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Record W2050679985 · doi:10.1163/15685306-12341350

Animal Publics: Accounting for Heterogeneity in Political Life

2014· article· en· W2050679985 on OpenAlexafffund
Gwendolyn Blue, Melanie Rock

Bibliographic record

VenueSociety and Animals · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Calgary
FundersAlberta Innovates - Health SolutionsUniversity of Calgary
KeywordsPublicsSituatedPoliticsScholarshipAgency (philosophy)SociologyEnvironmental ethicsPolitical scienceEpistemologySocial scienceLaw

Abstract

fetched live from OpenAlex

To what extent do non-human animals participate in that particular political configuration known as a public? While conventional wisdom about publics is predicated on a vision of political agency that privileges discursive and deliberative processes, recent scholarship situated in the material turn in the social sciences and humanities challenges the notion that publics are purely human and constituted exclusively through language. With these theorizations as a backdrop, this paper takes into consideration the multiple species that are implicated in political life and that play a role in constituting publics. Placing material definitions of publics in line with central concerns raised by human-animal studies, it is argued that animality is significant to publics in ways that have yet to be sufficiently theorized. The intent of this research is to invite further investigation of the myriad ways in which animal bodies and lives influence public formations in a manner that accounts for and also exceeds human capacity for symbolic communication.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.006
Scholarly communication0.0060.009
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.042
GPT teacher head0.346
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2014
Admission routes2
Has abstractyes

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