“A Meat Locker in Hebron”: Meat Eating, Occupation, and Cruelty in To the End of the Land
Bibliographic record
Abstract
In this paper, I explore the connections between meat-eating, cruelty, and the Israeli/Palestinian crisis in Israeli author David Grossman's 2008 novel To the End of the Land (translated from the Hebrew in 2010 by Jessica Cohen). Using the radical vegetarian-feminist theories of Carol J. Adams, I argue that in the novel, Grossman reveals how the Israeli nation-state's treatment of the occupied Palestinian people is part and parcel of the same ideological construct that allows its citizens to consume the flesh of dead animals; if a nation can eat meat, it can dehumanize and oppress its unwanted others. In particular, I look at a pivotal moment in the novel, where the protagonist Ora's son's military unit leaves an elderly Palestinian man chained up and suffering in a Hebron meat locker; I locate this event as the most important physical space in a novel preoccupied with space, land, and physicality. I also look at another example of a Jewish author grappling with the cruelty of eating meat, the Yiddish writer Isaac Bashevis Singer's short story "The Slaughterer." Finally, I interrogate the idea, put forward by Todd Hasak-Lowy, that Grossman is less concerned with the sufferings of the Palestinian people than he is the sufferings of the stoic Israeli, forced to make compromising moral choices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".