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Record W2041500002 · doi:10.4000/shakespeare.1702

Failures of Eating in The Merchant of Venice

2012· article· fr· W2041500002 on OpenAlexaff
David B. Goldstein

Bibliographic record

VenueActes des congrès de la Société française Shakespeare · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicDeath, Funerary Practices, and Mourning
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

The Merchant of Venice contient de nombreuses références aux repas. Cependant, il est frappant de constater qu’aucun n’est mis en scène dans la pièce. La nourriture ne nourrit pas, ou elle demande pour cela un tel effort qu’il en devient dissuasif. Néanmoins, les gens doivent se sustenter. Dans cette pièce comme dans tout le corpus shakespearien, le corps exige que l’on calme son terrible appétit. La nourriture occupe une place centrale dans la pièce, qui s’ouvre sur l’image du vent refroidissant la « soupe » de la mer et qui offre plus loin une métaphore comparant la générosité de Portia à une manne tombée du ciel. Le monde décrit dans la pièce semble potentiellement comestible, il est offert à certains mais refusé à d’autres. Les personnages semblent également comestibles, et donc vulnérables. Shakespeare crée une œuvre dans laquelle il interroge l’interchangeabilité d’une « livre de chair » et d’une livre de mouton, de chèvre, de porc, ou de tout être humain. The Merchant of Venice est une pièce sur la réduction de l’humanité à une simple matière et sur le potentiel de cette matière d’être consommée. Elle démontre comment le fait de manger peut unir, ou plus fréquemment comment il peut mener à la destruction.

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)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.017
Scholarly communication0.0070.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.052
GPT teacher head0.358
Teacher spread0.307 · 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
GenreOther

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
Published2012
Admission routes1
Has abstractyes

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