The Contagion of Slow Violence: The Slaughterhouse and COVID-19
Bibliographic record
Abstract
COVID-19 has brought to the fore the violence faced by slaughterhouse workers and those they are charged with slaughtering. This article argues that COVID-19 has wrought an acceleration of the slow violence of state organized race crime (Nixon, Ward), in spreading rapidly through the slaughterhouse and to surrounding racialized communities. We show that zoonotic pandemics are the result of state organized race crime, and that abattoirs are locations of inseparable animal and racial violence. We then analyse how the law and state institutions have positioned slaughterhouse work as essential, contra workers’ claims and general knowledge that meat is an inessential ‘item’. We argue that this demonstrates the mechanics of state organized race crime and accelerates the speed of slow violence, while maintaining its insidious and routine nature. We then consider the #Boycottmeat movement which includes slaughterhouse workers, whom despite having a vested interest in this industry, have advocated for meat boycotts and a transition to plant-based diets as a matter of personal and collective safety.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".