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Record W4205542407 · doi:10.7202/1081521ar

Représentations du corps ivre dans la littérature et la peinture hispaniques

2021· article· en· W4205542407 on OpenAlexvenueno aff
Juan Manuel Ibeas-Altamira, Lidia Isabel Bañares Vázquez

Bibliographic record

VenueTopiques études satoriennes · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
Fundersnot available
KeywordsPaintingArtWineThe ImaginaryPoetryChristianityIdeologyRepresentation (politics)HumanismLiteratureHumanitiesArt historyVisual artsPoliticsPhilosophyPsychologyReligious studiesTheologyLaw

Abstract

fetched live from OpenAlex

Wine has been linked to Spanish culture since the time of the Romans and early Christianity. In Spain, a land of vines since antiquity, the representation of the drunken body in literature and painting is an omnipresent topos since the Middle Ages. The pros and cons of this are found in medical, philosophical, moral and religious texts, but especially in novels, which warn against excess. This article studies how Spanish painters and writers developed the imaginary of wine in all its forms, be they masculine or feminine, solar or twilight, enthusiastic or drowsy, in their reflections, in their drawings and paintings, in poems or novels, in order to transmit the ideological transformation that was going to occur in Spain around this drink. For only the artist seems to preserve the tradition of the divine origin of wine, reclaiming its thaumaturgical role thanks to the Bacchic nectar. Spanish men and women suffer or benefit from the virtues of wine, the main alcoholic beverage in Spain until the 21st century.

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)0.001
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 score0.013
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.020
GPT teacher head0.304
Teacher spread0.284 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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