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Record W2154909023 · doi:10.1093/shm/hkm044

Food in Medieval England: Diet and Nutrition

2007· article· en· W2154909023 on OpenAlexaffabout
Constance B. Hieatt

Bibliographic record

VenueSocial History of Medicine · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsWestern University
Fundersnot available
KeywordsNew englandFood studiesClassicsGerontologyLibrary scienceHistoryArtMedicineSociologyPolitical scienceAnthropologyLawPolitics

Abstract

fetched live from OpenAlex

This volume is principally concerned with the thirteenth to the fifteenth centuries, but sometimes extends all the way back to Roman times and occasionally stretches as far forward as the sixteenth century. Since this is a book by historians and archeologists, it is not much concerned with how the food was eaten (i.e. culinary details) but these are not completely lacking. Among the contributors, the archeologists slightly outnumber the historians, appropriately, since only they can tell us much about the diet of the lower classes. The editors tell us in their introduction that ‘the emphasis of this volume … is on the use of archeological material in a quantitative and comparative framework to indicate overall patterns of diet and nutrition’. Most of the work needed for this kind of analysis is relatively recent, having been done in the last half-century, and the contributing archeologists frequently emphasise that what has been done is just the beginning and that conclusions are often tentative, for various reasons.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.002

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 head0.026
GPT teacher head0.234
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations60
Published2007
Admission routes2
Has abstractyes

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