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Record W2048368101 · doi:10.1017/s0007087405007582

Examples and experience: on the uncertainty of medicine

2006· article· en· W2048368101 on OpenAlexaff
Stephen Pender

Bibliographic record

VenueThe British Journal for the History of Science · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHippocratic OathArgument (complex analysis)InvectiveRhetorical questionAnalogySet (abstract data type)EpistemologyMedical practiceRhetoricPhilosophyClassicsMedicineLawMedical educationHistoryPolitical scienceTheologyComputer science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0130.055
Scholarly communication0.0110.015
Open science0.0020.010
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.069
GPT teacher head0.259
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2006
Admission routes1
Has abstractyes

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