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Record W2552818835 · doi:10.2527/jas.2016-0805

INVITED REVIEW: Farm size and animal welfare1

2016· review· en· W2552818835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Animal Science · 2016
Typereview
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of Canada
KeywordsBiologyAnimal science

Abstract

fetched live from OpenAlex

Critics of agricultural intensification have argued that the transition from smaller to larger farms has compromised animal welfare. To critically examine evidence relevant to this claim, we reviewed more than 150 publications that examined the relationship between farm size and at least one animal welfare indicator. Although much of this literature focuses on dairy cattle, we also reference other farmed species where appropriate. We found little evidence of any simple relationship, negative or positive, between farm size and animal welfare. Instead, the evidence suggests that larger farms provide some opportunities to improve animal welfare but may also create welfare risks. For example, larger farms permit more specialized and professional management of animal health but can make it more difficult to accommodate outdoor access that some view as integral to animal welfare. Future research should attempt to specify the underlying casual mechanisms by which statistical associations between farm size and indicators of welfare are believed to occur. We also suggest that policy and advocacy efforts aimed at reversing increases in farm size would be better directed toward improving welfare on farms of all sizes.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.101
GPT teacher head0.421
Teacher spread0.320 · 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