Prison Zooing and Conservation: Human and Animal Caging in a Time of Ecological Catastrophe
Bibliographic record
Abstract
Prisons are responsible for the social and biological death of the humans trapped within them, the animals whom it coerces prisoners to farm and slaughter, free-living animals displaced by prison building, as well as the ecosystems and waters destroyed by prison effluent which makes the lives of those dependent upon these systems and resources for survival, unliveable. In the context of the Sixth Extinction, the prison is at once one of the most resource intensive institutions contributing to Anthropogenic climate change and biodiversity loss, and paradoxically, in the last two decades, sometimes positioned similarly to zoos as an ecological saviour of threatened species. The most established example of this is the Sustainability in Prisons Project that operates in many United States prisons. Specific to conservation, it trains prisoners – often in partnerships with zoos – to captively rear endangered animals and plants. There is also a zoo located on the grounds of a Florida prison in which prisoners care for abandoned animals, which is open to the public for tours. This article argues that the current initiatives of prison zoos and prison conservation programs reflect the trajectory of animal zoo eras and human zoos, with unique implications: two institutions of captivity, the zoo and the prison, now reify each other under the auspices of ecological conservation – a project whose need and operation continues the racialized and anthropocentric projects that gave it rise.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".