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Record W2416906263 · doi:10.2527/2001.793634x

The "new perception" of animal agriculture: legless cows, featherless chickens, and a need for genuine analysis.

2001· article· en· W2416906263 on OpenAlexaff
David Fraser

Bibliographic record

VenueJournal of Animal Science · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAgriculturePerceptionAnimal welfareAnimal agricultureEnvironmental ethicsAnimal ethicsProfit (economics)Animal rightsPolitical scienceBusinessPublic relationsPsychologyEconomicsLawBiology

Abstract

fetched live from OpenAlex

A growing popular literature has created a "New Perception" of animal agriculture by depicting commercial animal production as 1) detrimental to animal welfare, 2) controlled by corporate interests, 3) motivated by profit rather than by traditional animal care values, 4) causing increased world hunger, 5) producing unhealthy food, and 6) harming the environment. Agricultural organizations have often responded with public relations material promoting a very positive image of animal agriculture and denying all six of the critics' claims. The public, faced with these two highly simplistic and contradictory images, needs knowledgeable research and analysis to serve as a basis for public policy and individual choice. Scientists and ethicists could provide such analysis. In some cases, however, scientists and ethicists have themselves produced misleading, polarized, or simplistic accounts of animal agriculture. The problems in such accounts include the repetition of unreliable information from advocacy sources, use of unwarranted generalizations, simplistic analysis of complex issues, and glossing over the ethical problems. The New Perception debate raises important and complex ethical issues; in order to provide useful guidance, both scientists and ethicists must consider these issues as research problems that are worthy of genuine investigation and analysis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations103
Published2001
Admission routes1
Has abstractyes

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