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Record W2313737110 · doi:10.1111/cag.12010

Panda politics

2013· article· en· W2313737110 on OpenAlexaffvenueabout
Rosemary‐Claire Collard

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWildlifePoliticsGeographyChinaPolitical scienceEcologyArchaeologyLaw

Abstract

fetched live from OpenAlex

This article argues that China's agreement in 2012 to loan Canada two panda bears is emblematic of animals’ simultaneous material‐symbolic inclusion and exclusion in contemporary politics. Employing a material focus, this article draws a connection between the panda gift and the promise to which it is attached: a promise of material flows; of Chinese access to Canadian resources, especially; and controversially, tar sands oil. Common to geographical flows of both pandas and oil is a devaluation of nonhuman life. In one flow, two pandas cross the Pacific for a decade of captivity at the Toronto and Calgary Zoos, where visitors will pay to view the permanently visible pandas. In the other instance, oil will be shipped across the same ocean, oil whose production comes at great cost to wildlife, including caribou, birds, and fish, and whose spill at any point along its journey to China would devastate marine and terrestrial wildlife populations. Stark power imbalances between species are at the heart of both of these flows and their material consequences. This article argues that, in emphasizing what the pandas symbolize, the extent to which their own and others’ lives are materially affected is elided.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.006
Science and technology studies0.0040.005
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations14
Published2013
Admission routes3
Has abstractyes

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