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Record W2555232907 · doi:10.1111/phc3.12365

Locating Animals in Political Philosophy

2016· article· en· W2555232907 on OpenAlexaff
Will Kymlicka, Sue Donaldson

Bibliographic record

VenuePhilosophy Compass · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsQueen's University
Fundersnot available
KeywordsPoliticsPolitical philosophyEnvironmental ethicsSociologyMoral philosophyEpistemologySocial philosophyPolitical scienceSocial scienceLawPhilosophySocial relation

Abstract

fetched live from OpenAlex

Abstract While animal rights have been a central topic within moral philosophy since the 1970s, it has remained virtually invisible within political philosophy. This article explores two key reasons for the difficulties in locating animals within political philosophy. First, even if animals are seen as having intrinsic moral status, they are often seen as ultimately distant others or strangers, beyond the bounds of human society. Insofar as political philosophy focuses on the governing of a shared social life, animals are seen as falling outside its remit. Second, even if animals are recognized as members of society, they are seen as lacking the capacities or competences said to be essential for politics, and for membership in the demos. We challenge both assumptions. Many animals live and work alongside us, within an interspecies society, and all members of society should have the right to shape decisions about how that society is governed. An interspecies society requires interspecies politics.

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)0.009
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.057
Scholarly communication0.0080.009
Open science0.0010.006
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.036
GPT teacher head0.258
Teacher spread0.222 · 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 designTheoretical or conceptual
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

Citations19
Published2016
Admission routes1
Has abstractyes

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