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Record W2587881078 · doi:10.1093/ehr/cex013

Salsamenta pictavensium: <i>Gastronomy and Medicine in Twelfth-Century England</i>

2016· article· en· W2587881078 on OpenAlexaff
Giles E. M. Gasper, Faith Wallis

Bibliographic record

VenueThe English Historical Review · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsMcGill University
Fundersnot available
KeywordsGastronomyExtant taxonRecipeClassicsFish <Actinopterygii>HistoryGenealogyArtAncient historyArchaeologyBiology

Abstract

fetched live from OpenAlex

Abstract This article presents a collection of culinary recipes from a manuscript produced in England from the later twelfth century. The suite of ten recipes for ‘Poitou sauces’ or ‘Poitou relishes’ (salsamenta pictavensium—literally ‘of the Poitevins’) to garnish various kinds of meat, fish and fowl are introduced and analysed, with an appended edition and translation. These are, to date, the oldest extant medieval recipes for such sauces, and in their role as gastronomic enhancements, the earliest surviving medieval culinary recipes. The historical and cultural contexts for the recipes at Durham Cathedral Priory are explored: the nature of the community for whom the recipes were written, its choices of library acquisition, its relationships with the bishopric, and attitudes within the community towards food and medicine in a monastic setting. The Poitevin designation of the sauces is also considered. Above all the article investigates the question of the relationship between gastronomy and medicine in the twelfth century, and seeks to demonstrate that any distinction between medical and culinary recipes suggests a false dichotomy, particularly in the case of salsamenta. The authors argue against the position that medieval cuisine is, in its origins and essence, applied dietetics, and suggest that in the twelfth century salsamenta belonged in the first instance to gastronomy, but were in the process of being appropriated as medicines by the authors of the new literature of therapeutics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2016
Admission routes1
Has abstractyes

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