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Record W3016237943 · doi:10.1017/s0953820820000060

The Vegan's Dilemma

2020· article· en· W3016237943 on OpenAlexaff
Donald W. Bruckner

Bibliographic record

VenueUtilitas · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsKensington Health
Fundersnot available
KeywordsHarmDilemmaArgument (complex analysis)French hornEnvironmental ethicsLaw and economicsAnimal ethicsPolitical scienceSociologyLawPhilosophyEpistemologyBiology

Abstract

fetched live from OpenAlex

Abstract A common and convincing argument for the moral requirement of veganism is based on the widespread, severe, and unnecessary harm done to animals, the environment, and humans by the practices of animal agriculture. If this harm footprint argument succeeds in showing that producing and consuming animal products is morally impermissible, then parallel harm footprint arguments show that a vast array of modern practices are impermissible. On this first horn of the dilemma, by engaging in these practices, vegans are living immorally by their own lights. This first horn can be avoided by assuming that morality requires not minimizing harm, but only keeping the harm of our actions within some budget. On the second horn, however, we recognize that there are many ways of keeping our harm footprints within budget other than through our dietary choices. On the second horn of the vegan's dilemma, therefore, veganism is not a moral requirement.

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)0.007
metaresearch head score (Gemma)0.018
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: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0050.026
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0080.001

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 head0.008
GPT teacher head0.185
Teacher spread0.178 · 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
GenreOther

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

Citations5
Published2020
Admission routes1
Has abstractyes

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