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Record W28357959 · doi:10.22329/p.v8i2.4093

Nonhuman Animal Rights, Alternative Food Systems, and the Non-Profit Industrial Complex

2013· article· en· W28357959 on OpenAlexvenueno aff
Corey Lee Wrenn

Bibliographic record

VenuePhaenEx · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsAnimal rightsGrassrootsProfessionalizationAnimal welfareEnvironmental ethicsRationalization (economics)Political scienceLaw and economicsBusinessSociologyLawEcologyBiology

Abstract

fetched live from OpenAlex

Alternative food systems (namely the humane product movement) have arisen to address societal concerns with the treatment of Nonhuman Animals in food production. This paper presents an abolitionist Nonhuman Animal rights approach (Francione, 1996) and critiques these alternative systems as problematic in regards to goals of considering the rights or welfare of Nonhuman Animals. It is proposed that the trend in social movement professionalization within the structure of a non-profit industrial complex will ultimately favor compromises like “humane” products over more radical abolitionist solutions to the detriment of Nonhuman Animals. This paper also discusses potential compromises for alternative food systems that acknowledge equal consideration for Nonhuman Animals, focusing on grassroots veganism as a necessary component for consistency and effectiveness.

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)0.004
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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.059
Scholarly communication0.0070.007
Open science0.0010.008
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.218
Teacher spread0.173 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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