugning its universalizing claims with the tractable experience of his own embodiment, with his own historia and consilium, while Francis Bacon enlists dietetics, Hippocratic case-taking and medical history in his broad programme for the reform of medicine. He more or less accepts Montaigne's argument for particularity in medical theory and practice, but presses the particular into service in his reformist programme. Like many sixteenth- and early seventeenth-century scholars and physicians frustrated with Galenic methods and models, both turn to Hippocratic practice and to hygiene and dietetics as salves for an ailing discipline. Finally, I argue that both writers enquire into viable means for inflecting learned medicine with particular experience, and both settle on rhetorical tools - analogy and exemplarity - as the means by which universalized medical models might be particularized or reformed.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.055 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".