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Record W4389967351 · doi:10.14453/asj/v12i2.6

Prison Zooing and Conservation: Human and Animal Caging in a Time of Ecological Catastrophe

2023· article· en· W4389967351 on OpenAlexaff
Kelly Struthers Montford

Bibliographic record

VenueAnimal studies journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPrisonThreatened speciesContext (archaeology)Environmental ethicsAnthropocentrismEndangered speciesSustainabilityEcologyPolitical scienceSociologyCriminologyGeographyLawBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.382
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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