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Diegetic Pregnancy in Jesse Greengrass’s Sight (2018), or the Ethics of Building Bodies in(to) Literature

2023· article· en· W4385347027 on OpenAlexaff
Maxence Gouleau

Bibliographic record

VenueSillages critiques · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTheological Perspectives and Practices
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsCuriosityMetaphorTheme (computing)NarrativeSightPsychoanalysisPaintingAestheticsPsychologyArtLiteratureVisual artsPhilosophySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Although they have often been used as metaphors for the act of writing, pregnancy and childbirth have a long history of being left out of literature itself, especially as diegetic events in the novel. Jessie Greengrass’s novel Sight (2018) provides us with a rare pregnant narrator and as such includes pregnancy as a diegetic event and as a theme. Starting with the assessment that pregnancy in literature can be summed up by the image of “a man pac[ing] a carpet” while a woman gives birth outside the frame of the narration, Greengrass’s novel tackles the compulsion to look and to look away, to show and to hide that is at the heart of this image. The novel shows that pregnant bodies have been overlooked by literature not for lack of curiosity, but rather because of an obsessive curiosity for what lies inside them and what comes out of them. By investigating scientist/object relationships alongside mother/daughter relationships, Sight formulates the beginning of an ethics of looking at and of writing about bodies, which lies in a practice of parenthood that acknowledges both curiosity for and discomfort with bodies. The novel thus deconstructs the metaphor of writing as pregnancy and childbirth and points to an ethical way of incorporating bodies, especially female ones, into literature.

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)0.006
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0090.034
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.094
GPT teacher head0.446
Teacher spread0.352 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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