The permissible and the perverse: Indian geographies of interspecies sex
Bibliographic record
Abstract
We argue in this paper that what separates permissible from perverse acts of killing, or sex with, an animal is a matter of material and symbolic space. We focus on interspecies sex –which is often, but not always, bound up with killing –to argue that what separates permissible from perverse acts of interspecies sex in India, or husbandry from bestiality, is where it occurs geographically in proximity to an upper-caste, anthropatriarchal imaginary of a Hindu nation. We argue that the state-sanctioned abattoir and its breeding facility are spaces of normalized exception, in which anthropatriarchal violences are relatively permissible, and on the same grounds as in the “human” space of the home. We trace interspecies sexual contact across spheres of bestiality, animal husbandry, petkeeping, and population control. We conclude with a queer bestial ethics of avowal, one that dispenses with anthopatriarchal innocence towards a more capacious embrace of the panspecies desire for touch and thriving.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".