Diegetic Pregnancy in Jesse Greengrass’s Sight (2018), or the Ethics of Building Bodies in(to) Literature
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".