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Record W2108181781 · doi:10.1017/s0008423914000195

Unruly Beasts: Animal Citizens and the Threat of Tyranny

2014· article· en· W2108181781 on OpenAlexaff
Sue Donaldson, Will Kymlicka

Bibliographic record

VenueCanadian Journal of Political Science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsQueen's University
Fundersnot available
KeywordsCivilitySociologyAltruism (biology)CitizenshipEnvironmental ethicsReciprocity (cultural anthropology)EmpathyPoliticsSocial psychologyAgency (philosophy)EpistemologyPsychologyPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

Abstract Many commentators—including some animal rights theorists—have argued that non-human animals cannot be seen as members of the demos because they lack the critical capacities for self-rule and moral agency which are required for citizenship. We argue that this worry is based on mistaken ideas about both citizenship, on the one hand, and animals, on the other. Citizenship requires self-restraint and responsiveness to shared norms, but these capacities should not be understood in an unduly intellectualized or idealized way. Recent studies of moral behaviour show that civil relations between citizens are largely grounded, not in rational reflection and assent to moral propositions but in intuitive, unreflective and habituated behaviours which are themselves rooted in a range of pro-social emotions (empathy, love) and dispositions (co-operation, altruism, reciprocity, conflict resolution). Fifty years of ethological research have demonstrated that many social animals—particularly domesticated animals—share the sorts of dispositions and capacities underlying everyday civility. Once we broaden our conception of citizenship to include a richer account of the bases of civic relations, it becomes clear that domesticated animals and humans can be co-creators of a shared moral and political world. We have nothing to fear, and much to gain, by welcoming their membership in the demos.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.011
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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.

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

Citations32
Published2014
Admission routes1
Has abstractyes

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