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Record W2144211690 · doi:10.1177/0539018413477522

In the (bleary) eye of the tiger: An anthropological journey into jungle backyards

2013· article· en· W2144211690 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSocial Science Information · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsJungleTigerAntiquePopulationDomesticationState (computer science)GeographyBestiaryEthnologyEnvironmental ethicsHistorySociologyEcologyBiologyArchaeologyDemography

Abstract

fetched live from OpenAlex

North America shelters a growing population of so-called ‘exotic animals’. If the phenomenon is not recent, it now fuels a considerable black market. Jungle backyards compose a non-negligible (yet often neglected) part of some modern ecological landscapes. This article explores problematical situations emerging from these shared humanimal lives. It presents the first results of a multi-species ethnography and examines the prevalence of what I call beastness – an antique commerce amid humans and animals that reveals not only utilitarian purposes, but also relational entanglements. Such a commerce feeds a sizeable economy and exerts major selective pressures (both biological and cultural) on organisms and their environment. For instance, there are more captive tigers living in the state of Texas alone than wild specimens running free anywhere else on the planet. From a strictly statistical point of view, the average tiger is no longer the tiger we imagine. Not wild anymore but neither quite domesticated, some animals – pioneers, in a sense – shuffle traditional taxonomical and ontological conceptions. Through biographical material, I reflect on adaptive responses as well as on zoological potentialities developed by this always-evolving bestiary. Providing serious case studies to further debates dealing with bio–eco–conservation, I discuss the influence of informational and communicational processes crystallized by some of our contemporary crossed becomings.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.004
Scholarly communication0.0000.007
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.373
Teacher spread0.347 · 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