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Record W2796446898 · doi:10.1080/20549547.2018.1458563

The Garden, the Library, the Body, and the Table: Ways of Knowing Food in John Evelyn’s<i>Acetaria: A Discourse of Sallets</i>

2018· article· en· W2796446898 on OpenAlexfundno aff
Caroline Lieffers

Bibliographic record

VenueGlobal Food History · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Philosophy and Science
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaPierre Elliott Trudeau FoundationYale University
KeywordsTable (database)ArtFood studiesArt historySociologyAestheticsAnthropologyComputer scienceDatabase

Abstract

fetched live from OpenAlex

This article uses John Evelyn’s Acetaria: A Discourse of Sallets (1699), a short book on the garden’s edible products, to highlight the place of food in early modern science. Exemplifying the period’s epistemic dynamism, Evelyn blended facts and interpretations gleaned from the garden, the library, the body, and the table. Food was a kind of quotidian trading zone, a potential meeting place for publics and ideas, and Evelyn was able to find points of contact and exchange between these diverse sources. Acetaria distilled the many flavors of early modern knowledge making and illustrated food’s capacity to hold them in tasteful harmony.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.035
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.201
Teacher spread0.167 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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