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Record W2208296064 · doi:10.33137/rr.v32i1.9591

Shakespeare's Penknife: Grafting and Seedless Generation in the Procreation Sonnets

2009· article· fr· W2208296064 on OpenAlexaffvenue
Vin Nardizzi

Bibliographic record

VenueRenaissance and Reformation · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSonnetArtHumanitiesPoetryLiterature

Abstract

fetched live from OpenAlex

Cet essai remet dans son contexte la figure de la greffe qu'utilise Shakespeare dans ses «sonnets de procréation» (numéro 1-17) par l'examen de la présentation de cette technique horticole dans la littérature de jardinage des seizième et dix-septièmes siècles. On y argue que le personnage du sonnet 15 se réfère à cette littérature, se terminant sur le vers «I engraft you new», visualisant la greffe horticole autant comme une technique d'écriture que comme une forme analogue à la procréation humaine. En tant qu'écriture, la greffe permet à l'orateur de se hisser au niveau des héritiers et de la poésie, puisque le canif est indispensable autant au poète qu'au jardinier, respectivement pour préparer une plume et une greffe. Toutefois, en tant qu'analogue de la procréation humaine, la greffe ne procède pas par semis ou par mélange des semences. Au lieu de cela, elle constitue une forme de génération ne nécessitant pas de semences, et de ce fait évoque le potentiel de la greffe comme reproduction travestie dans les Sonnets de Shakespeare.

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: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.010
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.032
GPT teacher head0.304
Teacher spread0.272 · 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

Citations21
Published2009
Admission routes2
Has abstractyes

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