‘The eye could literally not follow her’: deviant girlhood, reproduction, and meat animals in twentieth-century American literature and culture
Bibliographic record
Abstract
This project follows fictional girls in American cultural texts as they move within and sideways to spaces of meat production and animal agriculture, negotiating their reproductive futures alongside the animal allies they find in these spaces. What might happen when industrial meat production, animal domestication and the girl are held together? I assert that the intimacies between girls and domesticated agricultural animals are sites through which these girls work through not only their fraught relationship with animality but also with America as a white supremacist, patriarchal, and settler-colonial project. I thus ultimately ask how they gesture towards alternate futures at odds with their contemporary American empires. Chapter One centres Ona who labours in the sausage room and in childbirth to show how her womb troubles the efficiency of meat imagined by Upton Sinclair’s The Jungle, which I demonstrate is also intimately tied to reproduction. Chapter Two turns to Tillie Olsen’s Yonnondio From the Thirties to follow Mazie’s coming of age, which takes place sideways to three spaces: the home, the slaughterhouse, and the depleted Prairie landscape. Chapter Three looks to Charles Burnett’s film, Killer of Sheep, to ask how the character of Angela, who first appears in a dog mask in a threshold space, blurs boundaries between the home and the slaughterhouse as well as between dogs, sheep, and humans. Chapter Four moves to occupied Hawai’i, looking to Lovey and Toni, the Japanese Hawaiian girls who narrate Lois-Ann Yamanaka’s Wild Meat and the Bully Burgers and Heads by Harry. I question how both girls negotiate menstruation, pregnancy, and their sexualities alongside domesticated animals violently mounted, killed, and consumed. Chapter Five reads Bong Joon Ho’s film, Okja, for its representation of Mija and Okja’s interspecies intimacy as queer. I also argue that the film positions Mija as a flexible acrobat who transacts herself transnationally. Finally, three interludes punctuate this project to tug at questions of girlhood, domesticated animals, abortion, and American literature. Together, I assemble a chorus of girls and their animal allies who speak across a century of American texts, centring love and care in a landscape of violent empire.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| 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".