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Record W4405024181 · doi:10.3998/phimp.6219

Pets, Power, and Legitimacy

2024· article· en· W4405024181 on OpenAlexfundno aff

Bibliographic record

VenuePhilosophers Imprint · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsnot available
FundersWageningen University and ResearchUniversity of SouthamptonUK Research and InnovationHORIZON EUROPE Framework ProgrammeGovernment of the United KingdomQueen's UniversityHelsingin Yliopisto
KeywordsComputer science

Abstract

fetched live from OpenAlex

This article argues that the relations of social and political power that obtain between humans and pets are illegitimate. We begin by showing that pets, a largely neglected population in political philosophy, are subject to socially and politically organised power, which stands in need of justification. We then argue that pets have three moral complaints against the relations of power to which they are subject. First, our power over pets disrespects their moral independence: the fact that they are not simply available to be used to serve the interests or projects of others. Second, our power over pets systematically sets back their interests in exercising control over their own body, actions, and environment. Third, in subjecting pets to asymmetric relations of power in which they are heavily dependent on humans for the satisfaction of their interests, we subject them to objectionable risks of harm. Together, these complaints support our thesis that the power relations central to the insitution of pet keeping are illegitimate. The practical upshot is that we have a strong moral reason to abolish this institution.

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)0.008
metaresearch head score (Gemma)0.016
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 score0.010
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.070
Scholarly communication0.0090.012
Open science0.0010.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.327
Teacher spread0.291 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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