Bibliographic record
Abstract
This paper explores the cultural politics of the police dog by tracing the role of dogs in the fabrication and reproduction of an anthropocentric social order in line with the imperatives of racial capitalism. These imperatives are based on sorting forms of life in accordance with their proximity to a normative white humanity as part of a project of meeting capitalism’s shifting valorization requirements. I argue that such sorting manifests as both labourers compelled to work by the violence of policing and as populations rendered surplus and made to die through killing, confinement, or organized abandonment. The paper reads the historical use of police dogs against Black protesters from the Civil Rights Era to the present, the children’s television show PAW Patrol, and Israel’s use of robot dogs in its ethnic cleansing of the Gaza Strip as examples of policing as an operation of life sorting and as a manifestation of racial (bio)capitalism that makes use of the lively capacities and properties of dogs. The paper draws on work at the intersections of animal studies, Black studies, labour studies, and critical theories of settler colonialism (especially those focused on occupied Palestine) to argue for thinking together Black liberation, police abolition, Palestinian liberation, and animal liberation toward a project of mutual freedom for all life on a shared and finite world.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".