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Record W4415899478 · doi:10.5539/ijel.v15n7p7

“The Parent of Health and Long Life”. Food and the Popularization of Learned Medicine in Late-seventeenth-century England

2025· article· en· W4415899478 on OpenAlexvenueno aff
Giulia Rovelli

Bibliographic record

VenueInternational Journal of English Linguistics · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsnot available
FundersEuropean Commission
KeywordsMateria medicaPromotion (chess)Balance (ability)Health promotionFood productsAlternative medicineLatin Americans

Abstract

fetched live from OpenAlex

Although newer approaches, including the Paracelsian one, also started to gain more prominence, late-seventeenth-century medicine was still largely based upon the Hippocratic-Galenic system, where the relationship between nutrition, health and well-being occupied a prominent position. Indeed, food was included among Galen’s six “non-naturals”, that is, the activities that need to be regulated to balance the humors in the body and, consequently, to preserve (and in some cases also restore) health. Moreover, the distinction between food and drug was only pragmatic, as, because of their therapeutic properties, several kinds of foodstuff also appear among the simples and in the ingredients lists of compound remedies in all materia medica and receptaria. Following the methodology of Historical Discourse Analysis, the paper investigates how the relationship between food and well-being was presented and represented in a corpus of general medical handbooks that were translated from Latin into English in the late seventeenth century with the purpose of rendering learned medical notions accessible to a wider English-speaking audience, thus shedding light on dominant discourses on food and nutrition and their role in the promotion of well-being in early modern medicine.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.037
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.286
Teacher spread0.259 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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